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Aviation is often seen as an innovative sector eager to seek technological solutions. It is often assumed that aircraft cockpits have panels with electronic displays and many buttons, some labeled "auto." While this might be the case for commercial aviation (Figure 1), the vast majority of noncommercial civil aircraft cockpits look nothing like these modern cockpits. Non-commercial civil aircraft, known as general aviation (GA), typically have cockpits that mainly consist of analog instruments that show the heading of the aircraft, the altitude, and the air speed (Figure 2). While flying, the pilots make calculations using a compass and an aviation calculator. Due to the slow entry rate of new, glass-cockpit aircraft [1], the composition of the GA aircraft fleet is not going to change any time soon. [ABSTRACT FROM AUTHOR]

This article proposes a hierarchical learning architecture for safe data-driven control in unknown environments. We consider a constrained nonlinear dynamical system and assume the availability of state-input trajectories solving control tasks in different environments. In addition to task-invariant system state and input constraints, a parameterized environment model generates task-specific state constraints, which are satisfied by the stored trajectories. Our goal is to use these trajectories to find a safe and high-performing policy for a new task in a new, unknown environment. We propose using the stored data to learn generalizable control strategies. At each time step, based on a local forecast of the new task environment, the learned strategy consists of a target region in the state space and input constraints to guide the system evolution to the target region. These target regions are used as terminal sets by a low-level model predictive controller. We show how to i) design the target sets from past data and then ii) incorporate them into a model predictive control scheme with shifting horizon that ensures safety of the closed-loop system when performing the new task. We prove the feasibility of the resulting control policy, and apply the proposed method to robotic path planning, racing, and computer game applications. Note to Practitioners—This paper was motivated by the challenge of designing safe controllers for autonomous systems navigating through new environments. We consider scenarios where trajectory data from control tasks in different environments is available to the control designer. Possible applications include autonomous vehicles racing on new tracks or robotic manipulators performing tasks in the presence of new obstacles. Existing approaches to model-based control design for new environments generally use trajectory libraries, systematically adapting stored trajectories to the constraints of the new environment. This typically requires a priori knowledge of the entire task environment as well as resources to store and maintain the growing library. This paper suggests a new hierarchical control approach, in which stored trajectories are used to learn high-level strategies that can be applied while solving the new task. The strategies are learned offline, and only the parameterized strategy function needs to be stored for online control. Strategies only require knowledge of the nearby task environment, and provide navigation guidelines for the system. In this paper we show how to find such strategies from previous task data and how to integrate them into a low-level controller to safely and efficiently solve the new task. We also show how to adapt the modular framework as needed for a user’s desired application. Simulation experiments in robotic manipulator, autonomous vehicle, and computer game examples suggest that our approach can be used in a wide range of applications. In future research, we will address how to adapt the method for time-varying or stochastic environments. [ABSTRACT FROM AUTHOR]

This paper proposes a model predictive current control (MPCC) method of six-phase permanent magnet synchronous hub motor (PMSHM) using auxiliary voltage vectors. First of all, 26 voltage vectors can be obtained from the switching states of six inverters, and 24 auxiliary voltage vectors can be generated by combining them. Second, four virtual voltage vectors can be found through the required locations, and the two vectors with the lowest cost will be selected by cost function. Then, additional current error correction module can better track the current. Finally, the proposed method is compared with the conventional MPCC method and another method with virtual voltage vectors. The innovation of this paper is that the recombination of vectors can better track and predict the current. A current error compensation module is added to reduce the error between the actual current and the predicted current. And the experimental results show that the proposed method has better performance such as smaller torque ripple and current THD both in steady and dynamic states. Finally, the strategy proposed in this paper was applied to the vehicle model through HIL test platform. The possibility of applying the strategy proposed in this paper to pure electric vehicles was verified under New European Driving Cycle (NEDC). [ABSTRACT FROM AUTHOR]

Text is a new way to guide human image manipulation. Albeit natural and flexible, text usually suffers from inaccuracy in spatial description, ambiguity in the description of appearance, and incompleteness. We in this paper address these issues. To overcome inaccuracy, we use structured information (e.g., poses) to help identify correct location to manipulate, by disentangling the control of appearance and spatial structure. Moreover, we learn the image-text shared space with derived disentanglement to improve accuracy and quality of manipulation, by separating relevant and irrelevant editing directions for the textual instructions in this space. Our model generates a series of manipulation results by moving source images in this space with different degrees of editing strength. Thus, to reduce the ambiguity in text, our model generates sequential output for manual selection. In addition, we propose an efficient pseudo-label loss to enhance editing performance when the text is incomplete. We evaluate our method on various datasets and show its precision and interactiveness to manipulate human images. [ABSTRACT FROM AUTHOR]

The muscle synergy hypothesis assumes that the nervous system controls muscles in groups to simplify behavioral tasks, which makes it possible for modularizing motor function assessment. This paper presents a new assessment method based on muscle synergy space (MSS) model to evaluate motor functions after stroke. It consists of spatiotemporal feature module, muscle activation module and synergy activation module, and focuses on the spatial and temporal characteristics of muscle synergies via synergy vectors and activation coefficients. We further applied this method to reveal spatial and temporal characteristics difference of muscle synergy between healthy controls and stroke patients. The effectiveness and accuracy of MSS model were proved by significant positive correlations between Fugl-Meyer score and the total number of optimal synergies of three modules. This measurement methodology could serve as a quantitative indicator for motor function and provide more scientific rehabilitation guidance. [ABSTRACT FROM AUTHOR]

With the large-scale wind power integration into the power system, the inertia and damping characteristics of the system have been weakened, which is not conducive to fulfill the grid-friendly operation of wind power. Aiming at this, an adaptive control scheme combining virtual inertia control (VIC) and supplementary damping controller (SDC) is proposed in this paper. Firstly, the mathematical model of wind grid-connected power system with VIC is established. Secondly, the polytopic linear parameter varying (LPV) system is built to describe the uncertainty of system operating points, and the gap metric-based nonlinear evaluation method is used for polytope vertex configuration. Next, Youla-Kucera parametrization are extended to polytopic LPV system to design an adaptive damping control, in which VIC and SDC are coordinated to provide damping and virtual inertia simultaneously. Finally, the proposed adaptive control scheme is compared with several existing control techniques to validate its effectiveness and advantages in suppressing system oscillation in the modified IEEE 39-bus system integrated with 2 wind turbines. [ABSTRACT FROM AUTHOR]

