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Microgrid is a key to an efficient and resilient power grid operation. Thus in this paper, a robust control scheme is implemented namely modified frequency locked loop (MFLL), proficient in eliminating the voltage and current fluctuations because of phase/frequency variation. Therefore, enhancing the consistency of the supply across nonlinear load through a smooth transition from utility-interactive to islanded mode. It also achieves accelerated convergence and reduced steady-state error. MFLL is an easy control technique, with only one interfacing voltage source converter, which delivers a stable supply to critical loads during different operating modes. The implemented system has the main advantage of the capability of power-sharing between distributed generations (DGs) systems while regulating the voltage at the DC link. It also provides power quality improvement through harmonics suppression; voltage regulation during contingencies like unbalance in load and compensation in reactive power at the common coupling point following the prerequisite of the system. The performance through the implemented control algorithm is brought about in MATLAB 15b/Simulink platform. The performances of results are compared with already reported control strategies. Thus, simulated results comparison with existing work presents the competence of the implemented control strategy under dynamic conditions.

In this paper, afull-car prototype of the recently proposed mechatronic suspension, Series Active Variable Geometry Suspension (SAVGS), is developed for on-road driving experimental proof of concept, aiming to be adopted by suspension OEMs (original equipment manufacturers) as an alternative solution to fully active suspensions. Particularly, mechanical modifications are performed to both corners of the front double-wishbone suspensionof a production car, with active single-links attached to the upper-ends of the spring-damper units, while both corners of the rear suspension remain inthe original (passive) configurations.The mechanical modifications involve innovatively designed parts to enable the desired suspension performance improvements, while maintaining ride harshness at conventional levels.Areal-time embedded system is further developed to primarily implement:1) power supply, data acquisition and measurementsof the vehicle dynamics related variables, and 2) robust control application for the ride comfort and road holding enhancement, which is based on a derived linearized model of the full-car dynamics and a newly synthesizedH-infinity control scheme. Results obtained from on-road driving experiments are inessential agreement with numerical simulation results also produced. Overall, the full-car prototypeof SAVGS demonstrates promising suspension performance,with anaverage 3 dB attenuation (or equivalently 30% reduction) of the chassis vertical acceleration at aroundthe human-sensitive frequencies (2-5Hz),as compared to the original vehicle with the passive suspension system. More importantly, the prototype also indicatesthe practicality of the solution, as the SAVGS retrofit to a real car is achieved by simple mechanical modifications, compact actuator packaging, smallmass increment(21.5kg increase with respect to the original vehicle), limited power usage (an average value of 134W in DC batteries with a Class D random road) and acceptable economic cost.

In this paper, an uncertainty-based optimal control framework is proposed for the Hybrid Energy Storage System (HESS) which allows for improved frequency regulation of a distributed micro-grid. The control architecture updates the penalty factor of the controller quality function automatically and provides policy to the HESS which consists of battery and ultra-capacitor banks. The HESS supports a Photo-Voltaic Distributed Energy Resource (PVDER) during grid dynamics in the presence of frequency oscillations by managing the DC link voltage. The penalty factor update is based on the sensitivity of the battery and ultra-capacitor power contribution to the frequency change and is dynamically changing. These changing gains and penalty factors optimize the HESS output. The approach is generalized by making it compliant for extensions that include assimilation of affine, stochastic, linear time-variant, and trajectory following non-linear systems. A modified IEEE 123 bus distribution system is used as a test system to validate the proposed architecture and provide a quantitative comparison with the conventional frequency-droop approach. It has been observed that the proposed architecture provides around 50\% improvement frequency regulation when compared to optimal control.

To continue the shift from batch operations to continuous operations for a wider range of products, advances in real-time process management (RTPM) are necessary. The key requirements for effective RTPM are to have reliable real-time data of the critical process parameters (CPP) and critical quality attributes (CQA) of the materials being processed, and to have robust control strategies for the rejection of disturbances and setpoint tracking.Real-time measurements are necessary for capturing process dynamics and implement feedback control approaches. The mass flow rate is an additional important CPP in continuous manufacturing compared to batch processing. The mass flow rate can be used to control the composition and content uniformity of drug products as well as an indicator of whether the process is in a state of control. This is the rationale for investigating real-time measurement of mass flow of particulate streams. Process analytical technology (PAT) tools are required to measure particulate flows of downstream unit operations, while loss-in-weight (LIW) feeders only provide initial upstream flow rates. A novel capacitance-based sensor, the ECVT sensor, has been investigated in this study and demonstrates the ability to effectively measure powder mass flow rates in the downstream equipment.Robust control strategies can be utilized to respond to variations and disturbances in input material properties and process parameters, so CQAs of materials/products can be maintained and the amount of off-spec production can be reduced. The hierarchical control system (Level 0 equipment built-in control, Level 1 PAT based PID control and Level 2 optimization-based model predictive control) was applied in the pilot plant at Purdue University and it was demonstrated that the use of active process control allows more robust continuous process operation under different risk scenarios compared to a more rigid open-loop process operation within predefined design space. With the aid of mass flow sensing, the control framework becomes more robust in mitigating the effects of upstream disturbances on product qualities. For example, excursions in the mass flow from an upstream unit operation, which could force a shutdown of the tablet press and/or produce off-spec tablets, can be prevented by proper control and monitoring of the powder flow rate entering the tablet press hopper.In this study, the impact of mass flow sensing on the control performance of a direct compaction line is investigated by using flowsheet modeling implemented in MATLAB/Simulink to examine the control performance under different risk scenarios and effects of data sampling (sampling time, measurement precision). Followed by the simulation work, pilot plant studies are reported in which the mass flow sensor is integrated into the tableting line at the exit of the feeding-and-blending system and system performance data is collected to verify the effects of mass flow sensing on the performance of the overall plant-wide supervisory control.

