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Practical control problems are always subject to plant state and/or input constraints, which make designing an effective controller a challenging task. This paper introduces a novel virtual control approach to handling the presence of hard constraints in control systems by utilizing virtual mechanisms in the form of nonlinear springs and dampers. The augmented virtual mechanisms are to assist in better shaping the closed‐loop responses, especially when operating near the constrained boundary. A linear quadratic regulator based model predictive control method is utilized to develop stabilizing controllers that not only achieve desired system performance, but also meet the imposed hard constraints. The basic idea is to dramatically increase control penalty by way of tuning the spring and damper effect when the constrained state/input response is close to its hard constraint. The proposed method is applied to a balancing ball problem to demonstrate its applicability and effectiveness, and the simulation results validate the proposed concept. [ABSTRACT FROM AUTHOR]

Aiming at the problems of delay and couple in the sintering temperature control system of lithium batteries, a fuzzy neural network controller that can solve complex nonlinear temperature control is designed in this paper. The influence of heating voltage, air inlet speed and air inlet volume on the control of temperature of lithium battery sintering is analyzed, and a fuzzy control system by using MATLAB toolbox is established. And on this basis, a fuzzy neural network controller is designed, and then a PID control system and a fuzzy neural network control system are established through SIMULINK. The simulation shows that the response time of the fuzzy neural network control system compared with the PID control system is shortened by 24s, the system stability adjustment time is shortened by 160s, and the maximum overshoot is reduced by 6.1%. The research results show that the fuzzy neural network control system can not only realize the adjustment of lithium battery sintering temperature control faster, but also has strong adaptability, fault tolerance and anti-interference ability. [ABSTRACT FROM AUTHOR]

In this paper, a new robotic gripper is proposed and modeled which is able to bear a high amount of load and it can be used as the claws of climbing robots. As the climbing robots are usually heavy and their configuration should be kept in height against the gravity, firm grippers with no slippage possibility should be designed in order to guarantee the stability. The proposed new gripper is essentially required for the grip-based climbing robots which are heavy and are supposed to accomplish a specific operational task while they are grasping the pipe-shaped structures. The kinematic and quasi-static modeling of the proposed gripper is extracted and its related parameters are optimized to provide the maximum gripping force and the minimum slippage probability. Since these robust grippers are usually actuated by high torque motors, the reaction effect of the actuators force on the arm of the robot model is investigated here as a new study. Hence, the corresponding mechanical arm is also controlled, using a robust nonlinear controller to neutralize the destructive effect of extreme reaction forces or torques from the gripper motors to the robot arm during its mission. Thus, a robust controller is designed and implemented on the arm joint to cover the required positioning accuracy of the arm movement during the climbing motion. Afterward, the applicability of the proposed gripper and also the efficiency of the designed controller is verified by the aid of some analytic and comparative simulation scenarios performed in MATLAB-SIMULINK and MSC-ADAMS simulation. It is shown that the proposed gripper together with its related controlling algorithm for the arm can successfully provide a proper climbing mechanism for these kinds of robots which are supposed to climb through the structures and perform a special manipulating task. [ABSTRACT FROM AUTHOR]

At present, the methods based on using linearized dynamical equations are applied for syn- thesis of an attitude control system of a satellite with nonlinear dynamics. Linearized equa- tions describe the satellite dynamics approximately, which is the main their disadvantage. This article shows that basing on the angular momentum theorem, the nonlinear dynamical equations of the satellite attitude control system can be represented in the form of linear differential equations with variable coefficients, which makes it possible to use engineering methods of stability analysis and analysis of transient quality in the process of synthesis of the satellite attitude control system. [ABSTRACT FROM AUTHOR]

This paper investigates the trajectory tracking problem for a Multi-Input Multi-Output (MIMO) Twin Rotor Aerodynamic System (TRAS) using a hybrid architecture based on an H¥ controller and Iterative Learning Control (ILC). TRAS is a fast, nonlinear coupled system and therefore it is a challenging task to design a control system that ensures the tracking for fast changing trajectories. The controllers proposed in the literature for the TRAS through linear approaches tend to have a large control effort, while the ones designed using the nonlinear approaches track only for smooth input trajectories. Both issues are important from control point of view. In this paper, these issues are addressed by designing a feedback H¥ control that stabilizes the system and a feedforward ILC which reduces the control effort. The H¥ controller achieves the tracking for input trajectories with sharp edges, but the control effort required for tracking is large. With the proposed hybrid approach, tracking is achieved by the H¥ controller whereas the required control effort is reduced in each subsequent iteration by ILC. After a few iterations, accurate tracking at a minimized control effort is achieved. The simulations have been performed using MATLAB software and the controller designed through the proposed approach has been validated on nonlinear model of the system. The results of the proposed technique, compared with the flatness-based and back-stepping control strategies, show that the proposed controller ensures accurate tracking at the reduced control effort. [ABSTRACT FROM AUTHOR]

Linear motors (LMs) are widely used in numerous industry automation where precise and fast motions are required to convert electric energy into linear actuation without the need of any switching mechanism. This study aims to develop a control strategy of auto-tuning cross-coupled two-degree-of-freedom proportional-integral-derivative (ACC2PID) to achieve extremely high-precision contour control of a LMs-driven X-Y-Y stage. Three 2PID controllers are developed to control the mover positions in individual axes while two compensators are designed to eliminate the contour errors in biaxial motions. Furthermore, an improved artificial bee colony algorithm is employed as a powerful optimization technique so that all the control parameters can be concurrently evaluated and optimized online while ensuring the non-fragility of the proposed controller. In this way, the tracking error in each axis and contour errors of the biaxial motions can be concurrently minimized, and further, satisfactory positioning accuracy and synchronization performance can be achieved. Finally, the experimental comparison results confirm the validity of the proposed ACC2PID control system regarding the multi-axis contour tracking control of the highly uncertain and nonlinear LMs-driven X-Y-Y stage. [ABSTRACT FROM AUTHOR]

