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This study uses a comprehensive control approach to deal with the trajectory tracking problem of a two-flexible-link manipulator subjected to model uncertainties. Because the control inputs of two-flexible-link manipulators are less than their state variables, the proposed controller should be able to tackle the stated challenge. Practically speaking, there is only a single control signal for each joint, which can be used to suppress link deflections and control joint trajectories. To achieve this objective, a novel optimal robust control scheme, with an updated gain under the adaptive law, has been developed in this work for the first time. In this regard, a nonsingular terminal sliding mode control approach is used as the robust controller and a control Lyapunov function is used as the optimal control law, to benefit from the advantages of both methods. To systematically deal with system uncertainties, an adaptive law is used to update the gain of nonsingular terminal sliding mode control. The advantage of this approach over the existing methods is that it not only can robustly and stably control an uncertain nonlinear system against external disturbances but also can optimally solve a quadratic cost function (e.g. minimization of control effort). The Lyapunov stability theory has been applied to verify the stability of the proposed approach. Moreover, to show the superiority of this method, the computer simulation results of the proposed method have been compared with those of an adaptive sliding mode control scheme. This comparison shows that the presented approach is capable of optimizing the control inputs while achieving the stability of the examined two-flexible-link manipulator in the presence of model uncertainties and external disturbances. [ABSTRACT FROM AUTHOR]

A quadrotor with tiltable rotors is a kind of omnidirectional multirotor aerial vehicle (MAV) that has demonstrated advantages of decoupling control of position from the control of orientation. However, quadrotors with tiltable rotors usually suffer from Coriolis term, modeling error and external disturbance. To this end, the extended state observer (ESO)-based controller is designed to estimate and compensate for the above adverse effects. Especially, the controller involves position and attitude controller in parallel. The attitude controller is made up of cascade control-loops: an outer quaternion-based attitude control-loop and an inner ESO-based Proportional derivative angular velocity control-loop. Similarly, the position controller consists of an outer proportional position control-loop and an inner ESO-based PD velocity control-loop. Besides, a linear control allocation strategy, which allocates the controller outputs to tilting angles and motor speed directly, is proposed to avoid the nonlinear allocation matrix. Extensive simulations and flight tests are carried out to illustrate the effectiveness and robustness of the proposed ESO-based controller. [ABSTRACT FROM AUTHOR]

A model reference adaptive sliding mode control for the position control of the permanent magnet synchronous motor is developed in this article. First of all, a fast sliding surface is designed to achieve faster convergence than the ordinary sliding mode control. Then, the adaptive laws are developed to make the control parameters, especially the switching gain, updated online. Therefore, the chattering can be reduced effectively and the disturbance can be rejected well. Finally, a reference model which produces an exponential decay curve is applied for the position error to follow. Thus, not only fast error convergence can be guaranteed, but also the dynamic process of the system response can be controlled easily by modifying the decay rate of the reference model. The proposed model reference adaptive sliding mode control scheme combines the advantages of the sliding mode control and the model reference adaptive control. Simulation and experimental results reveal that faster and more accurate performance with smoother control signal and better robustness is obtained compared with other methods. Also, the model reference adaptive sliding mode control method can maintain good performance when the system inertia or the position reference varies in a wide range. [ABSTRACT FROM AUTHOR]

Obstacle avoidance strategy is important to ensure the driving safety of unmanned ground vehicles. In the presence of static and moving obstacles, it is challenging for the unmanned ground vehicles to plan and track the collision-free paths. This paper proposes an obstacle avoidance strategy consists of the path planning and the robust fuzzy output-feedback control. A path planner is formed to generate the collision-free paths that avoid static and moving obstacles. The quintic polynomial curves are employed for path generation considering computational efficiency and ride comfort. Then, a robust fuzzy output-feedback controller is designed to track the planned paths. The Takagi–Sugeno (T–S) fuzzy modeling technique is utilized to handle the system variables when forming the vehicle dynamic model. The robust output-feedback control approach is used to track the planned paths without using the lateral velocity signal. The proposed obstacle avoidance strategy is validated in CarSim® simulations. The simulation results show the unmanned ground vehicle can avoid the static and moving obstacles by applying the designed path planning and robust fuzzy output-feedback control approaches. [ABSTRACT FROM AUTHOR]

An optimal bounded control strategy for strongly nonlinear vibro-impact systems under stochastic excitations with actuator saturation is proposed. First, the impact effect is incorporated in an equivalent equation by using a nonsmooth transformation. Under the assumption of light damping and weak random perturbation, the system energy is a slowly varying process. By using the stochastic averaging of envelope for strongly nonlinear systems, the partially averaged Itô stochastic differential equation for system energy can be derived. The optimal control problem is transformed from the original optimal control problem for the state variables to an equivalent optimal control problem for the system energy, which decreases the dimensions of the optimal control problem. Then, based on stochastic maximum principle, an adjoint equation for the adjoint variable and the maximum condition of partially averaged control problem are established. For infinite time-interval ergodic control, the adjoint variable is assumed to be a stationary process and the adjoint equation can be further simplified. Finally, the probability density function of the system energy and other statistics of the optimally controlled system are derived by calculating the associated Fokker–Plank–Kolmogorov equation. For comparison, the bang–bang control is also investigated and the control results are compared to show the advantages of the developed control strategy. [ABSTRACT FROM AUTHOR]

This paper deals with the finite-time trajectory tracking problem for a typical 3-DOF (degree of freedom) autonomous surface vehicle (ASV) subjected to parametric uncertainties and environmental disturbances. Based on the nonsingular terminal sliding mode control (NTSMC) method, several separate classes of robust control inputs are designed to exactly steer all position states of the 3-DOF AVS to the desired paths during alterable finite times. By exploiting the Lyapunov stability theorem and using mathematical analysis, it is proven that all classes of designed robust control inputs are able to fulfill the mentioned finite-time tracking aim. Moreover, three applicable formulas (represented as several nonlinear inequalities) are extracted to determine the required total finite times for the suggested control schemes. Lastly, all designed control methods are numerically tested onto a benchmark 3-DOF AVS called CyberShip II. Provided computer-based numerical simulations (using MATLAB software) depicted the acceptable performance of the proposed control techniques. [ABSTRACT FROM AUTHOR]