Individual pitch control technology can reduce asymmetric loads of wind turbines. The assumption of three completely symmetrical blades is the design premise of traditional individual pitch controller. However, production, assembly, and operation will inevitably lead to aerodynamic imbalanced characteristics for blades. Therefore, the failure mechanism of the traditional individual pitch controller is analyzed based on the frequency-domain decomposition method and verified by the simulation analysis. Based on the failure mechanism, the uncertainty modeling method is proposed to handle aerodynamic imbalanced loads. Then the robust individual pitch control is designed based on the product perturbation model. The D–K iterative algorithm is used to solve the H ∞ -optimization for the controller. The proposed robust individual pitch controller can effectively suppress imbalanced loads through simulation verification.

For the speed control system of autonomous electric vehicle (AEV), challenge happens with how to determine an appropriate driving speed to satisfy the dynamic environment while resisting uncertainty and disturbance. Therefore, this paper proposes a robust optimal speed control approach based on hierarchical architecture for AEV through combining deep reinforcement learning (DRL) and robust control. In decision‐making layer, a deep maximum entropy proximal policy optimization (DMEPPO) algorithm is presented to obtain an optimal speed via dynamic environment information, heuristic target entropy and adaptive entropy constraint. In motion control layer, to track the learned optimal speed while resisting uncertainty and disturbance, a robust speed controller is designed by the linear matrix inequality (LMI). Finally, simulation experiment results show that the proposed robust optimal speed control scheme based on hierarchical architecture for AEV is feasible and effective.

For a practical engineering system, disturbances usually have a negative impact on system performance. Especially, when the system physical constraints (e.g., actuator amplitude saturation and input channel constraint) are present, the study for antidisturbance controllability (ADC) is of paramount importance. This article presents the concepts of disturbance estimability, disturbance compensability, and an enhanced antidisturbance control (EADC). From the viewpoint of control system design, an example of spacecraft attitude control is given. The control constraints and multiple disturbances are explicitly analyzed for the sake of attitude control system design of flexible spacecraft. Subsequently, an EADC approach with integration of the disturbance observer-based control (DOBC) and active disturbance rejection control (ADRC) is proposed, based on the characteristics of disturbances exposed. Moreover, prescribed performance approach is incorporated into the spacecraft attitude tracking control. In consequence, the presented control can not only achieve superior antidisturbance capability than DOBC or ADRC, but also quantify the control performances. Numerical simulations and hardware-in-the-loop tests exemplify the applicability of the proposed scheme.

The development of effective load relief strategies is key to the improvement of launcher flight performance as it enables a joint increase of wind resilience and decrease of mass. This is particularly relevant for reusable launchers, which are aimed at maximising operational availability and payload capacity. Yet, despite various load relief advances in the aeronautics and wind energy sectors, classical feedback-only techniques remain the state-of-practice for launchers. In this article, an improved load relief functionality for reusable vehicles is proposed based on the use of a disturbance observer for on-board wind anticipation and a load relief compensator driven by the estimate of the wind for its amelioration. Two space systems are used to demonstrate the capabilities of the proposed approach. First, it is applied to a 3 degrees-of-freedom nonlinear simulation model of DLR’s EAGLE vertical-flight demonstrator. Then, it is applied to a 6 degrees-of-freedom nonlinear simulation model of a generic lightweight, reusable launch vehicle. For both cases, the results highlight the benefits of using this type of wind-estimation/load-relief compensation schemes. Further, for the second case, which uses thrust vector control and planar fins for ascent and descent attitude control, it is also shown that the use of fins during ascent (which is not common practice), can further improve launcher performance.

This article deals with a robust control strategy for a distributed generation system (DGS), which operates in both islanded and grid-connected modes. Generally, in the low-voltage islanded mode of DGS, the point of common coupling (PCC) voltages are unbalanced due to the unbalanced load connection. Therefore, in an islanded mode of DGS, the load-side converter is controlled using the improved proportional resonant controller to maintain the PCC voltages quality within the IEEE-1547 standard. Moreover, the DGS is capable to synchronize to the grid without any transient current. During the change of modes of DGS, large transients occur in the battery current due to the switching of battery control. This problem is resolved by the presented bidirectional dc–dc converter control strategy and robust inner-loop quadrature second-order generalized integrator-based phase-locked loop. The effectiveness of this DGS control strategy is verified by the corresponding MATLAB/Simulink platform under load unbalance, solar irradiance changes, and during the mode of switching. Moreover, the simulation results are validated using the test results and show the robustness of the control strategy during abnormal grid voltage condition.