Finite-control-set model predictive current control (FCS-MPCC) always has large steady-state fluctuation and computational burden. In this paper, a novel FCS-MPCC without a modulator to drive permanent magnet synchronous hub motors (PMSHMs), which combines virtual vectors expansion scheme and duty cycle control was proposed. The lack of a modulator reduces the complexity of the control system. The virtual vectors are synthesized by using active vectors, which improve the accuracy of voltage selection, and further improve PMSHM's steady-state performance and reduce current harmonics. The duty cycle control uses a zero vector to obtain better steady-state performance. However, the duty cycle of the virtual vectors is limited by the synthesis method, and further analysis is needed. A new calculation process is proposed to reduce the amount of calculation. The deadbeat principle is used to get reference voltage which determines sectors. Then, the best voltage vector in the selected sector is determined by the predetermined cost function. The traditional MPCC and the duty cycle MPCC (DCMPCC) are used as a comparison item to compare with the proposed method to illustrate its effectiveness. Results confirm that improved MPCC has good steady-state performance while maintaining a fast dynamic response. [ABSTRACT FROM AUTHOR]

Facial attributes in StyleGAN generated images are entangled in the latent space which makes it very difficult to independently control a specific attribute without affecting the others. Supervised attribute editing requires annotated training data which is difficult to obtain and limits the editable attributes to those with labels. Therefore, unsupervised attribute editing in an disentangled latent space is key to performing neat and versatile semantic face editing. In this paper, we present a new technique termed Structure-Texture Independent Architecture with Weight Decomposition and Orthogonal Regularization (STIA-WO) to disentangle the latent space for unsupervised semantic face editing. By applying STIA-WO to GAN, we have developed a StyleGAN termed STGAN-WO which performs weight decomposition through utilizing the style vector to construct a fully controllable weight matrix to regulate image synthesis, and employs orthogonal regularization to ensure each entry of the style vector only controls one independent feature matrix. To further disentangle the facial attributes, STGAN-WO introduces a structure-texture independent architecture which utilizes two independently and identically distributed (i.i.d.) latent vectors to control the synthesis of the texture and structure components in a disentangled way. Unsupervised semantic editing is achieved by moving the latent code in the coarse layers along its orthogonal directions to change texture related attributes or changing the latent code in the fine layers to manipulate structure related ones. We present experimental results which show that our new STGAN-WO can achieve better attribute editing than state of the art methods. [ABSTRACT FROM AUTHOR]

Intelligent traffic light control is one of the modern approaches to solve traffic congestion, where reinforcement learning is a widely used method. Conventionally, reinforcement learning is used to determine whether to change the current phase (or choose a traffic phase) after each small interval. One major drawback of these approaches is that it makes the current traffic light phase duration uncertain before the current phase terminates. Directly determining the duration of the traffic light phase can effectively avoid this shortcoming. An adaptive traffic light timing system is proposed in this paper which can directly control the phase duration. In the proposed system, the Q-learning algorithm is employed and the action space is defined as all possible phase durations. In addition, the reward function is redefined to guide the agent to balance more traffic metrics, and the state is redefined to reduce the state space. Finally, the proposed system is evaluated by equal, unequal, and complex traffic scenarios. Results show that the proposed system has a better performance compared with other methods in controlling traffic lights, even on complex traffic scenarios. [ABSTRACT FROM AUTHOR]

Generative adversarial networks have achieved great success in unpaired image-to-image translation. Cycle consistency, a key component for this task, allows modeling the relationship between two distinct domains without paired data. In this paper, we propose an alternative framework, as an extension of latent space interpolation, to consider the intermediate region between two domains during translation. It is based on the assumption that in a flat and smooth latent space, there exist many paths that connect two sample points. Properly selecting paths makes it possible to change only certain image attributes, which is useful for generating intermediate images between the two domains. With this idea, our framework includes an encoder, an interpolator and a decoder. The encoder maps natural images to a convex and smooth latent space where interpolation is applicable. The interpolator controls the interpolation path so that desired intermediate samples can be obtained. Finally, the decoder inverts interpolated features back to pixel space. We also show that by choosing different reference images and interpolation paths, this framework can be applied to multi-domain and multi-modal translation. Extensive experiments manifest that our framework achieves superior results and is flexible for various tasks. [ABSTRACT FROM AUTHOR]

The three main modules of autonomous vehicles, i.e., sensing, decision making, and motion controlling, have been studied separately in most existing works on autonomous driving, which overlook the correlations among these modules, leading to a result of unsatisfactory performance. In this paper, we propose a novel scheme that first tactfully processes the sensing data, then jointly learns and optimizes the decision-making and motion-controlling using reinforcement learning (RL). Specifically, the proposed scheme designs a novel state representation mechanism, where the sensing data goes through the attention layer and the convolutional neural network (CNN) layer sequentially. The attention layer focuses on extracting the most important local information and then CNN layer takes a broad view to comprehensively consider the global information for a better representation. Furthermore, the proposed scheme jointly learns decision-making and motion-controlling, therefore, the relevance of these two modules is implicitly considered, which helps to achieve a better autonomous driving policy. Extensive simulation results show that the proposed scheme is better than classic control methods and some RL methods in terms of safety, velocity, etc. We also demonstrate the respective functions of the attention layer and the CNN layer through ablation studies. Finally, we construct a traffic scene with a real autonomous vehicle, and verified the feasibility of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper briefly reviews the common-mode voltage (CMV) and neutral point (NP) voltage for neutral point clamped three-level inverter (NPC TLI). Then, the space vector pulsewidth modulation (SVPWM) and traditional virtual SVPWM (VSVPWM) are discussed in terms of these two issues, revealing the drawbacks in reducing CMV or eliminating NP voltage oscillation. A novel virtual space vector modulation, named as RCMV_VSVPWM, is proposed in this paper to reduce CMV and eliminate NP voltage oscillation for NPC TLI. By selecting vectors with lower CMVs, a set of novel virtual voltage vectors are generated. The highlight of the method is zero average NP current in one control cycle and lower CMV. Furthermore, the active NP voltage control suitable for RCMV_VSVPWM is presented and evaluated. The corresponding experimental results are given, which are well-consistent with theoretical analysis. [ABSTRACT FROM AUTHOR]