In this paper, the nonlinear robust H ∞ control is investigated for nonlinear course control systems of unmanned surface vessel (USV) with uncertain parameters and external disturbance. Firstly, we suppose that the part or all of the system parameters are unknown but within some ranges, due to the effect of different conditions such as the loading of ship. Then, the course system is modeled as a polynomial one with time invariant polytopic uncertainty. With the aid of parameter dependent Lyapunov function method and positive polynomial theory, the sufficient conditions are given for stability and stabilization with H ∞ performance. These conditions are formulated in terms of parameter-dependent nonlinear matrix inequalities which can be verified by semidefinite programming relaxations based on the sum of squares technique. Finally, simulation results show the effectiveness of the approach. [ABSTRACT FROM AUTHOR]

Articulated wheeled loader vehicles have frequent rollover accidents as they operate in the complex outdoor environments. This article proposes an active anti-rollover control method based on a set of single-frame control moment gyro stabilizer installed on the rear body of the vehicle. The rollover dynamic model is first established for articulated wheeled loader vehicle with gyro stabilizer. The proposed control strategy is then applied in simulation to verify the rollover control effect on the vehicle under steady-state circumferential conditions. Finally, a home-built articulated wheel loader vehicle with gyro stabilizer is used to further verify the proposed control strategy. The results show that the vehicle can quickly return to the stable driving state and effectively avoid the vehicle rollover when a suitable anti-roll control moment can be provided by the gyro stabilizer. As a result, the articulated wheeled loader vehicle is able to operate safely in a complex outdoor environment. [ABSTRACT FROM AUTHOR]

A robust approximate constraint-following control method based on the fundamental equation of Udwadia--Kalaba approach is designed to control the permanent magnet linear motor. The control scheme consists of three parts: the nominal part to suppress any tendency of deviating from the constraints, the second part to deal with any possible initial condition deviation from the constraint manifold and drive the system toward the constraints, and the robust part to compensate for the effect due to uncertainty. Theoretical proof, numerical simulation, and experimental validation have been done to verify the effectiveness of this control method. [ABSTRACT FROM AUTHOR]

To alleviate subsynchronous resonance in doubly fed induction generator--based wind farm, this study devises a robust nonlinear control for a rotor-side converter based on a fractional-order sliding mode controller. The designed fractionalorder sliding mode controller is able to realize finite-time control and reduce the control time compared with terminal sliding mode control, which contributes to the faster mitigation of subsynchronous resonance. Impedance-based analysis and transient simulation are carried out to evaluate the performance of the fractional-order sliding mode controller compared with terminal sliding mode control and subsynchronous damping control. Simulation results verify that the fractional-order sliding mode controller is able to damp SSR within shorter time and effectively reduce the fluctuation range of a system's transient responses under various working conditions of compensation degrees and wind speeds. Furthermore, the fractional-order sliding mode controller enhances the robustness under external disturbance and parametric uncertainty, ensuring safe operation of the practical wind farm. [ABSTRACT FROM AUTHOR]

One of the most challenging topics in electric railway networks (ERNs) is power quality (PQ) problems caused by single-phase feeding of time-varying and high-power locomotives. During previous years, many techniques and compensators have been offered to alleviate these problems. Railway active power quality controller (RAPQC) is considered as one of the most efficient approaches. Due to the time-variant, uncertainty and distorted features of ERNs, the controlling of RAPQCs has always been a substantial concern to experts. This paper presents, a new robust control system for two-phase three-wire RAPQC (ThRAPQC) based on generalized model predictive control integrated with modified instantaneous reactive power theory (GMPC-MIRP). A dual-loop balancing system has been adopted in the proposed control system to equalize the active powers of traction power substation (TPSS) adjacent feeders, compensate reactive powers and suppress harmonic simultaneously. The performance of the proposed method in comparison with the conventional Fryze-Buchholz-Depenbrock (FBD)-based current strategy together with hysteresis current controller (FBD-HCC) has been evaluated through the detailed simulations and Opal-RT 5600-based laboratory setup results. The fast response, high precision, lower fluctuation in reference current tracking and high capability of working in distorted conditions are the outstanding privileges of the proposed method that are confirmed by the output results. [ABSTRACT FROM AUTHOR]

To research the tendencies of immediate change in the scheduled parameters, a linear parameter–varying control strategy is made in real time for lab-based inverted pendulum system. An adjusted and observing virtual instrument is designed in LabVIEW to construct this mechanism. To obtain the transient response data, a step response is transmitted by virtual instrument to the inverted pendulum by which model of inverted pendulum is identified. System model depicts its characteristics, so this model is employed in designing controller. To improve the performance and robustness, linear parameter–varying controller is created to deal with parameter distinctions. Furthermore, the effectiveness of this designed robust controller is checked by integrating on hardware system. The discovered model is checked by evaluating the presented approaches in real time and simulation outcomes with traditional controller as proportional–integral–derivative controller and linear–quadratic regulator. [ABSTRACT FROM AUTHOR]

Tailsitter unmanned aerial vehicles are utilized extensively nowadays since they merge advantages of both fixed-wing unmanned aerial vehicles and rotary-wing unmanned aerial vehicles. However, their attitude control suffers from unknown nonlinearities and disturbances due to the wide flight envelope. To solve the problems, a robust attitude controller based on a newly designed flying-wing tailsitter is proposed in this paper. By employing the angular acceleration feedback to compensate unmodeled dynamics, the proportional incremental nonlinear dynamic inversion control law is first developed. The proportional incremental nonlinear dynamic inversion strengthens the conventional nominal gain incremental nonlinear dynamic inversion with a proportional term to reflect the change of the angular acceleration more directly. Therefore, the tailsitter has a quicker response and performs better in suppressing model uncertainties and external disturbances. Since the angular acceleration is difficult to measure in practice, an angular acceleration estimation method is then established to provide accurate signals for the proportional incremental nonlinear dynamic inversion. The signals are derived as complementary results of model prediction method and direct differential method. Theoretical analysis and systematic simulations are conducted to corroborate the effectiveness of the developed estimation method as well as the robustness of the proposed controller. [ABSTRACT FROM AUTHOR]