Nonlinear effects and external disturbances can severely impact the control of an autonomous race car at the handling limits. State-of-the-art approaches do not take these uncertainties explicitly ...

In this paper, the stability issue of networked system with dynamical topology in intelligent vehicle is studied. The systems are comprised by multi-vehicles coupled by vehicle network. The topological structure of vehicle network is subject to jump, and control signals are exchanged by the communication network with random network-induced delay. Firstly, the discrete-time state space equation for coupled intelligent vehicle with switching topology is modeled. Then, two output feedback controllers are designed by considering the coupling of controllers or not. In which, a new output feedback coupled-controller is designed in order to achieve decouple. Furthermore, the delay-dependent stability conditions on Lyapunov-functional method are given to guarantee the stochastic stability of the closed-loop networked system. Finally, a simulation experiment is executed to illustrate the designed method and verify the stability performance.

In this paper, a hybrid approach based on robust control and radial basis function network has been proposed to adjust the output power and generator speed of a variable speed wind turbine. The system is composed of four characteristics: aerodynamics, turbine mechanism, generator dynamics, and actuator dynamics. Such a system has high nonlinearity essence and involves high dynamic mutation. To guarantee the robust stability of internal dynamics, the linearized model of wind turbine has been derived around its operating points. Afterward, H2/H∞ state feedback law has been determined by solving some linear matrix inequalities. Moreover, to keep the system close to its working conditions, a nonlinear compensator has been designed. For instant estimation of the nonlinearity of wind turbines, RBF has been used through an online learning procedure. The performance of the proposed algorithm has been assessed because of internal stability, tracking performance, and eliminating the system’s nonlinearities in the presence of wind with fixed and variable speed.

For in-wheel driving vehicle electric vehicles (EVs), mechanical electromagnetic coupling effect caused by the air gap deformation in permanent magnet synchronous hub motor and intensified by the road excitation deteriorates the EVs performance. In this paper, after studying the numerical method for multi-field coupling problems of hub-driving vehicle under the coupled action of electromagnetic field and mechanical field. The experimental validation is investigated. The results indicate that the multi-field coupling effect in hub-driving motor worsens the dynamics performance of the vehicle. To enhance the vehicle performance, suppress mechanical electromagnetic coupling effect and, at same time, reduce the influence of controllable suspension time delay, a delay-dependent H∞ controller is designed based on Lyapunov theory. By applying the particle swarm optimization (PSO) algorithm and the linear matrix inequality theory, the desired output controller gain is derived. Numerical simulations reflect that the active suspension controller considering control time delay not only achieves the favorable riding comfort performance and restrains the coupling effect in hub driving motor but also ensures the suspension deflection and the safety performance requirement. Moreover, it maintains the closed-loop asymptotically stability regardless of t the variation on the sprung mass and control time delay.

This paper deals with a control system and an algorithm of Lithium-ion battery fast charging. Charger structure consists of an electromagnetic filter, two parallel full-bridge DC-DC converters with low-pass filter. The parallel full-bridge DC-DC converter has two isolated transformers. Sometimes, changes are observed in the transformer ratio and the leakage inductance due to a fault caused by partial short circuit in the transformer. In addition, a transformer is rarely open circuit by a fault or out of service for maintenance. So, a control system which is based on sliding mode control is used for covering the uncertainties of transformer ratio and its leakage inductance. The transformer ratio has an important role in state-space equation of the charger circuit and has important effects on the control system in constant current and constant voltage modes. Therefore, this paper analyses the impact of the parameters of isolated transformer and the control system on the reference signal tracking and the accuracy of current sharing between two parallel DC-DC converters. The simulation results show the effectiveness of the proposed control system.

In order to improve the transient and static performances of power following system in series hybrid electric vehicle (SHEV), this paper presents a delay-dependent MIMO robust control strategy. The control scheme coordinates the engine and the generator in the auxiliary power unit (APU) to reach the optimal speed and torque synchronously to output the required power. By the way of Pade approximation and multiple linear regression analysis, the delay time uncertainty in engine torque response is emphatically analyzed, which improves the accuracy of the engine torque model. The stability of the system is ensured theoretically by the Lyapunov Stability Theory and a sufficiently robust stability condition is established in terms of the linear matrix inequality (LMI). To avoid the problem of power reverse undershoot, a method of directly limiting the generator torque command is adopted, which is analyzed to not affect the stability of the system. The effectiveness and practicability of the proposed control strategy are demonstrated through numerical simulations and experiments.