This paper presents a novel method, advisory dynamic programming (AD-DP), for power management of a fuel cell hybrid vehicle (FCHEV). The presented method embraces a new understanding of vehicle states as driver-dependent and -independent states in time domain to define a suitable state space to be used for dynamic programming. Driver-dependent states are defined in terms of multiple characteristic parameters for vehicle speed and power demand, corporately. Driver-independent states are defined in terms of discrete values for supercapacitor's state of charge $SoC_{sc}$. Transition costs between all states in the state space are calculated offline and tabulated in look-up tables for online implementation. A state predictive model is developed based on the transition statistics of driver-dependent states for a suitable number of driving cycles. Backward calculation of the total transition cost for the predicted horizon in state space is used to define optimal power split strategy for the powertrain. The formulation of optimal control problem, in terms of situation-based solutions related to vehicle states, enables a significant reduction of computational steps and hence addresses the main challenge of real-time applications. The algorithm is adapted in terms of optimization horizon and number of discrete states for DIS to suit the real-time application. Experimental application of AD-DP, using an emulation test-rig, is conducted over different driving cycles. The obtained results reveal an improvement in energy efficiency up to 29% compared to the adaptive rule-based method. The contribution of this paper can be identified as: first, development of a corporate definition for vehicle states, that can be further implemented in optimization-based power management methods. Second, the formulation of an adaptive DP that requires lower computational steps and hence suits real-time applications in hybrid electric vehicles. [ABSTRACT FROM AUTHOR]

Knowledge transfer is a promising concept to achieve real-time decision-making for autonomous vehicles. This paper constructs a transfer deep reinforcement learning (RL) framework to transform the driving tasks in the intersection environments. The driving missions at the unsignalized intersection are cast into a left turn, right turn, and running straight for automated vehicles. The goal of the autonomous ego vehicle (AEV) is to drive through the intersection situation efficiently and safely. This objective promotes the studied vehicle to increase its speed and avoid crashing other vehicles. The decision-making policy learned from one driving task is transferred through three transfer rules in another driving mission and evaluated. Simulation results reveal that the decision-making strategies related to similar tasks are transferable and have a high success rate. It indicates that the presented control framework could reduce time consumption and realize online implementation. Therefore, the transfer RL concept is helpful for establishing the real-time decision-making policy for autonomous vehicles. [ABSTRACT FROM AUTHOR]

In a human–robot coexisting environment, reaching the target place efficiently and safely is pivotal for a mobile service robot. In this paper, a Risk-based Dual-Tree Rapidly exploring Random Tree (Risk-DTRRT) algorithm is proposed for the robot motion planning in a dynamic environment, which provides a homotopy optimal trajectory on the basis of a heuristic trajectory. A dual-tree framework consisting of an RRT tree and a rewired tree is proposed for the trajectory searching. The RRT tree is a time-based tree, considering the future trajectory predictions of the pedestrians, and this tree is utilized to generate a heuristic trajectory. However, the heuristic trajectory is usually nonoptimal. Then, a line-of-sight (LoS) control checking algorithm is proposed to detect whether two time-based nodes can be rewired with the least cost. On the basis of the LoS control checking algorithm, a tree rewiring algorithm is proposed to optimize the heuristic trajectory. The tree generated in the tree rewiring process is called the rewired tree. The trajectory generated by the Risk-DTRRT algorithm proves to be optimal in the homotopy class of the heuristic trajectory. The navigation run time and the lengths of the planned trajectories are selected to demonstrate the effectiveness of the proposed algorithm. The experimental results in both simulation studies and real-world implementations reveal that our proposed method achieves convincing performance in both static and dynamic environments. Note to Practitioners—This paper is motivated by planning optimized trajectories for the mobile service robots in dynamic environments with pedestrians. In this area, the sampling-based motion planning algorithms have been widely used for their high efficiency and robustness. However, the real-time optimality of the motion planning cannot be guaranteed due to the challenges caused by the moving pedestrians. In this paper, we propose a dual-tree framework to solve this problem. First, a classic Rapidly exploring Random Tree (RRT) is constructed to generate a heuristic trajectory. Then, instead of reconnecting the nodes on the heuristic trajectory directly, a rewired tree is built to optimize the heuristic trajectory. This proposed dual-tree framework can fully exploit the information of the RRT tree and ensure the completeness of the motion planning. The proposed motion planning algorithm also considers the constraints of the nonholonomic mobile robots, and it can be applied in most mobile service robots to improve their motion planning quality. [ABSTRACT FROM AUTHOR]

The aviation industry pursues the integration of fuel cells (FCs) to reduce pollutant emissions. Their connection to the on-board power supply leads to new requirements for electrical grid protection. The limited short-circuit current of a weight-optimized FC system cannot trip a standard fuse. Hence, in this paper, a new protection device is developed as an under/overvoltage primary protection. The proposed device consists of three basic elements: relay; differential amplifier; and current source. This paper includes a detailed description of the protections design process, which includes a requirement analysis, a detailed robustness consideration, and an experimental validation of a developed prototype. [ABSTRACT FROM AUTHOR]

This paper presents an overview of technology related to on-board microgrids for the more electric aircraft. All aircraft use an isolated system, where security of supply and power density represents the main requirements. Different distribution systems (ac and dc) and voltage levels coexist, and power converters have the central role in connecting them with high reliability and high power density. Ensuring the safety of supply with a limited redundancy is one of the targets of the system design since it allows increasing the power density. This main challenge is often tackled with proper load management and advanced control strategies, as highlighted in this paper. [ABSTRACT FROM AUTHOR]

This paper deals with the innovative “variable-voltage” bus concept for future more-electric aircraft platforms. Using new functionalities and opportunities offered by innovative sources actively controlled by power electronics, there is an opportunity for a significant increase of their output power (within powertrain capabilities, machine thermal limits, and power converter maximum current) to supply increased load demands under certain conditions. This paper investigates applications of this concept to satisfy power demands for the wing ice-protection system for business jet. The study includes a detailed study into the control challenges of the proposed approach and suggests corresponding theoretical solutions. Furthermore, the controller design aspects are explored with considerations to achieve stable operation. The concept is tested in simulation environment and validated through experimental studies. This paper might be of interest for the researchers and engineers focused on innovative solutions for future aircraft platforms. [ABSTRACT FROM AUTHOR]

