Observer-based output regulation of cooperative-competitive high-order multi-agent systems

In this paper, a coopetitive output regulation problem is considered for general linear multi-agent systems with antagonistic interactions, where not all the agents have access to the state, the output, the system matrix and the output matrix of the exogenous system or exosystem. In this sense, the internal model incorporation of the system matrix of the exosystem is also only available to some agents. Thus, we propose distributed observers for each agent: (i) To estimate the state, the output, the system matrix and the output matrix, and (ii) the unavailable internal model of the exosystem. Then, a distributed dynamic output feedback controller is proposed for each agent to solve the coopetitive output regulation problem. The exponential stability of the closed-loop system is analyzed with the output regulation theory. Finally, some simulation results are presented to validate the proposed control strategy.     

Distributed fault-tolerant output regulation for heterogeneous linear multi-agent systems under actuator faults

This study investigates the distributed fault-tolerant output regulation for heterogeneous linear multi-agent systems in the presence of actuator faults. For the systems which are not the neighbors of exosystem, the distributed fixed-time observer is put forward to observe the state of exosystem. Note that it is dependent on the global information of network topology. To address this issue, the fully distributed adaptive fixed-time observer is further proposed. It can estimate not only the state of exosystem, but also the system matrix of exosystem. Based on the proposed observer, a novel fault-tolerant controller is developed to compensate for actuator faults. Moreover, it is proven that the proposed controller is effective to address the fault-tolerant output regulation problem by the Lyapunov stability theory. Finally, two illustrative examples are given to illustrate the feasibility of the main theoretical findings.     

Trajectory tracking of flexible joint manipulators actuated by DC-motors under random disturbances

For a class of flexible joint manipulators actuated by DC-motors, the problem of modeling and trajectory tracking control under random disturbances is considered in this paper. How to describe random disturbances and introduce them to the system is the key for modeling and control. According to the relative motion and the equivalent circuit, the effect of random disturbances can be regarded as torque or voltage disturbed by colored noises. Thus, a random model is constructed. By using the vectorial backstepping and the technique of separating out the noise from coupled terms, a state feedback tracking controller is designed such that the state of closed-loop system has an asymptotic gain in the 2nd moment and the mean square of tracking error converges to an arbitrarily small neighborhood of zero by tuning design parameters. The effectiveness of the proposed scheme is demonstrated by the simulation results for a two-link robot.     

Global sampled-data output feedback stabilization for a class of stochastic nonlinear systems with time-varying delay

This paper studies the global sampled-data output feedback stabilization problem for a class of stochastic nonlinear systems. The considered system is in non-strict feedback form with unknown time-varying delay. A state observer is introduced to estimate the unmeasured states. With the help of the backstepping method, a linear sampled-data output feedback controller is constructed. By choosing an appropriate Lyapunov–Krasoviskii functional and an allowable sampling period, it is shown that the stochastic system can be globally asymptotically stabilized in the mean square sense under the developed control scheme. Finally, two examples are presented to verify the effectiveness of the designed control scheme.     

Adaptive fuzzy-based composite anti-disturbance control for a class of switched nonlinear systems with unknown backlash-like hysteresis

For a class of switched nonlinear systems with unmatched external disturbances and unknown backlash-like hysteresis, an adaptive fuzzy-based control strategy is proposed to handle the anti-disturbance issue. The unmatched external disturbances come from a switched exosystem. Our aim is to achieve the output tracking performance and the disturbance attenuation by using the adaptive fuzzy-based composite anti-disturbance control technique. First, based on the fuzzy logics, we design a switching adaptive fuzzy disturbance observer to estimate unmatched external disturbances. Second, a composite switching adaptive anti-disturbance controller is constructed. By means of the backstepping technique, disturbance estimations are added in each virtual control to offset the unmatched disturbances, which results in the different coordinate transformations. At last, the availability of the proposed approach is illustrated by a mass-spring-damper system.     

Rendezvous problem of multiple linear uncertain systems under state-dependent dynamic networks

This paper studies the rendezvous problem for a class of linear systems with uncertain parameters and external disturbances under the state-dependent dynamic network, which is also called rendezvous network here. By combining potential function technique, distributed internal model design and adaptive control technique, a distributed adaptive state feedback control law is proposed to solve the rendezvous problem by completing the tasks of maintaining the connectivity of the rendezvous network, achieving asymptotic tracking, rejecting unknown external disturbances as well as handling uncertain parameters in the system dynamics, the leader system and the exosystem simultaneously.     