A new adaptive robust control method based on Udwadia-Kalaba(U-K) approach which can be applied to the underactuated system is designed and used to a two-wheeled inverted pendulum system in this paper. We separate this typical underactuated system into two subsystems(forward subsystem and yaw subsystem), which are fully underactuated and actuated. For these different subsystems, we use different control methods. We apply an adaptive robust control method which has been proved many times to the fully actuated subsystem. Based on this adaptive robust method, a new control strategy can be redesigned and applied to the underactuated subsystem by modifying the adaptive law and other things. This adaptive robust control with a leakage-type adaptive law could guarantee the uniform boundedness and uniform ultimate boundedness of the system. Finally, the simulation is executed to demonstrate the advantage and simplicity of the proposed method.

A method of robust control of a specialized manipulator designed to work as part of a robotic complex for servicing vertical surfaces is proposed and studied. The complex consists of a wheeled platform, a wheeled vertical motion robot with a vacuum contact device and a manipulator. In the transport position, the robot is attached to the operating element (gripper) of the manipulator and is located on the platform so that its contact plane is almost parallel to the plane of the platform. After the platform approaches the wall, the manipulator brings the robot into the working position, bringing its contact plane to the surface of the wall. Then the vacuum pump of the robot is switched on, the robot is sucked against the wall, disconnects from the grasp of the manipulator, and then moves along the wall in autonomous mode. This article describes the operation of the manipulator at the stage of bringing the robot into the working position.

Modern algorithms based on artificial neural networks (ANNs) are extremely useful in solving a variety of complicated problems in computer vision, robust control, and natural language analysis of sound and texts as applied to data processing, robotics, etc. However, for the ANN approach to be successfully incorporated into critically important systems, for example, in medicine or jurisprudence, a clear interpretation is required for the internal architecture of ANN and for ANN-based decision-making processes. In recent years, analysis methods based on various visualization techniques applied to computation graphs, loss function profiles, parameters of single network layers, and even single neurons have become especially popular as tools for creating explainable deep learning models. This survey systematizes existing mathematical analysis methods and explanations of the behavior of underlying algorithms and presents formulations of corresponding problems in computational mathematics. The study and visualization of deep neural networks are new poorly studied yet rapidly developing areas. The considered methods give a deeper insight into the operation of neural network algorithms.

The wind turbine system is one of the most challenging control problems in power systems due to its fast and slow dynamics and the optimal and robust control of the doubly fed induction generator i...

This paper presents analysis of number of steps required for the consensus in a leader-following discrete multi-agent system (DMAS) with discrete-time sliding mode protocols designed by Gao’s reaching law and power rate reaching laws. The DMAS is configured for communication with a fixed, undirected graph topology having one leader and other agents as followers. The sufficient condition for global stability is established using the Lyapunov function in both the cases. The efficacy of both the protocols is compared in simulation for number of steps required for the consensus of a homogeneous multiple two degree of freedom helicopter systems where the pitch angle and its velocity and yaw angle and its velocity are used for consensus. The simulation results reveal that the consensus performance due to protocol with power rate reaching law outperforms the protocol with Gao’s reaching law.

This work presents the design of state-feedback robust control law for a DC-DC three-port isolated converter, which interfaces a photovoltaic panel, a rechargeable battery, and an isolated output DC bus. First, the converter is represented through a state-space model that considers disturbances in both the photovoltaic and bidirectional (battery) input ports. The system is linearized around an average operational point, such that robust control techniques can be applied. Due to varying solar irradiation, battery charge, and load levels, the converter is subjected to step-like disturbances. The proposed controller is designed to maintain stabilization and voltage tracking performance in the presence of these disturbances. This approach is different from multiport control strategies usually employed in the literature, which are based on decentralized controllers that require the use of decoupling techniques that can lead to control problems. To ensure robustness, stabilization, and voltage tracking, an [Formula: see text] approach with pole placement restrictions and based on linear matrix inequality (LMI) constraints is formulated and solved. Finally, the performance of the proposed controller has been verified via hardware-in-the-loop (HIL) experiments and compared with a decentralized control strategy.

This article presents the design and evaluation of robust controllers, based on linear programming, Kharitonov's theorem and Chebyshev's theorem, in order to enhance the performance of a typical structure of multistage converters present in direct current (dc) systems. In such electric power distribution systems, point-of-load converters act as a constant power load (CPL), which introduces a destabilizing nonlinear effects to their supply bus voltage. The multistage converter system uses a simplified scheme based on a cascaded converter, which is comprised of two dc–dc buck converters in a series connection. The robust controllers evaluated overcome the negative incremental impedance instability problem due to CPL, which causes a high risk of instability in interconnected converters. Thereby, the robust controllers evaluated ensure robust control performance and stability with a minor performance degradation compared to a conventional controller when the cascaded converter system is subjected to parametric uncertainties. The control methodologies evaluated are applied in both dc–dc buck converters. Assessments on the performance of the control methodologies evaluated are conducted. Experimental validations on a 160-W dc–dc cascaded converter system test board are carried out to verify the theoretical claims.