The article applies the robust generalized dynamic inversion control methodology to the problem of stabilizing upright equilibrium configuration of the under-actuated rotary inverted pendulum system while tracking rotary motion of the actuated arm. The proposed robust generalized dynamic inversion control law comprised equivalent and switching control parts. The equivalent control part works to enforce a virtual constraint dynamics of the controlled state variables by means of Moore– Penrose generalized inversion. The switching control part is of the sliding mode type, and it improves robustness against unmodeled system dynamics, parametric uncertainties, and external disturbances. The robust generalized dynamic inversion control design on the linearized model of the under-actuated rotary inverted pendulum is shown to guarantee semi-global asymptotically stable tracking performance. Numerous computer simulations and experiments are conducted on the Quanser rotary inverted pendulum system, revealing that the proposed algorithm has better convergence and tracking performance than conventional sliding mode and generalized dynamic inversion control strategies when both are applied separately. [ABSTRACT FROM AUTHOR]

The aim of this article was to determine control strategy for balance control of rotary double inverted pendulum system, which is highly nonlinear and unstable under-actuated system. The complexities involved in rotary double inverted pendulum dynamics make this system a useful engineering test bed to test and verify newly designed controllers. In this article, a constraint-based control approach titled robust generalized dynamic inversion is designed and implemented for robust stabilization of rotary double inverted pendulum system. The robust generalized dynamic inversion control is designed in two stages; in the first stage, constraint differential equations of the controlled state variables are prescribed, which encompasses the control objectives. To enforce the constraint dynamics, the equivalent control is realized by means of Moore–Penrose generalized inversion. To enhance robustness, the switching (discontinuous) control is introduced in second stage, whose design principle is based on classical sliding mode control theory. Finally, the controllers obtained in two stages are augmented to form the resultant robust generalized dynamic inversion control law. The proposed controller ensures robustness along with improved time domain performance regardless of system nonlinearities, uncertainties, and unwanted disturbances. The stability analysis is presented for guaranteeing semi-global asymptotically stable closed loop performance via Lyapunov stability criteria. Numerical simulation and experimental investigations are carried out along with comparative analysis, to demonstrate the effectiveness of robust generalized dynamic inversion control algorithm over other conventional control methods. [ABSTRACT FROM AUTHOR]

This paper presents an integrated nonlinear robust adaptive controller with uncertainty observer for active front wheel steering system and direct yaw moment control system. First, an integrated vehicle chassis control model is established as the nominal model with the additive and multiplicative uncertainties of the system. Secondly, an integrated nonlinear robust adaptive control law with the additive uncertainty observer is designed via Lyapunov stability theory to calculate the corrective yaw moment, and an adaptive law is designed based on projection correction method to online estimate and compensate the multiplicative uncertainty of the system. Then, the constrained optimal allocation problem of the corrective yaw moment is transformed into the nonlinear optimization problem, and the sequential quadratic programming method is used to solve the nonlinear optimization problem to coordinate active front wheel steering system and direct yaw moment control system. Finally, the performance of the proposed integrated nonlinear robust adaptive controller is verified via vehicle dynamics simulation software. [ABSTRACT FROM AUTHOR]

In this paper, the robust control problem is tackled by employing the state-dependent Riccati equation (SDRE) for uncertain systems with unmeasurable states subject to mismatched time-varying disturbances. The proposed observer-based robust (OBR) controller is applied to two highly nonlinear, coupled and large robotic systems: namely a manipulator presenting joint flexibility due to deformation of the power transmission elements between the actuator and the robot known as flexible-joint robot (FJR) and also an FJR incorporating geared permanent magnet DC motor dynamics in its dynamic model called electrical flexible-joint robot (EFJR). A novel state-dependent coefficient (SDC) form is introduced for uncertain EFJRs. Rather than coping with the OBR control problem for such complex uncertain robotic systems, the main idea is to solve an equivalent nonlinear optimal control problem where the uncertainty and disturbance bounds are incorporated in the performance index. The stability proof is presented. Solving the complicated robust control problem for FJRs and EFJRs subject to uncertainty and disturbances via a simple and flexible nonlinear optimal approach and no need of state measurement are the main advantages of the proposed control method. Finally, simulation results are included to verify the efficiency and superiority of the control scheme. [ABSTRACT FROM AUTHOR]

A high-speed supercavitating vehicle is a future underwater vehicle which exploits the supercavitating propulsion technology providing a promising way to increase the vehicle speed. Robust control challenges include complex vehicle maneuvering dynamics caused by factors such as undesired switching, delayed state dependency, and nonlinearities. As effective and applicable controllers, a novel fractional-order sliding mode controller is proposed to robustly control the uncertain high-speed supercavitating vehicle system against external disturbances. The control scheme uses sliding mode control and can produce better control actions than conventional the integer-order counterpart. In this algorithm, the fractional calculus is applied to calculate the noninteger integral or derivative in the sliding mode control algorithm, providing new capabilities for uncertain high-speed supercavitating vehicle control in seeking to operate the underwater vehicle better. The performance of the proposed fractional-order sliding mode controller has been proven through analytic simulation results, which show fast responses with smooth control actions and the ability to deal with nonlinear planing force and external disturbance. One of the interesting features of the fractional-order control system is the time convergence rate of the sliding variable vector, which is greatly improved compared with the integer-order sliding mode control. Finally, the robust control system with a novel fractional-order sliding mode controller algorithm, using high flexibility of controlling undersea vehicles, can provide superior dynamical performance with stability compared with its integer-order counterpart against system uncertainties and disturbances. [ABSTRACT FROM AUTHOR]

In this paper, an online temporal differences (TD) learning approach is proposed to solve the robust control problem for discrete-time Markov jump linear systems (MJLS) subject to completely unknown transition probabilities (TP). The TD learning algorithm consists of two parts: policy evaluation and policy improvement. In the first part, by observing the mode jumping trajectories instead of solving a set of coupled algebraic Riccati equations, value functions are updated and approximate the TP related matrices. In the second part, new robust controllers can be obtained until value functions converge in the previous part. Moreover, the convergence of the value functions is proved by initializing a feasible control policy. Finally, two examples are presented to illustrate the effectiveness of the proposed approach by comparing with existing results. [ABSTRACT FROM AUTHOR]