Steered particles offer a method for targeted therapy, interventions, and drug delivery in regions inaccessible by large robots. For example, magnetic actuation of particles has the benefits of requiring no tethers, being able to operate from a distance, and in some cases allows imaging for feedback (e.g., MRI). This paper investigates position control of particles using uniform forces (the same force is applied everywhere in the workspace). Given a controllable field that can generate bidirectional forces in three orthogonal directions, steering one particle in three-dimensional (3-D) is trivial. Adding additional particles to steer makes the system underactuated because there are more states than control inputs. However, the walls of in vivo and artificial environments often have surface roughness such that the particles do not move unless actuation pulls them away from the wall. In the previous work, we showed that the individual two-dimensional (2-D) position of two particles is controllable using global inputs in a square workspace with nonslip wall contact. Because in vivo environments are usually not square, this paper extends the previous work to all convex workspaces, and shows how this could be extended to 3-D positioning of neutrally buoyant particles. We investigate analytically an idealized variant of this problem with nonslip boundaries and control inputs that are applied uniformly to all particles in the workspace. This paper also implements the algorithms in 2-D using a hardware setup inspired by the gastrointestinal tract. [ABSTRACT FROM AUTHOR]

The postcapture of a partially failed spacecraft by space manipulators will bring a mutation in the dynamics of the combination. Both the inertia properties and the thruster configuration matrix will change significantly. The unknown dynamics of the partially failed spacecraft also cause a tremendous technical challenge for attitude takeover control. Accordingly, this paper describes a novel reconfigurable control system for postcapture attitude takeover of a partially failed spacecraft with parametric uncertainties, whose fuel has been exhausted or whose actuators have partial malfunctions. First, the reconfigurable control law is designed by command filtering adaptive back-stepping control to guarantee the system performance and global asymptotic stability considering inertia parametric uncertainties. Second, the thrusters are reconstituted, without changing the thruster physical configuration. Finally, the thrusters’ forces can be redistributed by the dynamic control reallocation method based on constrained quadratic programing. Numerical simulations validate the feasibility of the proposed approach for postcapture attitude takeover control of a partially failed spacecraft with parametric uncertainties. Note to Practitioners—This paper presents a methodology for a partially failed spacecraft with parametric uncertainties. It focuses on solving the attitude takeover control of the partially failed spacecraft perfectly, while considering the position and speed constraints of the actuator and avoiding the plume impact to the spacecraft. The proposed command filtering adaptive back-stepping control can be used for spacecraft’s thruster reconfiguration considering the parametric uncertainties. Furthermore, the dynamic control reallocation method is particularly useful for future applications that include spacecraft with redundant actuators. [ABSTRACT FROM AUTHOR]

This paper presents a control approach for an overground lower limb exoskeleton that is intended to provide guidance and assistance to poorly ambulatory individuals during walking without unduly interfering with their ability to maintain balance. The control approach achieves these objectives by emulating a viscous flow field acting on the lower limb joints. The extent to which the control approach achieves the objectives was assessed in experiments, conducted on five healthy subjects, comparing guidance and disturbance characteristics of the velocity-based controller to a potential-field-based controller. Results show that the flow controller provides a combination of lower guidance error and lower disturbance to the user, relative to the potential-field-based controller. The paper also discusses various potentially beneficial characteristics of the flow controller, such as first-order homogeneous behavior, implicitly combined guidance and assistance behaviors, and improved directionality in error correction relative to a potential-field-based controller. [ABSTRACT FROM AUTHOR]

This paper proposes a unified control based utility-interactive uninterruptible power converter (UIUPC). The proposed control enables the UIUPC to inherently transfer from a $ p-q$ control strategy in grid-connected mode to a voltage–frequency control strategy in autonomous mode and vice-versa. This happens seamlessly with the same control topology. The need to switch between two separate control architectures is thus eliminated. Critical islanding detection and synchronizing mechanisms are also not needed in the proposed control method. The unified controller proposed in this paper is derived from the concept of controlling the perturbations in the magnitude and speed of the point of common coupling (PCC) space vector. The PCC space vector is compared with a reference space vector applied in the direction of the PCC space vector on an instantaneous basis to extract the perturbations. The reference system of the proposed control is linked to the dynamics of the PCC space vector. This offers the ability of parallel operation of similar unified control UIUPC. Thus, in addition to the above said advantages, the proposed control also puts forth an alternative to paralleling approaches like conventional droop and master–slave configurations. The effectiveness of the proposed control is validated by simulation and experimentation. [ABSTRACT FROM AUTHOR]

Avionics and air traffic management (ATM) systems are evolving with the introduction of progressively higher levels of automation, toward attaining the ambitious operational, technical, and safety enhancements required to sustain the present growth of global air traffic. This paper presents novel 4-Dimensional Trajectory (4DT) functionalities that are being developed for integration in ATM and avionics systems to support trajectory based operations (TBO). The 4DT planning process, which is the main focus of the paper, is supported by a custom multiobjective variant of state-of-the-art optimal control algorithms, incorporating various operational, economic, and environmental factors. Capitalizing on the higher theoretical accuracy offered by optimal control algorithms compared to other methods, a key feature of the proposed approach is the introduction of a postprocessing stage to ensure that the mathematically optimal trajectories are translated into a set of standardized 4DT descriptors, which can be flown by state-of-the-art automatic flight control systems. Additionally, to support air-ground 4DT intent negotiation and validation in the TBO context, the 4DT postprocessing ensures that optimal trajectories are synthetically described by a limited number of parameters, minimizing the bandwidth requirements imposed on airborne data links. Simulation-based verification activities addressing operational efficiency improvements and computational performance in the terminal area ATM context support the viability of the proposed 4DT planning functionality for online tactical TBO. [ABSTRACT FROM AUTHOR]

This paper describes a high-performance neutral point voltage balancing technique for a neutral point clamped (NPC) converter. Conventional neutral point voltage balancing methods do not function well under low power factor, low pulse ratio, and near-unity modulation index operation conditions. These conditions are essentially dominant operation conditions for aircraft starter/generator systems. This paper introduces an alternative space vector modulation technique for three-level NPC converters in an aircraft starter generator system. The selection of voltage space vectors is optimized for high modulation index and low power factor operation. Disturbances caused by a low pulse ratio are also compensated. The proposed method maintains neutral point voltage balance and ripple minimization over the full range of operating conditions. This paper also provides a detailed analysis of the sources of neutral point voltage imbalances and ripples in high-speed drives with deep flux weakening. Simulation results obtained from a Simulink/PLECS model and experimental results obtained from a 45 kVA, 32 krpm aircraft starter generator test rig prove that the proposed method eliminates the neutral point voltage imbalance and significantly reduces the neutral point voltage ripple. [ABSTRACT FROM AUTHOR]