An energy-efficient smart home generally integrates renewable energy sources (RESs) with intelligent energy devices (IEDs) to make itself cost-efficient. However, the stochastic nature of the RESs and IEDs makes the power network uncertain, and it degrades the economic efficiency of the smart home. Hence a co-simulation based intelligent home energy management system (HEMS) is proposed in this article. It interconnects the rolling horizon-based model predictive energy scheduling mechanism with robust control strategies. It manages the load following energy supply entities (ESEs) optimally and efficiently. A time-ahead scheduler integrates an optimal algorithm to estimate the cost-optimal (e.g., minimizing total energy cost) decision signals for various ESEs by incorporating component based losses and efficiencies. Besides, a real-time distributed robust control strategy is established executing a coordinated energy sharing mechanism by incorporating an auxiliary power source. Time-triggered low-jitter wireless communication architecture is adopted to transfer the optimal decision signals from the central scheduler to the distributed device level local controller. A scenario based comparison of various ac/dc models of a home area power network evaluates the strength of the prospective HEMS.

Increasing connectivity to the Internet for remote monitoring and control has made cyber-physical systems more vulnerable to deliberate attacks; purely cyber attacks can thereby have physical consequences. Long-term, stealthy attacks such as Stuxnet can be described as Advanced Persistent Threats (APTs). Here, we extend our previous work on hypergames and APTs to develop hypergame-based defender strategies that are robust to deception and do not rely on attack detection. These strategies provide provable bounds—and provably optimal bounds—on the attacker payoff. Strategies based on Bayesian priors do not provide such bounds. We then numerically demonstrate our approach on a building control subsystem and discuss next steps in extending this approach toward an operational capability.

Wind Energy Conversion System (WECS) using a Doubly Fed Induction Generator (DFIG) is popular due to its control flexibility and higher conversion efficiency, but maintaining the operational stability and optimal efficiency under dynamic wind conditions is still a control challenge. In this paper, a nonlinear mathematical model for a DFIG based WECS was developed from fundamentals and its characteristics near the operating point were studied. A Proportional Integral (PI) controller and a Linear Quadratic Regulator (LQR) controller were designed to control the system and the behavior of the closed-loop system with these controllers was studied. While the designed PI controller failed to ensure stability, the LQR controller was giving stability but an LQR controller is vulnerable to loss of stability under uncertainties due to parameter variations or changes in operating points. A suboptimal $$H_{\infty }$$ controller was then synthesized to obtain robust control. The closed-loop system performance of the DFIG system with the proposed controller was found to be stable and superior to PI and LQR controllers in terms of performance.

In this paper, a single parameter Guardian Map-based simple adaptive guidance and control architecture for spacecraft formation flying is developed. When compared with traditional vehicles, the dynamics of spacecraft features larger non-linearities, tighter coupling and higher uncertainty as the eccentricity of an orbit increases. In addition, most formation flying applications involve following bounded relative trajectories that are only applicable to circular orbits and hence becomes an unnatural trajectory when used on eccentric orbits, resulting in unnecessary fuel consumption. Making use of a combination of nonlinear Simple Adaptive Control and Guardian Map theories, a novel autonomous adaptive guidance and control system is developed such that the desired closed-loop stability of the system and asymptotic convergence is guaranteed throughout the orbit while tracking fuel-efficient natural trajectories that are applicable to eccentric orbits. Simulation results show various new types and sizes of bounded natural relative orbits to illustrate the increased performance and robustness of the proposed adaptive controller compared to a conventional non-adaptive linear quadratic regulator found in literature.

The calibration of a zoom lens camera depends on the precision of the localization of control points. At a long focal length, the narrow depth-of-field (DOF) causes defocused blurring and an inevitable decrease in accuracy in control points localization. In particular, the camera calibration requires multiple control points defined on calibration patterns acquired at various camera angles. However, clear pattern images are difficult to obtain owing to the narrow DOF. We propose a robust and intuitive method to accurately estimate the control points in blurred images. To obtain control points that are less affected by blurring, we dynamically varied the circle size in the patterns and identified the local maximum point using the intensity gradient of accumulated concentric circles. This approach is robust to blurring and can be employed at all zoom levels. In our experiments, the error of the control point estimation was measured while varying the angles of the calibration patterns and the degree of blurring. Compared with the conventional checker pattern method, the performance of the proposed method in the estimation of the control points was better and its related camera parameters with severely defocused images were settled.

The advancement in the field of aerial robotics and control engineering has created many opportunities for the utilization of Unmanned Aerial Vehicles (UAVs). Applications of UAVs from precision agriculture to delivering medicines and products at our doorsteps cannot be ignored. Quadrotors are the widely studied as sub-category of the rotor-type UAVs. Their ability to hover, vertical take-off and landing along with their small size and simple design make them suitable for many real-life applications like medicine delivery in containment zones struck with COVID-19. But under actuation caused due to four rotors to control six inputs creates instability in their flight. In this paper, Quadrotors and various Quadrotor applications are discussed. The various modeling and control techniques are discussed. Controlling techniques like LQR, LQG, PID and robust control is implemented for position, attitude and altitude control. Results for Proportional Integral and Derivative (PID) and Model Reference Adaptive Control (MRAC) of model generated using force-moment mathematical model are analyzed and compared using MATLAB Simulink. These control techniques are implemented for position, attitude and altitude control. In this paper, it has been concluded that MRAC performs better as compared to PID controller for position, attitude and Altitude control of Quadrotor.