Populism studies have rapidly burgeoned but systematic global empirical evidence about this phenomenon has lagged behind. How can party values be measured in consistent, valid, and reliable ways, facilitating identification of varieties of populism in countries around the world? To address this issue, part I outlines the conceptual framework. Part II describes the research design. The Global Party Survey (GPS) replicates previous expert surveys, expands coverage worldwide, and incorporates innovative scaled measures of populism. It draws upon estimates from 1861 experts and covers 1043 political parties in 163 countries (see www.GlobalPartySurvey.org). Part III summarizes some key cross-national results. Part IV presents robustness tests which confirm that the new GPS estimates of ideological values and populist parties are consistently correlated with several previous measures. The conclusion in part V summarizes the main findings and considers the potential uses of the data set for understanding populism as a global phenomenon. [ABSTRACT FROM AUTHOR]

This article investigates the design of a novel nonlinear robust adaptive control architecture to stabilize and control an airplane in the presence of left-wing damage. Damage effect is modeled by considering the sudden mass and inertia changes, center of gravity, and aerodynamic variations. The novel nonlinear control algorithm applies a state predictor as well as the error between the real damaged dynamics and a virtual model based on the nominal aircraft dynamics in the control loop of the adaptive strategy. The projection operator is used for the purpose of robustness of the adaptive control algorithm. The stability of the proposed nonlinear robust adaptive controller is demonstrated applying the Lyapunov stability theory. The performance of the proposed controller is compared with two previous successful algorithms, which are implemented on the Generic Transport Model airplane to accommodate wing damage. Numerical simulations demonstrate the effectiveness and advantages of the proposed robust adaptive algorithm regarding two other algorithms of adaptive sliding mode and L 1 adaptive control. [ABSTRACT FROM AUTHOR]

In this article, a decentralized strategy is applied for active control of sound inside the automobile cabin by considering the uncertainty caused by the movement of the occupants. A coupled structural-acoustic analysis is done on the simplified geometry of the automobile cabin with passengers by the finite element method. The uncertainty caused by changes in the occupants' head positions and angles is also considered. Then, a decentralized robust feedback control strategy is proposed to reduce the sound pressure level in the ears of all the occupants using the H∞ method for each individual control unit by considering the unstructured uncertainty of the plant. The efficiency of the proposed control strategy in minimizing the sound pressure level caused by the structural disturbance on the firewall panel is investigated. [ABSTRACT FROM AUTHOR]

This article studies the problem of global stability of the Takagi–Sugeno fuzzy systems based on a novel descriptor-based non-quadratic Lyapunov function. A modified non-quadratic Lyapunov function, which comprises an integral term of the membership functions, and a modified non-parallel distributed controller constructed by constant delayed premise variables are considered that assure the global stability of the closed-loop T–S fuzzy system. The special structure of the used non-quadratic Lyapunov function results in time-delayed terms of the membership functions, instead of appearing their time derivatives, which is the well-known issue of the common non-quadratic Lyapunov functions in the literature. Also, the memory fuzzy controller is chosen such that the artificial constant delay-dependent stability analysis conditions for a non-delayed closed-loop T–S fuzzy system are formulated in terms of linear matrix inequalities. To further reduce the conservatives, some slack matrices are introduced by deploying the descriptor representation and decoupling lemmas. Moreover, the design of the robust fuzzy controller is studied through the H ∞ performance criteria. The main advantages of the proposed approach are its small conservatives and the global stability analysis, which distinguish it from the state-of-the-art methods. To show the merits of the proposed approach, comparison results are provided, and two numerical case studies, namely, flexible joint robot and two-link joint robot are considered. [ABSTRACT FROM AUTHOR]

The purpose of this study is to develop a simple and practical controller design method without modeling controlled objects. In this technique, modeling of the controlled object is not necessary and a controller is designed with an actuator model, which includes a single-degree-of-freedom virtual structure inserted between the actuator and the controlled object. The parameters of the virtual structure are determined so that indirect active vibration suppression is effectively achieved by considering the frequency transfer function from the vibration response of the controlled object to that of the virtual structure. Since the actuator model, which includes a virtually controlled object, is a simple low-order system, a controller with high control performance can be designed by traditional model-based optimal control theory. In this research, a mixed H 2 / H ∞ controller is designed considering both control performance and robust stability. The effectiveness of the proposed method is validated experimentally. The robustness of the controller is demonstrated by applying the same controller to various structures. [ABSTRACT FROM AUTHOR]

Piezoelectric stacks (PS) are wildly used as actuator mechanism for precise instrument in practical engineering. Nevertheless, hysteretic effect that is carried by the piezoelectric materials can degrade the control performance dramatically. For the purpose of improving the control precision, the problem of hysteresis compensation control for PS system is investigated in this paper. First, in order to compensate the hysteretic effect, two kinds of observers are proposed. The design of the observers has considered external disturbance and the creep effect in PS system. By utilizing Lyapunov function and linear matrix inequalities (LMI) technique, the observers can asymptotically estimate the hysteretic output with H ∞ performance. Second, a hysteresis-compensation based back-stepping controller is established. The design of the controller has considered the observation error, and it has a certain robustness. At last, numerical and experimental simulations are carried out to verify the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

In this study, a nonlinear adaptive controller that can be used to control a magnetic levitation (maglev) is designed. The designed controller is equipped with a nonlinear velocity observer to provide the control without measuring velocity. Its capability to adaptively compensate all parametric uncertainties during the control process is one of the main advantages of this controller. Utilizing this capability, control of the maglev system can be realized without using any knowledge about system parameters. Due to the fast convergence capability of the designed observer and the desired model dependent structure of the adaptation rules, the proposed control design provides better performance than most of the robust and adaptive controllers that have been frequently used to control maglev system. The observer dynamics are analyzed via a Lyapunov–like preliminary analysis. Then, convergence of the observation and the tracking errors under the closed–loop operation and stability of the closed–loop error dynamics are proven via a Lyapunov–based stability analysis where the result obtained in the mentioned preliminary analysis is used. Performance of the designed observer–controller couple is demonstrated via experimental results. The efficiency of the designed controller is tested against a robust proportional–integral–derivative (PID) controller and an another Lyapunov–based nonlinear robust controller called as robust integral of sign of error (RISE) controller. Experimental results show that the designed controller performs the best tracking performance with the least control effort among these three controllers. [ABSTRACT FROM AUTHOR]