This work investigates energy-optimal motion planning for a class of multiaxis motion systems where the system dynamics are linear time-invariant and decoupled in each axis. Solving the problem in a reliable and efficient manner remains challenging owing to the presence of various constraints on control and states, nonconvexity in its cost function, and obstacles. This paper shows how the cost function can be convexified by considering the system dynamics, while decomposing decision variables to obtain a convex representation of collision avoidance constraints. With the convexified cost function and constraints, the original problem is decomposed into two quadratic programming (QP) problems. An alternating quadratic programming (AQP) algorithm is proposed to solve both the QP problems alternatingly and iteratively till convergence. Requiring an initial feasible trajectory as a guess, AQP necessarily converges to an energy-efficient solution that is homotopic to the initial guess. Under certain circumstances, AQP is guaranteed to produce a local optimum. Simulation demonstrates that AQP is computationally efficient and reliable while claiming comparable energy saving as the mixed-integer QP approach. Note to Practitioners—This paper presents an energy-optimal motion planning algorithm that can be easily implemented on a class of multiaxis motion systems. Main advantages of the proposed algorithm are: 1) it produces a trajectory resulting in lower but comparable energy efficiency as the global optimum; 2) it is guaranteed to provide an energy-efficient and constraint-compliant trajectory, and thus is reliable; 3) it requires a low computational load and can be deployed on a wide range of applications; and 4) its implementation is straightforward to any engineer with basic knowledge of numerical methods. [ABSTRACT FROM AUTHOR]

Rising power demands in more electrical aircraft (MEA) put power converters for commercial airplanes under increasing pressure to fulfill current harmonic distortion regulations as specified, for example, in DO-160G. Today, the implementation of filters is seen as an effective tool for dealing with harmonics; however, their increased weight and volume are not welcomed in the aerospace industry. This paper proposes a circuit, named forced commutation controlled series capacitor (FCSC-rectifier), which is able to maintain low individual harmonic current levels without the need for filter components. The FCSC-rectifier includes a variable capacitive line reactance that interacts in a controlled manner with the inductive line impedance. The result is that the converter input current is nearly purely sinusoidal with a power factor of almost unity. The FCSC-rectifier is to be used for stand-alone variable-voltage, variable-frequency generation systems and can, therefore, power the full authority digital electronic control system (FADEC) in an MEA. This paper shows that the FCSC-rectifier can maintain a high power factor and acceptable current harmonic levels without the use of filters, despite large voltage and frequency variations. A full description of the circuit modes of operation is presented in this paper together with simulation results showing circuit performance characteristics over a range of voltages and frequencies. Results are experimentally verified using a 1-kW test circuit. [ABSTRACT FROM AUTHOR]

Power converters and electric motor drives when tightly regulated behave as constant power loads. These loads are different from resistive loads and have destabilizing negative impedance characteristics, which impact a system's stability. A boost converter is intrinsically nonlinear and is a nonminimum phase system at the output voltage with respect to the control input. The linear approximation of this boost converter loaded with a constant power load has a zero and poles in the right half of the $s$ -plane, making the system unstable and very difficult to control. Control techniques that employ some form of system inversion cannot be implemented for a nonminimum phase system. This paper describes a technique to modify the nonminimum phase boost converter to a minimum phase for a constant power load, further implementing the input–output linearization technique to stabilize the system. This paper also provides a methodological analysis of the problem followed by the proposed solution. Furthermore, it verifies the analysis of the proposed solution through simulation and experimental results. [ABSTRACT FROM AUTHOR]

This paper proposes an optimal design of quadrature-shaped pickup to satisfy various demands on performance at special positions for omnidirectional wireless power transfer (WPT). Omnidirectional WPT technology as a brand new way of energy supply has shown great potentials for charging objectives at all directions. In order to ensure the energy can be transmitted to arbitrary spatial directions, the orthogonal structure of three circular transmitting coils has been widely accepted matched with non-identical current control scheme. However, there are still some special positions where the transmitted power drops to the bottom which is not suitable for applications. Accordingly, this paper proposes an optimal design analysis for the quadrature-shaped pickup to satisfy different demands on either power or efficiency at such positions. The simulated analysis and experimental results are both given to verify the enhancement of the proposed quadrature-shaped pickup, which aims to provide a reference to fabricate an appropriate pickup up for utilizations. [ABSTRACT FROM AUTHOR]

In this paper, a novel robust fault detection (FD) approach called parity space vector machine (PSVM) is proposed for linear discrete-time systems. Aiming to achieve a tradeoff between false alarm rate (FAR) and FD rate (FDR) simultaneously, we focus our study on an integrated design of parity space-based FD in the context of residual generation and residual evaluation. Without a prior knowledge of the distribution of the unknown inputs, we propose to construct a PSVM model and formulate the underlying FD problem as a distribution-free Bayes optimal classifier, where the FAR and FDR indicate the worst-case classification accuracies of future residuals for the fault free case and faulty case. Then a bank of parity space vectors and corresponding thresholds can be designed integratedly by applying the techniques of the minimum error minimax probability machine and, at the same time, an optimal tradeoff between FAR and FDR is achieved. Finally, the effectiveness of the proposed approach is demonstrated on a longitudinal control system of unmanned aerial vehicle and further comparison with a traditional parity space-based FD is also addressed. [ABSTRACT FROM AUTHOR]