Summary: Classic control methods commonly used for a unified power quality conditioner (UPQC) include the following: proportional integral (PI) control, proportional resonance (PR) control, and repetitive control. Generally, the main weaknesses of these control methods are poor compensation accuracy and low response speed. In this article, in order to enhance the overall performance of the system, we introduce an innovative nonlinear control strategy based on the Lyapunov function for the three‐phase three‐wire neutral‐point clamp (NPC) type three‐level UPQC. We first develop the mathematical UPQC model, then obtain from the model the control law which we use to construct the switching function by creating the Lyapunov function, thus avoiding the introduction of closed‐loop feedback. The suggested strategy also achieves system stability and dynamic performance by selecting appropriate parameters, after which a carrier‐based pulse width modulation control method based on the injected zero‐sequence component is applied to maintain the stability and balance of the DC‐side capacitor voltage. In addition, both numerical simulation and comparison of experimental results using traditional PI control, passivity‐based control methods, and sliding mode control shows that the proposed nonlinear control strategy for three‐phase three‐wire NPC type three‐level UPQC has an excellent response speed and compensation efficiency. [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 article, an exact linearization algorithm and nonlinear control scheme of the inductive power transfer (IPT) system for electric vehicles (EVs) are proposed, considering a variation in system operating point. For ease of modeling, the secondary side of IPT system is equivalent to a reflected reactor and resistor on primary side at different operating frequencies. By utilizing the exact linearization method, the nonlinear model is accurately transformed into a linear one at whole operating points. Besides, to acquire constant current $\backslash$ voltage (CV/CC) charging and zero voltage switching (ZVS) operating for EVs, the controllers are designed and optimized in the linear space, and then inverse mapped to the nonlinear space. This avoids designing different controllers for each operating point. Compared with a traditional PI controller, the nonlinear control scheme suggested in this article enables the system to obtain a fixed dynamic response even if the operating point of the IPT system changes. Finally, practical results obtained from a hardware prototype are included. They confirm the performances of the system and indicate that the proposed nonlinear control scheme can automatically maintain CC $\backslash$ CV output and ZVS operation with a constant response time of 10 ms. [ABSTRACT FROM AUTHOR]

In this work, the effectiveness of the adaptive neural based fuzzy inference system (ANFIS) in identifying underactuated systems is illustrated. Two case studies of underactuated systems are used to validate the system identification i. e., linear inverted pendulum (LIP) and rotary inverted pendulum (RIP). Both the systems are treated as benchmark systems in modeling and control theory for their inherit nonlinear, unstable, and underactuated behavior. The systems are modeled with ANFIS using the input-output data acquired from the dynamic response of the nonlinear analytical model of the systems. The dynamic response of the ANFIS model is simulated and compared to the nonlinear mathematical model of the inverted pendulum systems. In order to check the effectiveness of the ANFIS model, mean square error is used as the performance index. From the obtained simulation results, it has been perceived that the ANFIS model performed satisfactorily within the trained operating range while a minor deviation is seen outside the trained operating region for both the case studies. Furthermore, the experimental validation of the of the proposed ANFIS model is done by comparing it with the experimental model of the rotary inverted pendulum. The obtained results show that the response of ANFIS model is in close agreement to the experimental model of the rotary inverted pendulum. [ABSTRACT FROM AUTHOR]

In this paper, a quantized controller is designed for a class of uncertain nonlinear systems subjected to unknown disturbances and unknown dead-zone nonlinearity. A general class of strict feedback nonlinear systems is taken as the plant to design the controller. Here, each differential equation of the system is considered to have unknown parameters and time-varying disturbances. The maximum upper bound of the disturbances is estimated instead of estimating each disturbance. This novel idea reduces the computational cost in handling the disturbances in uncertain systems. The tuning functions are constructed to estimate the unknown system parameter and maximum upper bound of the disturbances. It is considered that the actuator dead-zone nonlinearity is bounded by an unknown parameter and incorporated to design the final quantized controller. A backstepping technique is applied to design the tuning functions and controller that stabilizes the uncertain system. The stability of the proposed controller is proved using the Lyapunov stability based theory. The obtained MATLAB simulation test results verify the designed proposed controller. • A quantized controller is designed for nonlinear systems with dead-zone nonlinearity. • The disturbances are tackled by estimating a maximum upper bound of them. • The controller handles the uncertainty, disturbances, and dead-zone nonlinearity. [ABSTRACT FROM AUTHOR]

In this paper, a novel grey decision-differential evolution (GD-DE) optimized internal model controller is proposed for the control of nonlinear aeroelastic blade system (ABS) under time-varying uncertainties and control saturations. Two-port internal model control structure is presented for saturation compensation. The filter parameter of the controller is optimally tuned by proposed GD-DE algorithm, which is designed based on the grey decision incidence theory and differential evolution algorithm. The superiority of GD-DE optimized tuning technique is verified, compared to conventional IMC tuning method and other evolutionary algorithm based techniques. The robustness is analysed by comprehensive simulations from time-invariant uncertainties to large periodic or random time-varying uncertainties. The realistic condition with input/output disturbances is also involved. Simulation results show that the proposed controller outperforms existing adaptive IMC controller and other advanced controllers with greatly improved dynamic performance, stronger robustness and better saturation compensation on various conditions. • Nonlinear aeroelastic blade system with large periodic/random time-varying uncertainties. • Design of grey decision modified differential evolution (GD-DE) algorithm. • GD-DE optimized two-port IMC vibration controller is proposed. • A comparative performance analysis with conventional adaptive IMC controller. [ABSTRACT FROM AUTHOR]