The problem of H ∞ control is investigated for turbofan systems with uncertain parameters and multiple disturbances in this paper. Some disturbances with partly known information are described via an external system, and other disturbances are assumed to be L 2 norm bounded. According to the disturbance-observer-based-control (DOBC) method and resilient H ∞ control technique, a robust resilient controller is designed to reject and attenuate the influence of these disturbances, and guarantees that closed-loop systems are asymptotically stable with H ∞ performance. Some solvable sufficient conditions are obtained based on the linear matrix inequality (LMI) technique and Lyapunov stability theory. Finally, a simulation is presented to show the robustness and effectiveness of the developed resilient anti-disturbance H ∞ control method. [ABSTRACT FROM AUTHOR]

This article deals with the robust optimal control and identification of uncertain adaptive cruise control systems. Both measurement delay and engine's lag are investigated in system modeling and control design. The control structure consists of two steps. In the first step, by using a new approach, the uncertain parameters of longitudinal dynamics of each vehicle is identified. Afterwards, at the second step, by using the relative position and velocity measurement with respect to ahead vehicle, a robust control against size changing of platoon is presented to assure the internal stability, string stability, and safety of heterogeneous vehicular platoons. A cost function involving important metrics internal stability, maximum overshoot, and settling time is introduced, and the particle swarm optimization algorithm is used to find the optimal values of control parameters minimizing the cost function. It will be shown that the proposed robust controller guarantees the internal stability, string stability, and safety of adaptive cruise control systems in the presence of measurement and parasitic delays. Several simulation results are provided to show the effectiveness of the proposed approaches. [ABSTRACT FROM AUTHOR]

Proportional–integral–derivative is one of the most applicable control methods in industry. Although it is simple and effective in most cases, it does not provide robustness against disturbances and may not perform well in cases with uncertainties and nonlinearities. In this study, a fuzzy adaptive robust proportional–integral–derivative controller is used to control a nonlinear 4 degree-of-freedom quadrotor. An adaptation mechanism is submitted to the proportional–integral–derivative controller for updating the proportional, derivative, and integral gains of proportional–integral–derivative control. Furthermore, a sliding surface is generated and submitted to the adaptation mechanism for better regulation of proportional–integral–derivative gains. Afterward, a fuzzy engine is applied to regulate the sliding surface for better performance of the adaptive proportional–integral–derivative when there are disturbance and uncertainties. The multi-objective grasshopper optimization algorithm is implemented on the control system for the regulation of the control system parameters to minimize the error and control effort of the proposed hybrid control system. Finally, the obtained results are presented for a nonlinear 4 degree-of-freedom multi-purpose (for marine, ground, and aerial maneuvers) quadrotor system designed and built in Sirjan University of Technology, Sirjan, Iran, to assure the effectiveness of this technique. [ABSTRACT FROM AUTHOR]

Piezoelectric bending actuators have been widely used in a variety of micro- and nano-applications, including atomic force microscopy, micro assembly, cell manipulation, and in general, micro electromechanical systems. However, their control algorithms at low frequencies suffer from nonlinearities such as hysteresis in high voltages and creep in long-time static applications. Also, in high-frequency applications, especially near the actuator natural frequencies, the actuator dynamic is greatly affected by the material nonlinearity. Therefore, the control approaches based on the linear dynamic modeling cannot be effective at high frequencies. Thus, the position control of the foregoing actuators become challenging, and it has been of researchers' interests in the last decade. In this article, the robust position control of a bimorph piezoelectric bending actuators is investigated. In this regard, based on the nonlinear constitutive equations and the Euler–Bernoulli beam theory, a nonlinear dynamic model is presented. Then, to track a desired motion trajectory, an observer-based robust position control algorithm is proposed. The proposed control methodology is able to accommodate parametric uncertainties and other un-modeled dynamics. Also, it ensures the elimination of the position tracking error in the presence of the estimated states. Finally, the tracking ability of the controller is demonstrated in an experimental study. The experimental results show that the identification of the system is properly conducted with the average error of 5.5%. Also, the efficiency of the robust controller is proved with the error of 3.7% and 4.9% in the position tracking of the actuator inside and outside of the identified region, respectively. [ABSTRACT FROM AUTHOR]

Shifting automotive powertrain development tasks to earlier phases (frontloading) increases efficiency by utilizingtest-benches as opposed to prototype vehicles (road-to-rig approach). The coupling of distributed test-benches by a virtualized shaft connection is required to reproduce interactions of automotive powertrain components. A coupling algorithm simulates a rigid connection by synchronizing the torque and speed of two distributed test-bench's electric motors. System dead-times lead to limited stability and reduced bandwidth of the coupling algorithm. In this study, a method for a stable bidirectional coupling of speed and torque of both subsystems is described analytically and verified by simulation. All component models are calibrated based on measurements using state-of-the-art test-bench equipment. A distributed prediction algorithm is proposed for the dead-time compensation. Four Kalman predictors estimate the coupling values of both subsystems at wall-clock-time without measurement and communication latencies. A detailed drive cycle analysis is performed through simulation. This enables a Virtual Shaft Algorithm to achieve a higher bandwidth and an improved coupling robustness. [ABSTRACT FROM AUTHOR]

This paper proposes a framework for path tracking under additive disturbance when a vehicle travels at high speed or on low-friction road. A decoupling control strategy is adopted, which is made up of robust model predictive control and the stability control combining preview G-vectoring control and direct yaw moment control. A vehicle-road model is adopted for robust model predictive control, and a robust positively invariant set calculated online ensures state constraints in the presence of disturbances. Preview G-vectoring control in stability control generates deceleration and acceleration based on lateral jerk, later acceleration, and curvature at preview point when a vehicle travels through a cornering. Direct yaw moment control with additional activating conditions provides an external yaw moment to stabilize lateral motion and enhances tracking performance. A comparative analysis of stability performance of stability control is presented in simulations, and furthermore, many disturbances are considered, such as varying wind, road friction, and bounded state disturbances from motion planning and decision making. Simulation results show that the stability control combining preview G-vectoring control and direct yaw moment control with additional activating conditions not only guarantees lateral stability but also improves tracking performance, and robust model predictive control endows the overall control system with robustness. [ABSTRACT FROM AUTHOR]