In this paper, the modeling and control problem of an overhead crane equipped with a three-dimensional (3-D) variable length flexible cable is discussed. In order to achieve high control performance, a partial differential equation (PDE) model is deduced with exactly preserving high frequency modes of the original system. For the sake of dealing with the effect of input amplitude and rate constraints, a boundary control scheme is carried out to drive the payload to a desired position with the 3-D vibration reduction of the variable length cable by applying the backstepping technology. The exponential stability of the closed-loop system is demonstrated based on the Lyapunov’s direct method. The simulation results verify the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This article presents an optimal model predictive flux control (MPFC) for a two-level inverter fed induction motor. Integrating discrete SVM into FCS-MPFC enhances the performance of the IM drive. However, conventional DSVM-MPFC requires to enumerate and evaluate a higher number of virtual vectors in the prediction loop. In this paper, a high-efficient and low complexity voltage selection method is proposed to reduce the number of candidate voltage vectors from 38 to 15 without any suboptimality. Both steady-state and transient performances of the proposed method remain the same as the 38-vector based conventional DSVM-MPFC, producing the same cost-function values in all operating conditions. Furthermore, an online switching frequency reduction technique is proposed to achieve a minimum commutation per inverter vector change within each sampling cycle and between adjacent cycles. By appropriately arranging the sequence of real voltage vectors in each sampling cycle, a lower average switching frequency is achieved. The proposed switching frequency reduction method decreases the switching losses without compromising the performance of DSVM-MPFC as only the applied sequences of the real voltage vectors are optimized. Experimental studies are conducted to verify the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Toward wireless medical microrobot applications driven by an electromagnetic actuation (EMA) system, challenges associated with movability, the electromagnetic force, and the coil system size must be addressed. This paper presents an enhanced EMA system with a higher magnetic field via new coil configurations, an independent magnetic field control method, and application to the multi-degree-of-freedom (DOF) motion of an untethered capsule endoscope. The magnetically actuated capsule endoscope (MACE) system proposed herein consists of an endoscopic capsule with a permanent magnet in the body, eight air-cored stationary electromagnetic coils, and a control system. The coil system is designed to maximize the working space available within a limited equipment space. The MACE is designed to perform full 5-DOF motion, including 3-DOF translation and 2-DOF rotation. The independent magnetic field control method with the new coil configuration enables orientation-independent-driving (OID) control of the capsule endoscope that could not be accomplished by previous EMA systems. The developed system performance was verified by simulations and experiments. The MACE motion in the spatial domain was evaluated with a robotic endoscopic procedure and diagnostic performance by in-vitro and ex-vivo experiments. [ABSTRACT FROM AUTHOR]

One fundamental yet challenging issue in security control for resilient complex networks is to construct distributed control laws for the networks to perform various cooperative tasks in the presence of failures and attacks, where resilient indicates that the complex networks are exposed to the environment with cyber uncertainties and malicious adversaries. This is particularly important in today’s critical infrastructure networks since most of them are vulnerable to attacks in the era of the Internet. Inspired by this observation, this paper focuses on synchronization control for resilient complex networks subject to cyber and physical attacks, where the states of nodes being attacked may change abruptly (i.e., the synchronization error may suffer impulsive disturbances), and some nodes as well as their corresponding connections may not work in some instances. Suppose that a smart control center is equipped in the considered network to detect the attacks in real time. Furthermore, the nodes and communication channels are assumed to be recovered through some repair work after detecting the attacks. On the theoretical side, by using the ${M}$ -matrix theory, we get a few sufficient criteria to guarantee the achievement of secure synchronization against attacks on both nodes and communication links. On the algorithmic side, security control algorithm and architecture are proposed to select the coupling strength and the feedback gain matrix to realize synchronization. Finally, we perform two simulation examples to validate our theoretical results. [ABSTRACT FROM AUTHOR]

Most studies so far on trajectory tracking control of autonomous underwater vehicle (AUV) have assumed that the Euler angles are exactly known. However, the AUV inevitably suffers from external environmental disturbances which are driven by wind, density, and temperature gradients. The attitude transducers cannot derive accurate attitude information of the AUV. Additionally, the uncertain hydrodynamic parameters affect the stability of the system. Consequently, it is unknown whether tracking performance of the AUV can be guaranteed. In order to overcome these drawbacks, in this paper, a finite-time controller is developed by using the nonsingular fast terminal sliding mode control technique. A robust differentiator is proposed to estimate the external disturbances and uncertain parts. Simulations are performed to show that with the proposed control laws, the AUV converges to the desired trajectory even in the presence of external disturbances and system uncertainty. [ABSTRACT FROM AUTHOR]

The optimal control of the heating, ventilation, and air-conditioning (HVAC) system in buildings has a significant energy saving potential and therefore is of a great practical interest. An event-based HVAC control adjusts control actions when certain events occur, which may be faster and more scalable than state-based or time-driven control methods. However, events may capture either local or global changes in the rooms. The choice of events is a tradeoff between the computational efficiency and the control performance. This challenging problem remains open. We consider this as an important problem in this paper and make three major contributions. First, we define local and global events for the HVAC control problem. The complexity of these event-based control policies is defined. Second, based on hypothesis testing, we develop a method to select events that capture a sufficient state information and with a relatively small event space. Third, we demonstrate the performance of this method on two groups of examples, including one group of small-scale problems for the proof of concept and the other group of large-scale problems in the HVAC control. It is shown that our method outperforms the Levin search, which is a traditional complexity-based search method and finds event-based HVAC control policies with a good performance. Note to Practitioners—When there are multiple rooms in a building, the HVAC control may achieve a significant energy saving and an indoor comfort satisfaction in the same time through exploring the coupling among the rooms. By appropriately defining the events, the size of the event space is usually much smaller than the state space. Therefore, an event-based control is more scalable and preferred in practice. Local events capture the state changes of rooms in a small neighborhood, which leads to a small event space but limited information. Global events capture the state changes of rooms in a large neighborhood, which leads to more information but a large event space. It remains open how to select events in large-scale HVAC control problems, especially when the computing budget is limited. In this paper, we define the complexity of an event-based control policy by the number of neighboring rooms considered. We develop a method based on hypothesis testing to select events with a proper complexity in order to achieve a good system performance. The performance of this method is demonstrated on an HVAC control problem. [ABSTRACT FROM AUTHOR]

This paper evaluates the error rate of a memory-bound application implemented in different commercial-off-the-shelf multicore and many-core processors. To achieve this goal, two quantitative experiments are performed: fault-injection campaigns and radiation ground testing. In addition, this paper proposes an approach for predicting the application error rate by combining the results issued from both types of experiments. The usefulness of the approach is illustrated by three case studies implemented in processors having different manufacturing technologies and architectures: 45-nm silicon-on-insulator (SOI) free-scale P2041 quad-core processor, 65-nm CMOS Adapteva Epiphany multicore processor, and 28-nm CMOS Kalray multipurpose processing array-256 many-core processor. The reliability of the processors for avionics is obtained from their experimental error rates extrapolated to avionic altitudes. Reliability curves are plotted for observing the prediction accuracy. A comparison of the failure in time of the selected processors shows that the greater single-event effect vulnerability of CMOS technology compared with the SOI one can be compensated with the implementation of effective error detection and correction. These protection mechanisms allow the use of CMOS devices having huge memory capacity in applications operating in severe radiation environments. [ABSTRACT FROM AUTHOR]