The negative aspects of overusing fossil fuels for producing electricity attract the attention of engineers society to use renewable energies. Power electronic converters play an important role in the transmission and usage of renewable energy in the industry. Boost converters are a major part of devices in which convert renewable energies into usable energy for various industries or appliances. In this article, to control a boost converter with parametric uncertainty, a new robust‐optimal controller is designed. The proposed control method is designed based on merging two conventional control theory: the robust control theory and linear quadratic regulator technique. This method consists of two nested loops. The inner loop composed of a state feedback controller which works as active damping to improve the transient state. The outer loop consists of a PI controller to track the desired voltage and reject disturbance. The coefficients of both controllers are computed by a robust‐optimal control technique. To evaluate the proposed control method, a well‐tuned single‐loop PI controller and a quantitative feedback theory based PID controller are compared with the proposed method. As shown by simulations, the proposed method has a more reliable performance in dealing with parameters uncertainties such as load changes and input voltage drops. [ABSTRACT FROM AUTHOR]

Summary: This article is concerned with the design of the observer and controller to perform fault estimation (FE) and fault tolerant control for the discrete‐time nonlinear stochastic systems with multiple time‐varying state delays and intermittent sensor and actuator faults. In comparison with the present research, the method addressed in this article is more flexible and feasible. A novel adaptive descriptor observer is developed to obtain the error dynamics and then realize n‐step FE. Then, an active observer‐based controller is constructed to stabilize the closed‐loop system. Moreover, an augmented closed‐loop system is acquired and a series of delay‐dependent sufficient conditions are collected by the delay‐dependent Lyapunov function utilizing linear matrix inequalities. The method is less conservative compared with the ones of the existence. At last, a simulation example is presented to demonstrate the advantages and effectiveness of the approach proposed in the article. [ABSTRACT FROM AUTHOR]

This paper proposes a novel observer-based nonlinear triple-step controller for the air supply system of polymer electrolyte membrane (PEM) fuel cell. The control objective is adjusting the oxygen excess ratio to its reference value under fast current transitions, so as to avoid the oxygen starvation and obtain the maximum net power. Considering that the cathode pressure cannot be measured directly, we design a disturbance observer to estimate the cathode pressure based on the developed third-order nonlinear model of air supply system. Next, a triple-step nonlinear method is applied to derive an oxygen excess ratio tracking controller, wherein the stability of closed-loop system is guaranteed by Lyapunov-based technique. Subsequently, several key issues of controller in practical implementation are explained, and then the robustness analysis against the considered lumped disturbance is carried out. Finally, the performance of the proposed control scheme is validated through a series of comparative simulations, and the simulation results demonstrate the effectiveness and robustness of the proposed approach under different load variations and parameter uncertainties. • A novel control scheme is proposed to regulate the air flow. • Stability and robustness analysis of the closed-loop system is performed. • Several key issues of controller in practical implementation are explained. • The proposed method has good performance in different simulation tests. [ABSTRACT FROM AUTHOR]

With the electrification and intellectualization of vehicle systems, electromagnetic active suspension has been paid more and more attention. Linear motor is one of the effective actuators of the electromagnetic active suspension system. The nonlinear factors of linear motor, such as nonlinear friction force and ripple force, as well as power limit and magnetic saturation, will reduce the performance of electromagnetic active suspension. However, the current research rarely considers the effect of these nonlinear factors on active suspension control. In this article, the effect of nonlinearities of linear motors on electromagnetic active suspension performance and the ways to improve their performance are studied. An adaptive filtering compensation method is proposed to reduce the influence of nonlinear factors on the electromagnetic active suspension control. According to the simulated calculations, performance degradation of the active suspension is observed in both the primary control objective and high-frequency range due to inherent disturbance from the nonlinear factors. Also, the electromagnetic nonlinearities will reduce the active suspension effective force output. By proposing an adaptive compensator based on the filtered-x recursive least squares algorithm, the first-order resonance of the suspension system could be controlled and the electromagnetic active suspension effective force could be magnified. Also, convergence of the adaptive compensator is found to be rapid and reasonable. [ABSTRACT FROM AUTHOR]

This paper develops a novel approximate optimal control method for a class of constrained continuous-time nonlinear systems in the presence of disturbances via adaptive dynamic programming (ADP) technique. First, an auxiliary dynamic compensator is introduced to deal with the input constraints. Through augmenting the original system with the designed auxiliary compensator, the design of constrained optimal controller is circumvented by stabilizing the equivalent augmented system. Then, the cost function is appropriately redefined by introducing an additional function connected with disturbances for the augmented nominal system in order to compensate the effect of unmatched disturbances. Next, the solution of associated Hamilton-Jacobi-Bellman (HJB) equation is solved online with weight adaptation law using neural networks (NNs). Furthermore, an additional robustifying term is utilized to compensate the effect of the approximation error of NNs, and thus the asymptotic stability of the closed-loop system is guaranteed. Finally, all signals of the closed-loop system are proved to be asymptotic convergence by using Lyapunov method. Simulation examples demonstrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper focuses on racecar longitudinal control with highly-varying driving conditions. The main factors affecting the dynamic behavior of a vehicle, including aerodynamic forces, wheel rolling resistance, traction force resulting from changing tire-road interaction as well as the occurrence of sudden wind gusts or the presence of persistent winds, are considered and assumed to have unknown models. By exploiting the theory on delayed input-state observers and using measurement data about the vehicle and wheel speeds, a dynamic filter that allows the online reconstruction of the above-mentioned unknown time-varying quantities is derived. Moreover, by exploiting the notion of effective tire radius, a reduced-degree-of-freedom model for the longitudinal vehicle dynamics is obtained, which is independent of the traction force and that enables, when used with the observer filter described above, an accurate speed control compensating for the resistance forces. One appealing feature of the proposed estimation and control method is that it requires no model information about such forces, for which, at the state-of-the-art, only heuristic approximations to be a-priori identified are available. Its effectiveness is shown via the simulation of scenarios where the car is required to execute aggressive maneuvers and the asphalt road surface abruptly changes from dry to wet, snowy, and icy. The evaluation also reveals that the proposed estimation technique outperforms standard solutions even in the presence of measurement noise. [ABSTRACT FROM AUTHOR]