The complexity of the closed-loop system, short transient response time, and fast synchronization error convergence rates are the three basic parameters that limit hacking in the data encryption and secure the communication systems. This paper addresses the following two challenges: The full-order synchronization (FOS) of two parametrically excited second-order nonlinear pendulum (PENP) chaotic systems with uncertain parameters. The reduced-order synchronization (ROS) between the canonical projection part of an uncertain third-order chaotic Rossler and the uncertain PENP systems. This article designs a new robust adaptive synchronization control (RASC) algorithm to address the above two challenges. The proposed controller achieves the FOS and ROS in a shorter transient time, and the synchronization error signals converge to the origin with faster rates in the presence of bounded unknown state-dependent and time-dependent disturbances. The Lyapunov direct method verifies this convergence behavior. The paper provides parameters updated laws that confirm the convergence of the uncertain parameters to some fixed values. The controller does not cancel the nonlinear terms of the plant; this property of the controller keeps the nonlinear terms in the closed-loop that results in the enhanced complexity of the dynamical system. The proposed RASC strategy is successful in synthesizing oscillation free convergence of the synchronization error signals to the origin for reducing the transient time and guarantees the asymptotic stability at the origin. The simulation results endorse the theoretical findings. [ABSTRACT FROM AUTHOR]

While the use of integral action in control is quite common, in part due to its benefits for output regulation, it can also be counterproductive when abrupt changes in disturbance occur during tracking. In order to mitigate its counterproductive effect while at the same time maintaining its advantages for regulation, this work proposes a new type of integral action, including a time-varying forgetting factor suited to the expected behavior of the disturbance during tracking. Also, Lyapunov stability techniques are used to derive general results aiming to reduce the complexity of stability analysis and control design when the proposed integral action is included in a control law. In particular, these results are used for stability analysis when the proposed integral action is implemented in a deterministic robust controller for a linear motor system. Furthermore, the controller is implemented in the corresponding experimental setup, resulting in an improvement on maximum tracking error of up to 32%. [ABSTRACT FROM AUTHOR]

Methods to optimise train movements to maintain time and avoid excessive energy consumption are becoming widely applied, but outcomes remain sensitive to uncertainties within the system. In this paper, variability in station dwell-times and the points of application of planned train control (traction, coasting or braking) are taken as examples of typical rail system uncertainties and are used to demonstrate an approach to multi-train trajectory optimisation that is resilient to them. Trade-offs are explored between highly optimised train trajectories that are vulnerable to perturbation and less optimal trajectories that are robust to typical disturbances. Beyond dwell and control variations the method has application for many other common rail network uncertainties, e.g. differences in the traction characteristics of nominally identical trains or variable train loading. Relative to optimisation without consideration of uncertainty, the approach is shown to find control strategies of substantially increased robustness for the test cases examined and offers a more principled way to plan a network than the ad hoc use of recovery time to mitigate everyday operational disturbances. [ABSTRACT FROM AUTHOR]

Actuator faults are inevitable in small reverse osmosis desalination plants. It may cause energy losses and reduce the quality of the freshwater, which may endanger human life. This paper focuses on the integrated fault detection and fault-tolerant control approach. The primary motivation of this paper is to propose a novel integrated fault detection and fault-tolerant control approach. The actuator fault is estimated using the concept of parity space approach. Then the system model is updated in the fault-tolerant control block using the information of the estimated fault parameter. Moreover, the proposed approach uses the receding-horizon predictive control-bounded data uncertainties controller, which is the robust and stable variant of generalized predictive control. The remaining uncertainty caused by the model and observer is compensated by this controller. The structure of a small reverse osmosis desalination plant is deployed. In this plant, the permeate flow rate and conductivity are controlled by a retentate valve and a bypass valve, which add a small amount of inlet to the outlet. The performances of three predictive model controllers are evaluated, and a comparison is made between their computational costs, stability, and robustness. The plant is considered to be linear time-invariant and subject to model uncertainties, measurement noise, and actuator fault in the retentate valve as efficiency dropping. The results reveal the robustness of the proposed approach concerning noise and matched uncertainties as well as its accommodation to actuator fault up to 90%. [ABSTRACT FROM AUTHOR]

In this article, we present a new controller for stable and robust walking control of ATRIAS, an underactuated bipedal robot designed based on the spring-loaded inverted pendulum (SLIP) model. We propose a forced-oscillation scheme for control of vertical motion, which we prove to be stable and contractive. Moreover, we prove that, through some mild assumptions, the dynamics of the system can be written in a hierarchical form that decouples the stability analyses of the horizontal and vertical directions. We leverage these properties to find a stabilizing class of functions for foot placement. The torso control is also proved to be decoupled using singular perturbation theory and is stabilized through a feedback linearization controller. We also take advantage of the proposed framework's flexibility and extend it to include a new reflex-based uneven-terrain walking control scheme. We test the controller for various desired walking speeds (0 to 2.5 m/s), for stepping up and down unexpected obstacles (15 cm), and for high-speed walking on a random uneven terrain (up to 10 cm of step-ups and step-downs and up to 1.8 m/s). The results show successful performance of the controller and its stability and robustness against various perturbations. [ABSTRACT FROM AUTHOR]

In this paper, a new value set based approach is presented to study the robust stability of a fractional order plant with parametric uncertainty of the interval type by using a fractional order proportional integral controller. The concept of interval uncertainty means that the parameters of the system transfer functions are uncertain parameters that each adopts a value in a real interval. Based on the zero exclusion principle, it is necessary to check whether the value set of the characteristic polynomial for the infinite frequency range [ 0 , ∞) includes the origin or not. To this end, in this paper, an auxiliary function is defined. The sign of this auxiliary function within a finite frequency range verifies whether the origin is included in the value set of the characteristic polynomial or not. The upper bound and the lower bound of this finite frequency range are obtained using the triangle inequality. Finally, the results of the numerical examples are provided, which confirm the effectiveness of the paper results. [ABSTRACT FROM AUTHOR]