Tolerance is an essential part of design and manufacturing. It plays a key role in product quality and manufacturing costs. Understanding and controlling production variations on key geometric features can provide firms with a competitive edge. A model to link production variation to tolerance is highly desirable but difficult to build, especially for deformable parts with complex surfaces. Inspired by an innovative idea of volumetric space envelope (constructed from a base parametric curve), this paper proposes a novel spatial tolerance model. In this proposal, a volumetric envelope is superimposed onto the target manufacturing part, whose deformation and deviation (during manufacturing or assembly) are viewed as spatial variation, and this variation is modeled and linked to movements of envelope’s control points. This unique model design bypasses direct modeling of complex intrapart interactions, which is nonlinear in general and a major source of inaccuracy and low efficiency of many existing methods. The adopted indirect modeling brings many benefits. It can handle complex shapes and surfaces, and is able to take into account form errors. Also, it is capable of modeling both global and local variations observed in many practical cases. The new method is illustrated and verified through an example on a deformable vehicle door hinge plate. The proposed model shows application potential in every major stage of production, and makes possible to build a coherent cross-production life-cycle tolerancing framework from the early stage design, to manufacturing, to postproduction quality inspection. Note to Practitioners—Tolerance is a matter of everyday life to manufacturing and assembly engineers and designers. It directly impacts the product quality and production costs. Driven by the client’s ever-increasing variety needs, more and more deformable parts with complex surfaces have been entering into production in the past decade. However, existing degree of freedom (DOF) concept-based models, surrounding the idea of six DOFs of a rigid body, have difficulty in handling. While the decomposed type of models may help provide useful insight into the geometric variation, they are dependent on reliable measurement data, which may not be readily available. Motivated by the idea of deforming a manufacturing part indirectly through reshaping its surrounding (purposely designed) parametric space envelope (PSE), this paper proposes a novel spatial model for tolerancing. The proposed model is intuitive and is able to provide insight into geometric variations by visualizing them. Due to its novel model design, the proposed method can handle some fairly complex parts and surfaces (be it parametric or implicit) and is able to take into account form errors. The base curve to construct the PSE can be a Bezier curve, which is commonly available in computer-aided design/computer-aided manufacturing systems and is familiar to many practitioners (designers and engineers). This could substantially lower the application hurdle and open up a potentially wide application for the proposed method. [ABSTRACT FROM AUTHOR]

This paper discusses a new control approach for robotic-assisted tele-echography. The control architecture follows a hierarchical approach, where explicit Cartesian force control arises as the primary task while orientation control is designed in the null space. The robot dynamics is driven by a 3-D time-of-flight camera and a force sensor. Based on depth camera and force data, contact stiffness is anticipated, allowing control adaptation before contact. This approach is adequate for tele-echographic tasks since it reduces robot dynamics before contact, enabling a smooth transition from free space to contact and vice versa. In contact, the environment stiffness is estimated online using force data and the manipulator inertial properties. A strong correlation between the stiffness perceived by the controller and the effective mass exists, being this correlation used in the estimation algorithm to improve force control performance. A set of experiments assess the control architecture, highlighting the relation between perceived stiffness and robot effective mass, including also clinical validation. Note to Practitioners—The teleoperation control architecture described in this paper relies on computed-torque techniques that take into account robot dynamics, contact stiffness estimation, task-space formulation, and null-space design. Our application is on the medical field, where a physician telecontrols a robot to obtain ultrasound images from a patient. The robot exhibits compliant behaviors in Cartesian space (for safety reasons) managed by the task-space formulation, and stiffer behaviors in orientation control managed by null-space design. This approach allows accurate orientation control with compliant positioning which is adequate for this type of teleoperation tasks. Due to free space and contact interactions, the proposed control approach anticipates the contact stiffness relying on vision sensing, adapting the control gains accordingly. While in contact, the perceived stiffness has a strong correlation with the effective mass, which is used together with force data for its estimation. This strategy allows slowing down robot dynamics toward contact, guaranteeing a smooth behavior, entailing also high-quality force tracking while in contact. All control details are described in this paper, allowing easy implementation not only for this specific context, but also for other telemanipulation architectures that require remote delicate handling, without jeopardizing force control and orientation control performances. [ABSTRACT FROM AUTHOR]

Fast-switching power converters are a key enabling technology for the more electric aircraft (MEA), but the generated electromagnetic interference (EMI) poses significant challenges to the electrification effort. To meet the stringent aerospace EMI standards, passive filters are commonly employed, despite the weight and size constraints imposed by the MEA. Alternatively, the EMI source, i.e., the high dv\text/ dt and di\text/ dt slew rates, can be addressed through waveform-shaping techniques. For example, while most soft-switching converters can reduce switching loss, they do so by switching the semiconductor devices in a slower and smoother manner, resulting in the attenuation of high-frequency harmonics. This paper examines the auxiliary commutated pole inverter (ACPI) topology, and its first contribution is the attenuation of the high-frequency content of its EMI source, that is, the output voltage, in a predictable manner, through the active control of the resonant circuit. This is achieved by first, discussing the time-domain characteristics of trapezoidal and S-shaped pulse-trains that lead to attenuated high-frequency harmonic content, and second, by analyzing the equivalent LC circuit of the ACPI. The design of the inverter is then focused on the active control of the resonant parameters, for a predetermined and enhanced output voltage high-frequency response. The second contribution of this paper is the comparison of the EMI performance of hard switching and of three soft-switching modes, fixed-timing control, variable-timing control, and capacitive turn-offs, and how this informs important metrics such as power efficiency, current stress, and implementation complexity. Finally, the third contribution is on the trade-offs that arise when the primary design goal is enhanced EMI performance as opposed to switching loss reduction. A 5-kW, 3-phase ACPI prototype is used for validating the high-frequency content attenuation at source. It is shown that the ACPI can achieve a 37 dB harmonic attenuation of its output voltage at 4 MHz, compared to a hard-switched inverter. [ABSTRACT FROM AUTHOR]

Controlled force–torque exertion by a small-scaled free-flying space robot will be potentially required for future on-orbit assembly missions. This paper presents a hybrid controller to achieve the desired end-effector motion and contact forces required for driving a screw into a floating target. Attitude of the spacecraft base is controlled simultaneously. Postcapture control to stabilize the entire system is also addressed in this paper. Simulation results have demonstrated the effectiveness of the proposed control laws. [ABSTRACT FROM AUTHOR]