This paper introduces a model-based robust adaptive input-output control framework for a family of robotic systems that include under-actuation, nonholonomic, and constrained properties. The propos...

In recent times, renewable energy demand is rapidly increasing worldwide. Offshore wind energy is one of the alternative solutions to the problems posed by non-renewable energy resources. The kinetic energy of the wind is converted to mechanical energy by using an offshore floating wind turbine (OFWT). The efficiency of the OFWT is dependent upon the vibrational effect induced by the environment. In this paper, for the mitigation of this vibrational effect, a new model of barge-type OFWT is designed by using an active control strategy called translational oscillator with a rotational actuator (TORA). The disturbance observer (DO) based advanced control techniques including robust backstepping sliding mode control (BSMC), backstepping integral sliding mode control (BISMC), backstepping nonsingular terminal sliding mode control (BNTSMC), and a new backstepping integral nonsingular terminal sliding mode control (BINTSMC) technique, are devised for the stabilization of OFWT model. The comparison of these techniques is carried out by using MATLAB/SIMULINK which validates the feasibility and correctness of the proposed OFWT model and control techniques.

Abstract Overexpression of recombinant proteins in Escherichia coli results in misfolded and non-active protein aggregates in the cytoplasm, so-called inclusion bodies (IB). In recent years, a change in the mindset regarding IBs could be observed: IBs are no longer considered an unwanted waste product, but a valid alternative to produce a product with high yield, purity, and stability in short process times. However, solubilization of IBs and subsequent refolding is necessary to obtain a correctly folded and active product. This protein refolding process is a crucial downstream unit operation—commonly done as a dilution in batch or fed-batch mode. Drawbacks of the state-of-the-art include the following: the large volume of buffers and capacities of refolding tanks, issues with uniform mixing, challenging analytics at low protein concentrations, reaction kinetics in non-usable aggregates, and generally low re-folding yields. There is no generic platform procedure available and a lack of robust control strategies. The introduction of Quality by Design (QbD) is the method-of-choice to provide a controlled and reproducible refolding environment. However, reliable online monitoring techniques to describe the refolding kinetics in real-time are scarce. In our view, only monitoring and control of re-folding kinetics can ensure a productive, scalable, and versatile platform technology for re-folding processes. For this review, we screened the current literature for a combination of online process analytical technology (PAT) and modeling techniques to ensure a controlled refolding process. Based on our research, we propose an integrated approach based on the idea that all aspects that cannot be monitored directly are estimated via digital twins and used in real-time for process control. Key points • Monitoring and a thorough understanding of refolding kinetics are essential for model-based control of refolding processes. • The introduction of Quality by Design combining Process Analytical Technology and modeling ensures a robust platform for inclusion body refolding.

This paper presents a robust detumbling strategy for a spacecraft equipped with a robotic manipulator to detumble a non-cooperative target with unknown inertial parameters. Reported detumbling strategies in the literature have been formulated with the assumption of accurately known target inertial parameters (mass, inertia tensor, center of mass location) and without consideration of magnitude limits on the robotic spacecraft’s control inputs. In reality, it is unrealistic to assume accurate knowledge of the target’s inertial parameters and the robotic spacecraft will be subjected to limits on its control inputs. In this paper, a novel detumbling strategy is presented to detumble targets with unknown parameters utilizing only bounds on their inertial parameters. A desired detumbling trajectory is delineated using only bounds on the target’s inertial parameters and subjected to end-effector force/torque limits. Magnitude constraints on the robotic spacecraft are taken into account by modeling them with a hyperbolic tangent function, which results in a system that is non-affine in its control inputs. To facilitate the development of the detumbling controller, an augmented model of the robotic spacecraft is formulated. Using bounds on the target’s inertial parameters, robust adaptive control approach is utilized to design the detumbling controller with the backstepping technique to ensure successful detumbling of the unknown target attached to the end-effector and rejection of its momentum. Numerical simulations have demonstrated the effectiveness of the proposed method.

Aiming at the problem that the navigation performances of unmanned underwater vehicle (UUV) may be affected by inaccurate prior navigation information and external environmental interference, which may make the accuracy and reliability of strapdown inertial navigation system (SINS) and global position system (GPS) integrated navigation results worse, positioning divergent and system even invalid, an adaptive H-infinite kalman filtering algorithm based on multiple fading factors (MAHKF) is proposed in this paper. Firstly, the time-varying adaptive fading factor is used to modify the filter parameters on-line to make the initial error of navigation filter converge quickly. Secondly, the H-infinite kalman filter of the SINS/GPS system is built on combining the advantages of robust control, which improved the system robustness under extreme external environment. Further, the adaptive threshold γ of the H-infinite kalman filter is introduced to make the filter adaptive to the environment change. Results of the simulation and experiment demonstrate that the initial error is converged at the beginning stage of navigation process, and the interference from external uncertainty inputs to the integrated navigation system are suppressed effectively with the proposed algorithm. Compared with the conventional kalman filter algorithm (KF), the position errors in three directions of the UUV are reduced by 66.57%,67.98% and 64.51% respectively with the proposed MAHKF.