Stewart platform or other parallel manipulators with a Stewart structure are commonly used in flight simulators, surgical operations, medical rehabilitation processes, machine tools, industrial applications, etc. Therefore, researchers have paid attention to position control of these manipulators in addition to their design and development process. In this study, a developed Stewart platform and its inverse kinematic analysis are presented first. Then, a model-free control scheme called a high order differential feedback controller scheme is designed for the Stewart platform in order to improve its trajectory tracking performance and robustness against to different reference trajectories. Real-time trajectory tracking experiments with varied reference trajectories are carried out to show the robustness and effectiveness of the high order differential feedback controller scheme compared to the traditional proportional–integral–derivative controller of which the parameters are optimally tuned. The obtained visual trajectory tracking results and numerical performance results based on error-based performance measurement metrics such as integral of absolute error, integral of squared error, and integral of time-weighted absolute error are provided for both the proposed high order differential feedback controller scheme and the optimal tuned proportional–integral–derivative controller. Experimental results show that the proposed high order differential feedback controller scheme is more robust than the proportional–integral–derivative controller. Furthermore, the high order differential feedback controller scheme has superiority in both transient and steady-state responses and even the parameters of the proportional–integral–derivative controller are optimally tuned. [ABSTRACT FROM AUTHOR]

To date, a novel class of smart materials, known as ionic polymer–metal composites, have been intensively studied because of their huge potential applications in robotics, microelectromechanical systems, biomedical devices, and artificial muscles. The position tracking control of the ionic polymer–metal composite actuators is one of the challenging tasks due to the highly nonlinear, uncertain, and unmodeled dynamics. These inaccurate and unmodeled dynamics cause the unwanted disturbances which reduce the control performance. Therefore, a robust feedback controller for position tracking of the ionic polymer–metal composite actuators is necessary. To address this issue, this article presents a super-twisting sliding mode controller combined with integral-chain differentiator as state observer. The main advantage of the proposed method is its potential to estimate the states of the system continuously. As a result, the controller not only eliminates the parameter uncertainties and external disturbance but also it can overcome the chattering problem. The results confirm the feasibility and efficiency of the proposed method both in simulation and experiment. [ABSTRACT FROM AUTHOR]

In recent years, unmanned aerial systems have attracted great attention due to the electronic systems technology advancements. Among these vehicles, unmanned helicopters are more important because of their special abilities and superior performance. The complex nonlinear dynamic system (caused by main rotor flapping dynamics coupled with the rigid body rotational motion) and considerable effects of ambient disturbance make their utilization hard in actual missions. Attitude dynamics have the main role in helicopter stabilization, so implementing proper control system for attitude is an important issue for unmanned helicopter hovering and trajectory tracking performance. Besides this, experimental utilization of low-cost flight control system for unmanned helicopters is still a challenging task. In this article, dynamic modeling, system identification, and robust control system implementation of roll and pitch dynamics of an unmanned helicopter is performed. A TRex-600E radio-controlled helicopter is equipped with a novel low-cost flight control system designed and constructed based on Raspberry Pi Linux-based microcomputer. Using Raspberry Pi makes this platform simpler to utilize and more time and cost-effective than similar platforms used before. The experiments are performed on a 5-degree-of-freedom testbed. The robust control system is designed based on H ∞ method and is evaluated in real flight tests. The experiment results show that the proposed platform has the ability to successfully control the roll and pitch dynamics of the unmanned helicopter. [ABSTRACT FROM AUTHOR]

In this paper, a new nonlinear vibration control scheme using piezoelectric actuator is proposed for a flexible plate with a free vibration and sudden perturbations. First, the effect of hysteresis nonlinearity from the piezoelectric actuator is considered by Prandtl-Ishlinskii (P-I) hysteresis model. Simultaneously, a dynamic model of the flexible plate with piezoelectric actuator is considered. Then, based on the dynamic model of the flexible plate, operator-based controllers are designed to guarantee the robust stability of the nonlinear control system. In addition, for ensuring the desired vibration control performance of the flexible plate with a free vibration and sudden perturbations, operator-based compensation method is given by the proposed design scheme. In the designed compensator, the desired compensation performances of tracking and of perturbations are obtained by increasing the number of designed n-times feedback loops. Finally, both of numerical simulation and experimental result are shown to verify the effectiveness of the proposed design scheme. [ABSTRACT FROM AUTHOR]

The integration of renewable energy resources to DC microgrid has captured the attention of the researchers in recent years. One of the active field of application of DC distribution is the islanded DC microgrid (DC ImG). The DC ImG present numerous challenges to researchers. Among many challenges, the regulation of voltage and stability of the system is indispensable to efficient operation. The voltage stability problem becomes more prominent when the system is exposed to disturbances and possess uncertainties in parameters. However, challenges can be overcome by skilful design of a robust controller for the system. Therefore, in this paper, an output-feedback based centralized robust control scheme is proposed. The proposed controller is designed to maintain good control performance in the presence of parametric uncertainties and exogenous disturbances. The uncertainties of the DC microgrid is modelled as a linear time-varying state-space system. The upper and the lower bounds of the time-varying parameters are determined by a Lebesque-measurable matrix. To attenuate the exogenous disturbances of the system H ∞ based output-feedback controller is designed. The system stability is assured by the Lyapunov function candidate. The output-feedback controller needs only the voltage measurement; therefore, it requires less communication bandwidth as compared to the state-feedback. To obtain the controller parameters linear matrix inequality constraints are formulated and solved. The performance of the proposed controller is verified via simulations and compared with the existing schemes. [ABSTRACT FROM AUTHOR]

In this paper, a robust model predictive control (MPC) scheme is developed for non-linear systems. We propose a new modeling approach, entitled piecewise non-linear, for plants with multiple operating points and with unstructured uncertainties. The systems, in each subregion, are composed of an affine model perturbed by an additive non-linear term which is locally Lipschitz. Considering a non-linear term in the model changes the control problem from a convex program to a non-convex one, which is much more challenging to solve. A standard dual-mode control strategy is introduced by parameterizing the infinite horizon control moves into a number of free control moves followed by a single state feedback law. The designed controller is robust against model uncertainty and guarantees system stability under switching between subregions. Numerical examples on a highly non-linear chemical process and another non-linear system are used to evaluate the applicability of the proposed method. Simulation results show a better performance in terms of speed of convergence and feasibility compared with the conventional robust MPC designs. [ABSTRACT FROM AUTHOR]