This article presents a novel event-driven guaranteed cost control method for nonlinear systems subject to actuator faults. For the purpose of handling the problem of actuator faults and obtaining the event-driven approximate optimal guaranteed cost control approach for general nonlinear dynamics, the reinforcement learning (RL) algorithm is utilized to develop a sliding-mode control (SMC) strategy. To begin with, the unknown faults can be estimated by designing a fault observer. Meanwhile, an SMC technique is presented aiming at countering the effect of abrupt faults. In addition, the optimal performance of the equivalent sliding mode dynamics is considered, then an event-driven guaranteed cost control mechanism is implemented by using RL principle. In the control process, a general cost function, which has a simpler structure, is given to reduce the computation complexity. At the same time, a modified cost function is approximated to obtain optimal guaranteed cost control by using a single critic neural network (NN). In addition, a modified weight update law for critic NN is presented to relax the persistence of excitation (PE) condition. Moreover, a newly triggering condition, which is easy to be implemented, is designed, and the critic NN update law makes sure that the system states are stable. Furthermore, in light of the Lyapunov analysis, it is demonstrated that the developed event-driven control method guarantees the uniformly ultimately bounded (UUB) property of all the signals. Finally, three simulation results are given to validate the designed control method. [ABSTRACT FROM AUTHOR]

In this paper, an integral reinforcement learning-based adaptive neural network (NN) tracking control is developed for the continuous-time (CT) nonlinear system with unknown control directions. The long-term performance index in the CT domain is prescribed. Critic and action NNs are designed to approximate the unavailable long-term performance index and the unknown dynamics, respectively. The reinforcement signal is explicitly embedded in the updated law of the action NN and then the estimated long-term performance index can be minimized. Rigorous theoretical analysis is provided to show that the closed-loop system is stabilized and all closed-loop signals are semiglobally uniformly ultimately bounded. Finally, to demonstrate the control performance, simulation results are provided to verify the tacking control performance of an autonomous underwater vehicle model. [ABSTRACT FROM AUTHOR]

This paper investigates the control problem of networked nonlinear multiagent systems with communication constraints and unknown dynamics, based on system input–output data. A cost function for the design of networked nonlinear multiagent control systems is presented, which considers not only the coordination performance between agents but also the performance of individual agents. Utilizing a data model to represent discrete-time nonlinear multiagent systems, a networked data-driven predictive control scheme is proposed to optimize control performance, compensate for communication constrains, and achieve both consensus and stability of networked nonlinear multiagent systems. An optimal control protocol is derived, which minimizes the cost function and makes compensation for communication constraints. The criteria of achieving both consensus and stability of networked nonlinear multiagent systems are provided. An example illustrates the performance of the proposed networked data-driven predictive control scheme. [ABSTRACT FROM AUTHOR]

This brief focuses on the control design for the aerial cargo transportation system that consists of a quadrotor unmanned aerial vehicle (UAV) and a cable-suspended payload. The underactuated properties associated with the system dynamics bring great challenges for the control development. Partial feedback linearization methodology is employed to formulate a nonlinear controller that yields an exponential regulation result of the quadrotor UAV position, while the swing motion of the payload is suppressed exponentially fast. A Lyapunov-based stability analysis is included to prove the convergence of the position error and the local exponential stability of the closed-loop system. Real-time experiments are performed on a self-built UAV testbed to validate the performance of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This article treats the design and implementation of a multi-input multi-output fractional-order controller for a nonlinear system composed of a tendon-driven continuum mechanism. As the continuum can be deformed along all Cartesian directions, it is suitable for the application as a flexible neck of a humanoid robot. In this work, a model-based control approach is proposed to control the position of the head, that is, the rigid body attached to the top of the continuum mechanism. Herein, the system is modeled as a rigid body on top of a nonlinear Cartesian spring, with an experimentally obtained deflection characteristic which provides a simple and real-time capable model. By nonlinear feedback, the output dynamics are linearized and decoupled, which enables the design of single-input single-output fractional-order controllers for the regulation of each output independently. The design of a fractional-order P D α controller is discussed to incorporate robustness and a fast transient response. The proposed control approach is tested in several experiments on the real system. [ABSTRACT FROM AUTHOR]

In this article, a new nonlinear algorithm based on the sliding mode control is developed for the ball and plate control system to improve dynamic response and steady-state tracking accuracy of the control system. First, a new sliding mode reaching law is proposed, variable exponential power reaching law (VEPRL), which is expressed in two different forms including a nonlinear combination function term and a variable exponential power term, so that it can be adjusted adaptively according to the state of the system by the variable exponential power reaching term during the reaching process. The computation results show that it can not only effectively weaken the chattering phenomenon but also increase the rate of the system state reaching to the sliding mode surface. Moreover, it has the characteristic of global finite-time convergence. Besides, a complementary terminal sliding mode control (CTSMC) method is designed by combining the integral terminal sliding surface with the complementary sliding surface to improve the convergence rate. Based on the proposed VEPRL and CTSMC, a new sliding mode control method for the ball and plate system is presented. Finally, simulation results show the superiority and effectiveness of the proposed control method. [ABSTRACT FROM AUTHOR]

This paper proposes a nonlinear robust track keeping control algorithm for energy efficiency from the perspective of ship motion control, based on the great significance of the twenty-first Century Maritime Silk Road. Replacing the course error e with the sin ⁡ (ω e) driven by the sine function in course keeping loop to serve as the input of the controller, the simulation results tested on the ship autopilot simulation platform show that the controller output (maximum rudder angle) decreases, and the control effect of track keeping is better than the previous one in aspects of energy efficiency and rudder shake inhibition. Otherwise, the proposed nonlinear track keeping control algorithm still works in relatively severe sea states. Substituting the nonlinear feedback for the linear feedback has the generality of control effect improving. [ABSTRACT FROM AUTHOR]