Adaptive fuzzy tracking control for input and output constrained stochastic nonlinear systems: A NM-based approach

This paper investigates the tracking control problem for output constrained stochastic nonlinear systems under quantized input. The main challenge of considering such dynamics lies in the fact that theirs have both input and output constraints, making the standard backstepping technique fail. To address this challenge, the introduction of nonlinear mapping transforms the constrained nonlinear systems into unconstrained nonlinear systems, which not only avoids the emergence of feasibility conditions but also simplifies the structure of designed controller. The obstacle caused by quantized input is successfully resolved by exploiting the decomposition of hysteresis quantizer. Additionally, the uncertain nonlinearities are approximated by fuzzy logic systems during the control design process. Under the proposed quantized tracking control scheme, the output tracking error converges to an arbitrarily small neighborhood of origin and all signals in the closed-loop system remain bounded in probability. Simultaneously, it can make sure that the output constraint isn’t violated. Ultimately, both a numerical example and a practical example are provided to clarify the effectiveness of the control strategy.     

Adaptive fault-tolerant shape control for nonlinear Lipschitz stochastic distribution systems

This paper addresses the problem of adaptive fault estimation and fault-tolerant control for a class of nonlinear non-Gaussian stochastic systems subject to time-varying loss of control effectiveness faults. In this work, time-varying faults, Lipschitz nonlinear property and general stochastic characteristics are taken into consideration in a unified framework. Instead of using the system output signal, the output distribution is adopted for shape control. Both the states and faults are simultaneously estimated by an adaptive observer. Then, a fault tolerant shape controller is designed to compensate for the faults and realize stochastic output distribution tracking. Both the fault estimation and the fault tolerant control schemes are designed based on linear matrix inequality (LMI) technique. Satisfactory performance has been obtained for a numerical simulation example. Furthermore the proposed scheme is successfully tested in a case study of particle size distribution control for an emulsion polymerization reactor.     

Trajectory tracking and disturbance rejection control of random linear systems

A more general trajectory tracking and disturbance rejection problem for the random linear system is considered in this paper. The known structural properties of the reference and the disturbance signals motivate us to use the internal model principle, and the motion decomposition for the linear systems prompts us to utilize the superposition principle. Combining the spectral analysis method with the pole assignment algorithm, the stability and tracking property can be obtained. The simulation result demonstrates that all the closed-loop system is exponentially practically stable in the mean square (EpS-2-M), the tracking error can be regulated to an arbitrarily small constant by turning the parameters.     

Fault diagnosis and fault tolerant control for the non-Gaussian time-delayed stochastic distribution control system

The purpose of fault diagnosis of stochastic distribution control (SDC) systems is to use the measured input and the system output probability density functions (PDFs) to obtain the fault information of the SDC system. When the target PDF is known, the purpose of fault tolerant control of stochastic distribution control system is to make the output PDF still track the given distribution using the fault tolerant controller. However, in practice, time delay may exist in the data (or image) processing, the modeling and transmission phases. When time delay is not considered, the effectiveness of the fault detection, diagnosis and fault tolerant control of stochastic distribution systems will be reduced. In this paper, the rational square-root B-spline is used to approach the output probability density function. In order to diagnose the fault in the dynamic part of such systems, it is then followed by the novel design of a nonlinear neural network observer-based fault diagnosis algorithm. The time delay term will be deleted in the stability proof of the observation error dynamic system. Based on the fault diagnosis information, a new fault tolerant controller based on PI tracking control is designed to make the post-fault probability density function still track the given distribution, which is dependent of the time delay term. Finally, simulations for the particle distribution control problem are given to show the effectiveness of the proposed approach.     

Passive fuzzy controller design for nonlinear systems with multiplicative noises

This paper proposes a passive fuzzy controller design methodology for nonlinear system with multiplicative noises. Applying the Itô's formula and the sense of mean square, the sufficient conditions are developed to analyze the stability and to design the controller for stochastic nonlinear systems which are represented by the Takagi-Sugeno (T-S) fuzzy models. The sufficient conditions derived in this paper belong to the Linear Matrix Inequality (LMI) forms which can be solved by the convex optimal programming algorithm. Besides, the passivity theory is applied to discuss the effect of external disturbance on system. Finally, some numerical simulation examples are provided to demonstrate the applications of the proposed fuzzy controller design technique.     

Robust time-varying output formation tracking for heterogeneous multi-agent systems with adaptive event-triggered mechanism

This paper investigates the time-varying output formation tracking problem of heterogeneous multi-agent systems subjected to model uncertainties and external disturbances via adaptive event-triggered mechanism. Firstly, an adaptive distributed event-triggered observer is constructed to acquire the leader’s state and a time-varying formation output tracking controller utilizing sliding mode method is proposed to deal with the model uncertainties and external disturbances can be addressed. Secondly, an algorithm is given to claim the design procedures of the event-triggered based controller and asymptotic convergence of the controller is proved based on Lyapunov theory. Thirdly, Zeno-behavior is proved to be excluded strictly. Finally, a numerical example is given to illustrate the effectiveness of the proposed algorithm.     