Tilt rotor unmanned aerial vehicles exhibit their effectiveness via a novel and convenient structure. However, the flight control system is a critical problem in need of a robust solution. Focusing on its flight features, which display strong nonlinear and varying dynamics, caused by complexity in the aerodynamic layout and tilting structure, a practical control scheme is proposed to meet such technical issues. This paper first develops the nonlinear model, consisting of the interference between rotors and the wing body, relying on wind tunnel technology. A simplified linear model that decomposes the longitudinal and lateral components is used in order to facilitate controller design. Then, a time-scale separation decoupling control scheme based upon active disturbance rejection control is proposed to cope with control challenges. Introducing the concept of virtual control input, an effective control allocation is obtained by choosing the appropriate bandwidth in the frequency domain. The extended state observer is applied to estimate and compensate for unknown total disturbances and model uncertainties. Finally, robustness verification, successful test-bench experiments, and practical flight tests that show the fast tracking and disturbance rejection of the active disturbance rejection control controller are discussed. The proposed practical coupling rejection control design demonstrates its capability to employ a single input single output method to control a tri-tiltRotor flying wing unmanned aerial vehicle relying on active disturbance rejection control. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel problem in control systems area involving the control of a magnetic needle in the presence of an external magnetic field. A magnetic needle when restricted to rotate about a single axis in an external magnetic field, by pivoting its center will produce a stable and unstable equilibrium. Here, we present the detailed mathematical modeling of the 1-D inverted magnetic needle system and its control in the unstable equilibrium point. We use sliding mode controller (SMC) to achieve the control objectives. The simulation results are validated with the experimental results. For achieving a close match, we consider sensor and actuator nonlinearities. Further, its robust performance is compared with proportional-derivative (PD), proportional-integral-derivative (PID) controllers in the presence of system parameter uncertainty, disturbance, and sensor delay. We also study the effect of change in SMC parameters, proportional and derivative gains on the system performance. It is to be noted that the proposed experimental setup can be extended to a much more general and complex system, both in modeling as well as control design leading to a new benchmark problem in the control system. [ABSTRACT FROM AUTHOR]

One of the most difficult challenges in robot motion planning is to account for the behavior of other moving agents, such as humans. Commonly, practitioners employ predictive models to reason about where other agents are going to move. Though there has been much recent work in building predictive models, no model is ever perfect: an agent can always move unexpectedly, in a way that is not predicted or not assigned sufficient probability. In such cases, the robot may plan trajectories that appear safe but, in fact, lead to collision. Rather than trust a model's predictions blindly, we propose that the robot should use the model's current predictive accuracy to inform the degree of confidence in its future predictions. This model confidence inference allows us to generate probabilistic motion predictions that exploit modeled structure when the structure successfully explains human motion, and degrade gracefully whenever the human moves unexpectedly. We accomplish this by maintaining a Bayesian belief over a single parameter that governs the variance of our human motion model. We couple this prediction algorithm with a recently proposed robust motion planner and controller to guide the construction of robot trajectories that are, to a good approximation, collision-free with a high, user-specified probability. We provide extensive analysis of the combined approach and its overall safety properties by establishing a connection to reachability analysis, and conclude with a hardware demonstration in which a small quadcopter operates safely in the same space as a human pedestrian. [ABSTRACT FROM AUTHOR]

This study investigates a modified electromechanical actuator for a guided ammunition fin control system. This modification, which is required due to space limitations, is the use of an eccentric type inverted slider crank mechanism instead of a centric type inverted slider crank mechanism. Brushless DC motor-driven mechanism is modeled experimentally. Using the obtained model, the H∞ type robust position controller is synthesized in the simulation environment and applied to the real system in hardware in the loop tests. The effectiveness of the proposed mechanism and the performance of the synthesized robust position controller are verified by comparing the pre-determined performance requirements and the obtained tests results. It has been shown that for a constant volume, the eccentric type mechanism provides about a 7.6% reduction ratio advantage over the centric type mechanism. [ABSTRACT FROM AUTHOR]

The sound level inside an automobile cabin plays a major role in the passengers' comfort. Active noise control has been widely used to reduce the sound level inside the car cabin. This article presents a design of an active and robust sound control system that can still be efficient despite the changes inside the passengers' compartment caused by the movement of the occupants. Initially, the coupled acoustic structural analysis is done on a simplified model of an automobile cabin by using finite element and modal coupling methods. Then, the uncertainty of the sound field inside the car, due to the presence of the occupants and the displacement of their heads, is investigated. A multi input multi output robust feedback control strategy, using the H∞ method and considering the unstructured uncertainty of the acoustic structural system, is proposed to reduce the sound pressure level at the ears of all the occupants. In order to achieve performance targets in a broad bandwidth and to reduce the waterbed effect, an optimization is performed on the weight function coefficients. The results show that in the frequency range of 0–334 Hz, the controller has an acceptable performance which is robust to changes in the interior sound field. [ABSTRACT FROM AUTHOR]

This paper focuses on event-triggered finite-time consensus problem of second-order multi-agent system, which is subjected to external bounded disturbance. First, a novel finite-time consensus control algorithm based on the event-triggering control scheme is proposed. The proposed algorithm contains a saturation function that is disturbance rejection and aims at eliminating the chattering problem caused by the discontinuity of the control algorithm in some existing work. Further, the utilization of saturation function reduces damages to the actuators and decreases energy consumptions in practical applications. Second, an event-triggering function is developed to generate the control event sequences, which is fully continuous communication free and avoids continuous update of the controller by contrast with real-time control method and continuous communication event-triggered control scheme. Third, finite-time bounded consensus can be reached with the scale of the convergence region adjusted by appropriate parameter selecting. A rigorous proof based on Lyapunov stability analysis is given to verify that the event-triggered control algorithm, under the derived conditions, solves the second-order finite-time consensus with chattering free and being robust to external disturbances as well as excluding the Zeno behavior. Finally, two simulation examples are performed to validate the effectiveness of the results. [ABSTRACT FROM AUTHOR]