This study presents both static and dynamic event-triggered mechanisms for the design of event-triggered stabilizing state feedback controllers for a class of uncertain nonlinear systems. Sufficient conditions based on linear matrix inequalities are first provided to guarantee the asymptotic stability of the closed-loop system. The controllers are then systematically designed. We also prove that the inter-event intervals of the considered event-triggered mechanisms are positive, therefore ensuring that the Zeno behavior does not happen. Two examples with simulations are provided to illustrate the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, the problem of time-varying output tracking is studied in discrete-time descriptor systems. The descriptor system is subject to practical constraints such as input saturation and exogenous disturbances and consists of algebraic equations besides the difference equations in system modeling. The control problem is solved by proposing an observer-based composite nonlinear feedback controller to attain a suitable response and desired performance. The proposed control law is designed based on estimated states from a full-order descriptor observer. Considering the nonlinearity behavior and complicated analysis procedure, a theorem is dedicated to studying the closed-loop system that looks into the operation of the proposed observer-based control law upon different cases of the saturation function. It is demonstrated that the proposed control law is capable of working even if the saturation occurs. Furthermore, ultimate boundedness analysis is also done to verify the performance of the proposed control law in the presence of exogenous disturbance. The accuracy of theoretical achievements is endorsed by computer simulations through a numerical example and a practical example (a hydraulic tank system). • Solving general time-varying output tracking problem in discrete-time descriptor systems with actuator saturation constraint. • Improving the transient behavior of the closed-loop system. • Increasing applicability of the proposed method by proposing an observer-based control law. • Guaranteeing performance in the presence of exogenous disturbances by ultimate boundedness analysis. • Verifying the theoretical achievements via computer simulations of numerical and practical examples. [ABSTRACT FROM AUTHOR]

For the nonlinear systems with input saturation constraint, a novel MTN-based output-feedback control strategy is developed via backstepping in this paper. Firstly, an MTN-based nonlinear state observer is designed to estimate the unmeasured states. Secondly, multi-dimensional Taylor networks (MTNs) are used to deal with the unknown nonlinear functions, based on this, the procedure of the adaptive MTN output-feedback controller design is developed by combining backstepping approach and dynamic surface control technique, and then the stability of the closed-loop system is proved based on the principle of Lyapunov stability theory. Finally, the theoretical results of this paper are demonstrated by two examples. [ABSTRACT FROM AUTHOR]

We consider an optimal control problem on a finite time-interval for a three-sector economic control object. We reduce the economic system to an optimal control problem for a nonlinear system with coefficients independent of the control object state and find a nonlinear synthesizing control based on the feedback principle and certain constraints on control. The results obtained for the nonlinear system are used to construct the control parameters in the mathematical model of a three-sector economic control object. We find an optimal distribution between the labor and investment resources satisfying the balance relations. Bibliography: 3 titles. Illustrations: 2 figures. [ABSTRACT FROM AUTHOR]

Summary: This article is concerned with the adaptive output‐feedback control of switched nonstrict feedback nonlinear systems. By introducing a novel error surface, an adaptive control strategy is proposed for the general case where the nonlinear functions and the control gain functions are unknown, and the states are unmeasurable. The considered switched nonlinear system contains unknown actuator failures, which are modeled as both loss of effectiveness and lock‐in‐place. In order to improve the transient performance in the presence of unknown actuator failures, the prescribed performance approach is used. The "explosion of complexity" problem is avoided through using low‐pass filters. The stability of the closed‐loop system under arbitrary switching is shown using Lyapunov stability theory, based on which, the tracking error is shown to converge to a small residual set with the prescribed performance bounds. The advantages of the proposed technique are verified through simulations of two numerical and practical examples. [ABSTRACT FROM AUTHOR]

This paper investigates the composite control scheme of robust nonlinear disturbance observer (RNDO) with adaptive non-singular fast terminal sliding mode control (NSFTSMC) technique for the attitude tracking of rigid spacecraft. The spacecraft is subjected to the parametric uncertainties, external disturbances, and actuator faults. The proposed RNDO estimates the overall lumped disturbance (combination of faults and disturbances) in finite-time. Moreover, it improves the disturbance rejection property of the composite control by feedforward compensation. An adaptive law is also employed in the composite control to enhance the robustness against the cases where RNDO takes some time for estimation, e.g., when there is a sudden change in the lumped disturbance. Further, the proposed controller is also enriched with anti-unwinding property to tackle the problem of unwinding in the quaternion based attitude representation. The stability analysis of the closed-loop system under the composite control scheme guarantees the finite-time convergence of relative state variables using the Lyapunov stability theory. The simulation analysis with the comparative study illustrates the effectiveness of the proposed strategy in terms of better disturbance rejection ability, higher accuracy, faster convergence, and better steady-state performance. [ABSTRACT FROM AUTHOR]

Fractional order controllers are widely used in the robust control field. As a generalization of the ubiquitous PID controllers, fractional order controllers are able to reach design specifications their integer counterparts cannot, and as a result they outperform them at particular situations. Their main drawback is that generalization of the design tools is not always evident, and therefore tuning this kind of controller is always a new and different challenge. Existing methods often use numerical computation to find the controller parameters that fit the specifications. This paper describes a graphical solution for fractional order controllers, which avoids the solution by nonlinear equations and helps designer to solve the control problem in a very intuitive way. This approach is tested in the servomotors of a real bio-inspired soft neck and results are compared with those obtained from other control strategies. The experiments show that the controller tuned by this method works as expected from a robust controller and that this approach is very competitive compared to other state of the art methods, while offering a more simplified and direct tuning process. • Robust control of a soft robotics platform. • New Graphical method for fractional order controller tuning. • Test and validation against state of the art methods. • Experiments on a real soft robotics platform. [ABSTRACT FROM AUTHOR]