In this paper, a new in-flight alignment (IFA) method of the integrated inertial navigation system (INS) and global positioning system (GPS) is proposed for the aerial mapping applications. The integrated INS/GPS measurement system is used to provide attitude information and, based on this, the exterior orientation parameters can be derived for the purpose of direct georeference of the airborne imagery. The IFA plays an important role in achieving high accuracy of attitude estimation. However, the statistics of INS noise is usually time-varying and seriously degrades the estimation accuracy in practice. In order to solve the problem, two strategies are taken into account in the paper. First, an adaptive estimation algorithm is developed by adjusting the window size of data processing in IFA, so that the covariances of INS noise can be estimated and updated online to improve the state estimation performance. Second, a strong tracking filter is applied to guarantee the convergence of the IFA algorithm as well as its robustness against parameter perturbations and trajectory maneuvers. Finally, an aerial mapping experiment is implemented, and the results demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

A parity space approach to monitoring and fault detection and identification of systems in nuclear power plants (NPPs) can be beneficial. However, if the number of fault classes exceeds the total independent residual signatures, the parity space method needs to be further enhanced to achieve the optimal fault classification. This situation happens frequently in NPP applications, where the safety and reliability are paramount. A possible enhancement proposed in this paper is to combine Fisher discriminant analysis with the parity space method to maximize the scatter among different fault classes, while minimizing the scatter within each class. Under identical conditions, the proposed technique can achieve optimal separation among different fault classes. Design, real-time implementation, and experimental evaluation of the proposed method are detailed in this paper. The implemented system has been validated on the Nuclear Power Control Test Facility to demonstrate the feasibility. The test results have revealed many salient features of the proposed method with potential applications in NPPs. [ABSTRACT FROM AUTHOR]

This paper proposes a unified optimal control framework that can be used to formulate and solve aircraft performance problems, such as maximum endurance and maximum range, for both propeller-driven airplanes and jet-propelled aircraft. It is proved in this paper that such problems have a common mathematical formulation and, under strict convexity assumptions, they have a unique feedback solution for the speed as a function of weight. The feedback solution yields an analytic expression for the optimal speed. For maximum endurance, the solution corresponds to the minimization of the rate of fuel consumption per unit time. For maximum range, the rate of fuel consumption per unit distance is minimized. Moreover, the optimal solution for maximum range will be interpreted geometrically using the concept of convex conjugate function and Legendre transformation. Although the optimal control framework is illustrated for maximum range and maximum endurance, it is a general approach that can be used for other aircraft performance problems. [ABSTRACT FROM AUTHOR]

In this paper, direct torque control (DTC) of five-phase induction motor (FPIM) is implemented using three-level neutral point clamped (TL-NPC) inverter. One of the advantages of three-level inverter over two-level one for DTC operation is the low torque ripple. Also TL-NPC inverter through space vector modulation technique gives low $ dv/dt$ transition with better voltage waveform. By applying conventional lookup table for DTC, the TL-NPC inverter does not ensures lower $dv/dt$ transition. In this paper, a novel switching scheme for DTC of FPIM using TL-NPC inverter is proposed that ensures the low $ dv/dt$ transition and balancing of dc-link capacitor voltages of TL-NPC inverter. To form the lookup table for DTC operation, instead of using voltage vectors directly, virtual vectors (VVs) are utilized. Two switching states are used in one sample time to generate a VV in $\alpha \beta$ plane, which gives zero resultant voltage in $ xy$ plane. The switching strategy ensures low number of transitions to reduce the switching losses. The switching state redundancies are used in a novel way to balance the dc-link capacitor voltages without using any additional hardware. The proposed technique to balance the dc-link capacitor voltage gives lower switching frequency. The MATLAB/Simulink environment is used for the simulation and the results are validated through experiments. [ABSTRACT FROM AUTHOR]

Lighting consumes the largest amount of energy in buildings. Recently, many studies of energy-efficient lighting systems with a variety of sensor and communication technologies have been conducted as a way to increase the cost efficiency of lighting. However, earlier studies have mostly focused on energy efficiency, whereas they have not significantly considered the occupant’s satisfaction. Therefore, this paper proposes an energy-saving lighting control system considering the occupant’s satisfaction. The proposed system improves the energy efficiency and the occupant’s satisfaction by controlling lighting control parameters considering the characteristics of space and the occupant’s behavior patterns. Moreover, this paper deployed the proposed lighting systems in a building and operated them in a real work environment to evaluate the performance. The results showed that the proposed system reduced energy consumption up to 43% by replacing the existing fluorescent lights with the proposed lighting control systems. [ABSTRACT FROM PUBLISHER]

This paper targets the reduction of common-mode voltage in an indirect matrix converter (IMC) through an intelligent space-vector-based modulation technique. This mode of control results in lower dV/dt at the motor terminals, thereby, reducing voltage stress to windings; and reduced output voltage distortion resulting in lower machine losses. The conventional indirect space vector pulse-width modulation method of controlling matrix converters involves independent control of either the rectifying stage or the inverting stage of the converter. However, in this paper, by suitable selection of space vectors, the rectifying stage of the matrix converter generates different levels of virtual dc-link voltage. Therefore, the responsibility of formulating output voltages with a particular magnitude and frequency, which can be translated to different machine speeds, has been transferred solely to the rectifying stage of the IMC. Estimation of the degree of distortion in the three-phase output voltage is another facet discussed in this paper, which aids the sizing and designing of output passive filters. The analysis of output voltage distortion and the proposed modulation strategies have been substantiated by simulations in MATLAB/Simulink and experimentally verified on a scaled down laboratory prototype. [ABSTRACT FROM AUTHOR]

Vehicle platooning gains its popularity in improving traffic capacity, safety and fuel saving. The key requirements of an effective platooning strategy include keeping a safe inter-vehicle space, ensuring string stability and satisfying vehicular constraints. To meet these requirements, this paper proposes a distributed min-max model predictive control (MPC). One technical contribution is that the proposed MPC can guarantee input-to-state predecessor-follower string stability, in the presence of vehicle-to-vehicle communication delays and realistic constraints. Another technical contribution is the development of a new concept of input-to-state stability margin for analyzing the platooning system that is nonlinear under MPC. The proposed MPC is applicable to both homogeneous and heterogeneous platoons because only the point-mass vehicle model is needed. The proposed MPC also has reduced communication burden because each vehicle in the platoon only transmits its current acceleration to the adjacent follower. The design efficacy is verified by simulating a platoon composed of five vehicles under different uncertainties and communication delays. [ABSTRACT FROM AUTHOR]