One of the problems facing the Die Attach engineers at Front of Line is the lack of control of their Die Attach Recipes. Currently, all Recipes are stored on a computer that is accessed by all users and transferred to the Die Attach machine using a diskette via a simple file copy operation. This kind of setup is vulnerable to the tampering of the Recipes, which may lead to problems in the production line, affecting the quality of the product. It is also difficult in the current setup to know which user copied the Recipe or changed its contents, making those activities untraceable. Finally, the manual management of Die Attach Recipes by file copy raises the risk of human error. To increase the quality of production as well as to protect Recipes from tampering, a computer-based program has been developed to fix the issues in the current setup. The Die Attach Recipe Management System, or DRMS, is a computer program that can do the following: (1) protect the Die Attach Recipes to prevent unauthorized users from accessing and changing them; (2) monitor users who access the Recipes; and (3) simplify the recovery and storage process to eliminate human error problems.

In this work, an energy-efficient extractive dividing-wall column process with heat integration (E-DWC-HI) is proposed for the first time to separate the dichloromethane (DCM)–methanol (MeOH) azeotrope, which is a widely existing waste effluent in the pharmaceutical industry. The result of economic evaluation shows that the E-DWC-HI process is a preferred choice for the separation of DCM–MeOH mixture. Designing a robust control strategy is essential for the E-DWC-HI process. Thus, four control structures are proposed and tested under the disturbances of ±20% feed flow rate and ±5% feed composition. The basic control structure (CS1) and the double temperature difference control structure (CS2) both have a fixed vapor split. The dynamic response shows that the required purity cannot be met due to the loss of an important control degree of freedom. In CS3, variable vapor split is carried out by adjusting the pressures on the two sides of the dividing wall, and all product purities are held close to their set points except for MeOH product purity with an obvious offset. The dynamic performance of CS4 has been significantly improved by integrating pressure swing and pressure compensation. The offset of MeOH product purity is significantly reduced from 2.05 to 0.03%.

Chaotic secure communication via synchronization of chaotic systems has attracted increasing attention in recent years. This note aims to introduce the function projective synchronization (FPS) of ...

Distributed control is the most popular control strategy for controlling numerous slave devices. However, the performance of slave devices is hard to improve because the control algorithm is handled by the commercial slave devices. Therefore, this paper proposes a hybrid control structure that follows the concept of centralized control strategy and handles part of the control loop on the master computer in a distributed control system through EtherCAT fieldbus. In this study, different advanced control methods such as robust control and learning control were applied to handle the position control loop of a scanning mirror system in a selective laser melting (SLM) system with stringent demand of position error around 40 µm based on EtherCAT fieldbus. By designing a proper controller, the experiment results showed that the tracking performance was significantly improved. The tracking error dropped by about 80% after the proposed hybrid control structure was applied. By applying the proposed hybrid control structure, one can improve the high-performance-requirement devices, while reducing the calculation burden of the master computer for other low-performance-requirement devices by retaining the benefit of distributed control.

The problems of robust stabilization and adaptive robust controller design are considered for a class of uncertain neutral systems with time delays and nonlinear uncertainties. In this paper, Pade approximation is used to deal with input-delays, and the adaptation laws are proposed to estimate the norm of the unknown parameter uncertainties. Based on the improved Razumikhin-type theorem and the updated values, a class of delay-independent adaptive robust state feedback controllers is constructed to guarantee the uniform ultimate boundedness of uncertain neutral systems with input-delays and nonlinear uncertainties. Finally, the chemical two-stage dissolution tank is used to illustrate the effectiveness of the proposed method.

This paper develops a coordinated wide-area control of power system stabilizers (PSSs), static VAr compensators (SVCs), and supplementary damping controllers (SDCs) for damping low frequency oscillations (LFOs) in a power system embedded with multiple high voltage DC (HVDC) lines. The improved damping is achieved by designing a coordinated wide-area damping controller (CWADC) that employs partial state feedback. The design methodology uses a linear matrix inequality (LMI)-based mixed $H_2/H_\infty$ robust control for multiple operating scenarios. To reduce the high computational burden, an enhanced version of selective modal analysis (SMA) is employed that not only reduces the number of required wide-area feedback signals, but also identifies alternate feedback signals, in case of failure of the primary signals. Additionally, the impact of delays on the performance of the control design is investigated. The studies are performed on a 29 machine, 127 bus equivalent model of the Western Electricity Coordinating Council (WECC) system-embedded with three HVDC lines and two wind farms.