This paper studies fuzzy adaptive dynamic surface control strategy for nonlinear system with sampled data and time-varying input delay. By utilizing the approximated property of fuzzy logic systems (FLSs), a fuzzy estimator (FE) model is designed to identify the states of the original system, which is mainly used to provide information of estimation states to replace the sampled data of the nonlinear controlled system. In the proposed strategy, with the help of sampled-data activity, an integral term is designed to compensate the problem of time-varying input delay. Moreover, by invoking the dynamic surface control (DSC) technique, the problem of 'explosion of complexity' has been overcame. And the developed control strategy demonstrates that all signals of the controlled system are semi-globally uniformly ultimately bounded (SGUUB). Ultimately, two numerical simulation examples are given to prove the feasibility of the developed control method and theory. [ABSTRACT FROM AUTHOR]

This article concentrates on the output feedback controller design problem for discrete-time nonlinear switched systems with actuator faults. The Takagi–Sugeno fuzzy model is adopted to approximate the nonlinearity of the plant with a set of local linear models. The persistent dwell-time (DT) switching law, which is more general than DT or average DT switching, is introduced to govern the switching among subsystems. In order to alleviate the effects of actuator failures on system stability and performance, a synthesized fault-tolerant output feedback controller ensuring various performance requirements is designed. Intensive attention is focused on establishing sufficient conditions, which can guarantee the exponential mean-square stability as well as the prescribed extended dissipativity property of the closed-loop system. By virtue of the Lyapunov stability theory and appropriate matrix transformation methods, the desired controller gains can be obtained by solving a convex optimization problem. The developed method is finally applied to address the control issue of a tunnel diode circuit system model to illustrate its efficiency and applicability. [ABSTRACT FROM AUTHOR]

Bei einer Vielzahl von Anwendungen aus dem Bereich der Ingenieurwissenschaften ist die Berechnung garantierter Einschlüsse der Mengen aller erreichbaren Zustandsgrößen von großem Interesse. Mögliche Anwendungsszenarien umfassen den Entwurf sowie die rechnergestützte Verifikation von (nicht-)linearen Zustandsregelungen sowie die Implementierung robuster modell-prädiktiver Regelungsansätze. Viele der hierbei betrachteten Anwendungen lassen sich nach einer geeigneten regelungsorientierten Modellbildung sowie gegebenenfalls nach einer Zustandstransformation in Form von gewöhnlichen Differentialgleichungssystemen mit einem dominierenden linearen Anteil beschreiben, wobei nichtlineare Effekte nicht vollständig vernachlässigt werden sollten. Für die Berechnung gesicherter Zustandseinschlüsse lassen sich beispielsweise allgemeine Ansätze basierend auf Taylor-Reihenentwicklungen der zu bestimmenden Lösungen heranziehen. Diese allgemeinen Ansätze nutzen jedoch in der Regel kein Vorwissen über systemspezifische Eigenschaften wie quasi-lineare Dynamik oder Stabilität. Um diese Eigenschaften in der Praxis effizient nutzbar zu machen, wird im Rahmen dieser Arbeit ein Exponentialansatz zur Berechnung garantierter Lösungseinschlüsse für Systeme gewöhnlicher Differentialgleichungen hergeleitet, der ausgehend von einer reellwertigen Implementierung für Systeme mit aperiodischer Dynamik auf die Berechnung komplexwertiger Zustandseinschlüsse für Prozesse mit oszillatorischem Verhalten verallgemeinert wird. Zum Abschluss werden Möglichkeiten vorgestellt, die entwickelten Verfahren auf Systeme von fraktionalen Differentialgleichungen auszudehnen. The computation of guaranteed state enclosures has a large variety of applications in engineering. Possible application scenarios involve the simulation-based verification of linear and nonlinear feedback controllers as well as the implementation of model-predictive control procedures. In many of these applications, system models can be derived in a control-oriented form by first-principle techniques so that they are characterized by a dominant linear part (commonly after a suitable coordinate transformation) with a not fully negligible nonlinear part. To compute guaranteed state enclosures for such systems, general purpose approaches relying on a Taylor series expansion of the solution can be employed. However, such procedures do not exploit specific knowledge about the structure of the system model at hand, such as quasi-linearity and stability. To incorporate these structural properties for real-life scenarios in an effective way, an exponential state enclosure technique is presented in this paper. Starting with a real-valued implementation for systems with aperiodic dynamics, a generalization is presented which makes use of complex-valued state enclosures for systems with oscillatory behavior. Possibilities to extend the presented method towards fractional-order differential equations conclude this paper. [ABSTRACT FROM AUTHOR]

This paper presents a hybrid robust control design method for a third-order lower-triangular model of nonlinear dynamic systems in the presence of disturbance. In this paper, a novel control design is presented systematically to synthesize a robust nonlinear feedback controller, called backstepping sliding mode control (BSMC), for the proposed system by a combined approach of backstepping design and sliding mode control. In this approach, a family of the "sliding surface" is introduced in state transformations. Then, a smooth switching function of the sliding surface is introduced and enforced to include in virtual feedbacks and a real control law from the control selection phrases of the backstepping design loop. The achieved control method proves a well-tracking command with asymptotic stability, provides a robustness in the presence of uncertainties, and eliminates completely a chattering phenomenon. The application of flight-path angle control corresponding to the longitudinal dynamics of a high-performance F-16 aircraft simulation model is implemented. Under some assumptions, full nonlinear longitudinal dynamics is reformed into a lower-triangular system for a direct application to formulate a control law. A closed-loop system is achieved for in-flight simulation with different flight profiles for a comparison of the existing methods. Also, an external disturbance on different loading/unloading conditions in flight is applied to verify and validate robustness of the proposed control method. [ABSTRACT FROM AUTHOR]

Summary: This article investigates the stability analysis and control design of a class of nonlinear positive Markovian jump systems with randomly occurring actuator faults and saturation. It is assumed that the actuator faults of each subsystem are varying and governed by a Markovian process. The nonlinear term is located in a sector. First, sufficient conditions for stochastic stability of the underlying systems are established using a stochastic copositive Lyapunov function. Then, a family of reliable L1‐gain controller is proposed for nonlinear positive Markovian jump systems with actuator faults and saturation in terms of a matrix decomposition technique. Under the designed controllers, the closed‐loop systems are positive and stochastically stable with an L1‐gain performance. An optimization method is presented to estimate the maximum domain of attraction. Furthermore, the obtained results are developed for general Markovian jump systems. Finally, numerical examples are given to illustrate the effectiveness of the proposed techniques. [ABSTRACT FROM AUTHOR]

Summary: This article investigates the problem of using sampled‐data state/output feedback to semiglobally stabilize a class of uncertain nonlinear systems whose linearization around the origin is neither controllable nor observable. For any arbitrarily large bound of initial states, by employing homogeneous domination approach and a homogeneous version of Gronwall‐Bellman inequality, a sampled‐data state feedback controller with appropriate sampling period and scaling gain is constructed to semiglobally stabilize the system. In the case when not all states are available, a reduced‐order sampled‐data observer is constructed to provide estimates for the control law, which can guarantee semiglobal stability of the closed‐loop system with carefully selected sampling period and scaling gain. [ABSTRACT FROM AUTHOR]

Based on the local T-S model, the switching control method for the nonlinear response of the seismic surface is studied, and the stiffness matrix of the composite interlayer element of viscoelastic damper and herringbone support is derived. The high-order single step ß method is applied to the nonlinear seismic response analysis and the instantaneous optimal active switching control. The local T-S model and controller are designed, and the approach and control of global nonlinear responses are realized through the multi-model switching control. The results show that the proposed method can accurately reflect the reduction of seismic ground load and the switching control of the main structure when the viscoelastic damper is installed. The switching control effect of the maximum spatial displacement becomes more and more obvious with the change of time history, and the control effect of all layers applying the switching control force is the most significant. Whether the controller is disturbed or not, it is always good and stable performance. [ABSTRACT FROM AUTHOR]

The multiple–input multiple–output (MIMO) output feedback (OF) control problem of an exothermic multi-jacket tubular open-loop unstable reactor is addressed. Over its axial length, the reactor has several equally sized cooling jackets. The controller must adjust the jacket temperatures on the basis of per jacket temperature measurements so that the closed-loop system is robustly stable. The problem is solved within a constructive framework, by combining notions and tools from chemical reactor engineering and partial differential equations (PDEs) control systems theory. The result is a MIMO nonlinear OF dynamic control design with (i) a decentralized MIMO passive state feedback (SF) controller implemented with a pointwise observer (PWO), (ii) closed-loop stability conditions in terms of sensor set and control gains, and (iii) efficient late lumping-based on-line implementation. The design is put in perspective with industrial PI and inventory control, and applied to a representative example through numerical simulation with favorable comparison against adaptive controllers. • The stabilization of an unstable multi–jacket tubular reactor is addressed by the construction of a PDE model-based MIMO decentralized output feedback controller. • The jacket partition and per jacket sensor locations are design degrees of freedom. • The MIMO output controller is a pointwise observer-based passive state feedback controller derived from notions and tools from chemical reactor engineering and passivity-based control. • Closed-loop stability criteria in terms of sensor locations and control gains are derived together with tuning guidelines and efficient late lumping on-line implementation that precludes unduly on-line computational load. • The control is tested with an example through simulation and favorably compared with adaptive controllers. [ABSTRACT FROM AUTHOR]

In this paper, an inverse control scheme based on the novel dynamic network (multi-dimensional Taylor network (MTN)) is proposed for the real-time tracking control of nonlinear time-varying systems with noise disturbances. Utilized in this scheme are the three MTNs: the adaptive model identifier for system modeling, the adaptive inverse controller for inverse modeling, and the adaptive nonlinear filter for eliminating the noise disturbances, whose weights are modified by the variable forgetting factor recursive least squares (VFF-RLS), back propagation through model (BPTM), normalized least mean square (NLMS) algorithms, respectively. To avoid "compromise", this scheme is designed into a structure wherein controlling the object dynamic response and eliminating the noise disturbances are implemented in two relatively independent processes. Furthermore, the weight-elimination algorithm is introduced for choice of effective regression items to avoid the dimension explosion, thus overcoming the shortcoming that the number of middle nodes needs to be determined before using the traditional neural network. After a certain number of training, the more streamlined MTNs are observed to contribute to satisfying the real-time requirements of software implementation and engineering application. To ensure that MTN inverse control is strict in theory, the general conditions for the existence of single-input/single-output (SISO) nonlinear inverse systems are identified. Simulation of the MTN inverse control is conducted to confirm the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

A filtered adaptive constrained sampled‐data controller for uncertain multivariable nonlinear systems in the presence of various constraints is synthesized in this paper. A piecewise constant adaptive law drives that estimation error dynamics to zero at each sampling time instant yields adaptive parameters. The filtered control scheme consists of two components. Based on an estimation/cancellation strategy, a disturbance rejection control law is designed to compensate the nonlinear uncertainties within the bandwidth of low‐pass filters, whereas a constraint violation avoidance control law is designed to solve an online constrained optimization problem. Although a reduced sampling time helps to minimize the estimation error caused by the neglect of unknowns, the resulting aggressive signals put more restrictions on the control law. Greater sacrifice of tracking performance is required to satisfy the constraints. The constraints violation avoidance control law is in favor of a larger sampling time. Sufficient conditions are given to guarantee the stability of the closed‐loop system with the sampled‐data controller, where the input/output signals are held constant over the sampling period. Numerical examples are provided to validate the theoretical results, comparisons between the constrained sampled‐data controller and unconstrained adaptive controller with the implementation of different sampling times are carried out. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of event-triggered active disturbance rejection control of nonlinear network control system in simultaneous presence of unknown dynamics, physical attacks and denial-of-service attacks. Considering the network congestion, an event-triggered communication mechanism is adopted, where the measurements are transmitted only when an 'event' occurs. An indicator obeying the Markov jump rule is introduced to characterize the randomly occurring denial-of-service attacks. In virtue of the extended state observer (ESO), the states and the total disturbance which involves both unknown dynamics and physical attacks are estimated. Then, the composite controller is designed which could stabilize the overall controlled system and eliminate the so-called total disturbance. Sufficient conditions are established to guarantee the stability of the observer system and overall controlled system. The cone-complementarity linearization algorithm is adopted to obtain the parameters of the extended state observer and the controller. Finally, both numerical and application design examples demonstrate the feasibility and efficacy of the proposed method. Simulation results show that the steady-state error within 0.02 can be achieved within 3 s. • A comprehensive control model which is subjected to DoS attack, physical attack and unmodeled nonlinearities is put forward. • An event-triggered ADRC protocol is design for the nonlinear system with physical attack and Markovian jump DoS attack. • The sufficient conditions are provided such that the corresponding augmented system is exponentially mean square bounded stable. [ABSTRACT FROM AUTHOR]