Modern greenhouses need a certain equipment to achieve the expected environmental temperature in a short time while saving energy. To achieve greenhouse temperature management and energy savings through intelligent control, a greenhouse mechanism model is first built to study the controller design for a greenhouse located in Yiyang city in this paper. Then, the model accuracy is verified by experimental data. Based on the verified model, two intelligent control technologies are proposed, namely, active disturbance rejection control and fuzzy active disturbance rejection control. Methods are adopted to adjust skylight opening and thermal air conditioning for greenhouse temperature control and energy savings. In 60 hours of continuous working time, fuzzy active disturbance rejection control takes 10 hours less than active disturbance rejection control to make the greenhouse temperature reach the ideal steady state, and the temperature overshoot is reduced by 60%. Through analysis, the proposed fuzzy active disturbance rejection control method for greenhouse temperature management can achieve 15% energy savings. The proposed intelligent control technology can also be applied to temperature management for real greenhouses.

Reactive and antisolvent crystallization processes are efficient techniques for the production of fine chemicals and pharmaceuticals. These processes are usually characterized by high levels of supersaturation and fast primary crystallization kinetics. Understanding the mixing mechanism and its interaction with various crystallization phenomena is advantageous for achieving robust control of these crystallization processes and the desired crystal properties. Much modeling effort has been devoted to accounting for the combined effects of mixing on various scales and the complicated kinetic phenomena involved in these processes as complementary to experimental investigations. This article provides a review on the numerical simulation of reactive and antisolvent crystallization processes with an emphasis on modeling the mixing effect. Relevant Lagrangian mechanistic micromixing models and probability density function (PDF) approaches are introduced followed by simulation examples from the literature. Various examples are categorized into four groups according to the different coupling between mixing, crystallization kinetics and flow field. Also, some suggestions on further model development are given to enhance their predictive performances and broaden the range of application.

International audience; Modern space-observation missions demand stringent pointing requirements that motivated a significant amount of research on the topic of microvibration isolation and line-of-sight stabilization systems. While disturbances can be reduced by mounting some of the noisy equipment on various isolation platforms, residual vibrations can still propagate through and be amplified by the flexible structure of the spacecraft. In order to alleviate these issues, the line of sight must also be actively controlled at the payload level. However, such systems typically have to rely solely on low-frequency sensors based on image processing algorithms. The goal of this article is to present a model-based control methodology that can increase the bandwidth of such systems by making use of additional rate sensors mounted on the main disturbance elements impacting the optical path. Following a comprehensive model identification and uncertainty quantification part, the robust control strategy is designed to account for plant uncertainty and provide formal worst case performance guarantees. Excellent agreement between theoretical prediction and experimental results are obtained on a test bench developed at the European Space Agency.

In this paper the feasibility of funnel control techniques for the Fokker--Planck equation corresponding to a multidimensional Ornstein--Uhlenbeck process on an unbounded spatial domain is explored...

This work presents a new robust control technique which combines a model predictive control (MPC) and linear quadratic gaussian (LQG) approach to support the frequency stability of modern power systems. Moreover, the constraints of the proposed robust controller (MPC-LQG) are fine-tuned based on a new technique titled Chimp optimization algorithm (ChOA). The effectiveness of the proposed robust controller is tested and verified through a multi-area power system (i.e., single-area and two-area power systems). Each area contains a thermal power plant as a conventional generation source considering physical constraints (i.e. generation rate constraint, and governor dead band) in addition to a wind power plant as a renewable resource. The superiority of the proposed robust controller is confirmed by contrasting its performance to that of other controllers which were used in load frequency control studies (e.g., conventional integral and MPC). Also, the ChOA’s ingenuity is verified over several other powerful optimization techniques; particle swarm optimization, gray wolf optimization, and ant lion optimizer). The simulation outcomes reveal the effectiveness as well as the robustness of the proposed MPC-LQG controller based on the ChOA under different operating conditions considering different load disturbances and several penetration levels of the wind power.

Active discharge circuit is of great significance for discharging the dc-bus capacitor voltage to safe voltage in the electric vehicles (EVs) based PMSM drive system when EVs encounter an emergency such as a crash event. However, when electric vehicle occurs a collision, the active discharge circuit may be damaged or failed, which poses a great electric threat to the passengers and succors. In order to resolve the problem, this article proposes a winding-based dc-bus capacitor discharge method. To quickly discharge the dc-bus capacitor energy, the machine windings are used as discharge resistance with active discharge circuit fault. For the purpose of reducing the bus voltage to safe voltage as soon as possible, the discharge method can be divided into two phases, rapid discharge stage and bus voltage regulation stage. Firstly, the dc-bus voltage will be dropped to safe voltage due to the large flux-weakening current applied to the d-axis. Secondly, in order to stabilize the bus voltage at safe voltage, an extended observer state (ESO) is designed to estimate and compensate the total power loss that is regarded as disturbance in bus voltage regulation stage. The parameters of the proposed ESO are designed and the tracking performance is analyzed. Finally, the proposed discharge technique is validated by both simulation and experiments, which are conducted on a three-phase SPMSM drive platform.