A boiler‐turbine unit is a primary module for coal‐fired power plants, and an effective automatic control system is needed for the boiler‐turbine unit to track the load changes with the drum water level kept within an acceptable range. The aim of this paper is to develop a nonlinear tracking controller for the Bell‐Åström boiler‐turbine unit. A Takagi‐Sugeno fuzzy control system is introduced for the nonlinear modeling of the Bell‐Åström boiler‐turbine unit. Based on the Takagi‐Sugeno fuzzy models, a nonlinear tracking controller is developed, and the proposed control law is comprised of a state‐feedforward term and a state‐feedback term. The stability of the closed‐loop control system is analyzed on the basis of Lyapunov stability theory via the linear matrix inequality approach and Schur complement. Moreover, model uncertainties are also considered, and it is proved that with the proposed control law the tracking error converges to zero. To assess the performance of the proposed nonlinear state‐feedback state‐feedforward control strategy, a nonlinear model predictive control strategy and a linear strategy are presented as comparisons. The effectiveness and the advantages of the proposed nonlinear state‐feedback state‐feedforward control strategy are demonstrated by simulations. [ABSTRACT FROM AUTHOR]

In this work, we consider the problem of controlling a single‐phase on‐board battery electric vehicle (BEV) charger with vehicle‐to‐grid (V2G) technology. The BEV charger consists of a bidirectional ac‐dc power converter connected to the single‐phase power grid, followed by a bidirectional dc‐dc power converter interfacing an EV battery pack. The main control objectives are fourfold: (i) Unitary Power Factor (UPF) in grid‐side; (ii) tight dc‐bus voltage regulation; (iii) safety battery charge and battery discharge during the grid‐to‐vehicle (G2V) mode and V2G mode, respectively; and (iv) asymptotic stability of the closed loop system. After an accurate system modelling, a nonlinear controller is designed using a backstepping design technique. The point is that the battery inner voltage is not accessible to measurement. Therefore, a nonlinear observer is invoked in order to estimate all non‐measured variables making the solution cheaper and noiseless. It is shown using a formal analysis and numerical simulations, that the proposed output feedback controller (combining a nonlinear controller and a nonlinear observer) meets all control objectives. [ABSTRACT FROM AUTHOR]

Recently, there have been a series of results regarding two time optimal control problems for a class of linear and nonlinear systems ‐ one is to keep the system states within certain bound for the longest time during feedback disruption and the other is to derive the system states to near the origin as fast as possible after feedback recovery, both under bounded control inputs. These are called maximal and minimal time optimal control problems, respectively. In the existing results, a bang‐bang controller has been commonly suggested as the actual implementation of the optimal controller. In this paper, we suggest a modified version of the bang‐bang controller which can also serve as an approximate optimal controller. Our proposed controller provides the (near) optimal performance with (i) possible reduction of a number of switchings; (ii) possible reduction of control input magnitude. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicles are among the most widely attracting interest, especially in the applications of transportation, inspection, and surveillance. The great mechanisms for motion control are set to become a vital factor in performing the robust and accurate stabilized flight relied on perturbations and disturbances. This paper presents modified adaptive sliding mode control for trajectory tracking of mini-drone quadcopter unmanned aerial vehicles, which aims at demonstrating the effectiveness of nonlinear adaptive control strategy for achieving the desired performance of the mini-drone quadcopter system. Besides providing mathematical modeling and nonlinear dynamic characteristic details of mini-drone quadcopter actuated system, the modified adaptive sliding mode algorithm is developed using adaptation law based on Lyapunov stability approach then applied on the attitude loop and the altitude loop control system so that the nonlinear adaptive behavior of the controller enables the compensation of disturbances and parameter perturbations. The effectiveness validations of the proposed control technique compared with the traditional approach are performed through the Matlab simulation. The results have been illustrated that the modified adaptive sliding mode control can decrease the error performance indexes to the minimum ISE at 1.041 m² and the zero percentage of overshoot while enables excellent stability and robustness even in the presence of parameter perturbations and disturbance. [ABSTRACT FROM AUTHOR]

Handling both intermittent actuator faults and coupled interconnections in uncertain multiple-input–multiple-output nonlinear system is still a challenge in the control community. In this paper, to address this issue, an adaptive neural fault-tolerant control scheme is developed. Firstly, neural networks with random hidden nodes are used to approximate unknown functions, and an inequality is introduced to construct controllers such that the singularity problem of the controllers can be circumvented. Secondly, a projection algorithm is adopted to update online the estimated parameters in the controllers such that the boundedness of estimated parameters is ensured. In particular, the boundedness of estimate of unknown fault parameters with intermittent jumps can be definitely guaranteed. Due to the effects of intermittency jumps of unknown parameters on the system stability during operation, a modified Lyapunov function is developed to prove the system stability. It is proved that the system stability only depends on the jumping amplitude of Lyapunov function and the minimum fault time interval and is not affected by the total number of faults. Thirdly, a root mean square type of bound for the tracking error is established by using iterative calculation to illustrate that the system transient performance in the sense of the tracking error is adjustable by proper choice of design parameters. Finally, simulation studies are carried out to verify the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]