Output tracking control with L1-gain performance for positive switched systems

This paper concentrates on the output tracking control problem with L₁-gain performance of positive switched systems. We adopt the multiple co-positive Lyapunov functions technique and conduct the dual design of the controller and the switching signal. Through introducing a new state variable, which is not the output error, the output tracking control problem of the original system is transformed into the stabilization problem of the dynamics system of this new state. The proposed approach is still effective even the output tracking control problem of any subsystem is unsolvable. According to the state being available or not, we establish the solvability conditions of the output tracking control problem for positive switched systems, respectively. In the end, a number example demonstrates the validity of the presented results.     

GIMC architecture for linear systems with a single I/O delay

A new feedback controller architecture is presented for linear systems with a single I/O delay in the generalized internal model control (GIMC) framework. According to the doubly coprime factorization of these systems, traditional GIMC strategy is extended to linear systems with a single I/O delay. The distinguished feature of the control system architecture is that high tracking performance and good external disturbance rejection could be done separately by a nominal Smith predictor part and a finite dimensional conditional controller. First, a nominal Smith predictor part could be designed to deal with command tracking performance. Second, according to the left coprime factorization of the nominal controller, a finite dimensional conditional controller could be considered for external disturbance rejection, when the controlled plant should be assumed to be a square one. Finally, a simple design example is illustrated the effectiveness of the presented method.Finally, a simple design example is illustrated the effectiveness of the presented method.     

Finite-time command filter-based adaptive fuzzy tracking control for stochastic nonlinear induction motors systems with unknown backlash-like hysteresis

In this article, an adaptive fuzzy control method is proposed for induction motors (IMs) drive systems with unknown backlash-like hysteresis. First, the stochastic nonlinear functions existed in the IMs drive systems are resolved by invoking fuzzy logic systems. Then, a finite-time command filter technique is exploited to overcome the obstacle of “explosion of complexity” emerged in the classical backstepping procedure during the controller design process. Meanwhile, the effect of the filter errors generated by command filters is decreased by utilizing corresponding error compensating mechanism. To cope with the influence of backlash-like hysteresis input, an auxiliary system is constructed, in which the output signal is applied to compensate the effect of the hysteresis. The finite-time control technology is adopted to accelerate the response speed of the system and reduce the tracking error, and the stochastic disturbance and backlash-like hysteresis are considered to improve control accuracy. It’s shown that the tracking error can converge to a small neighborhood around the origin in finite-time under the constructed controller. Finally, the availability of the presented approach is validated through simulation results.     

A case study on the universal compensation-improvement mechanism: A robust PID filter-shaped optimal PI tracker for systems with/without disturbances

Many dynamical systems are continuous-time non-square with unknown mismatched input and output disturbances. For such systems, a universal on-line robust optimal tracking control is often desirable. In this paper, the conventional proportional-integral-differential (PID) controller is utilized as a fictitious PID filter to shape the tracking error in the frequency-domain using a quadratic performance index as a weighting function, such that the robust PID-shaped PI tracker integrated with the equivalent input disturbance (EID) estimator is established to carry out the on-line robust optimal tracking control of the general disturbed system. The benefits and discrepancies of the proposed compensation improvement mechanism over the conventional optimal trackers for continuous-time non-square systems with/without unknown mismatched input and output disturbances are listed as follows: (i) It develops a new net EID estimator without any previously established constraints on the dimensions of the system and on the disturbances; (ii) It provides an efficient estimated-state-feedback-based EID estimator in contrast to the conventional output-feedback-based EID estimators; (iii) It is able to carry out on-line EID estimation of the tracking errors for systems with endogenous/exogenous output disturbances; (iv) It is a universal tracker which can be simply implemented as a plug-in EID estimator for most servo systems, to improve the performance of any existing observers/trackers which are not allowed to be removed from the system. The advantages of the proposed method over two existing outstanding approaches reported in the literature are pointed out using illustrative examples.     

Flatness-based adaptive fuzzy output tracking excitation control for power system generators

In this paper, a novel approach for the design of an indirect adaptive fuzzy output tracking excitation control of power system generators is proposed. The method is developed based on the concept of differentially flat systems through which the nonlinear system can be written in canonical form. The flatness-based adaptive fuzzy control methodology is used to design the excitation control signal of a single machine power system in order to track a reference trajectory for the generator angle. The considered power system can be written in the canonical form and the resulting excitation control signal is shown to be nonlinear. In case of unknown power system parameters due to abnormalities, the nonlinear functions appearing in the control signal are approximated using adaptive fuzzy systems. Simulation results show that the proposed controller can enhance the transient stability of the power system under a three-phase to ground fault occurring near the generator terminals.     

Design of a preview repetitive control with equivalent-input-disturbance system based on a continuous-discrete 2D model

This paper deals with the problem of two-dimensional (2D) system-based preview repetitive control (PRC) with equivalent-input-disturbance (EID) for uncertain continuous-time systems. First, to use the available values of the reference signal, we construct an equality constraint which includes the output of a basic repetitive controller, preview compensation and tracking error. Next, to compensate the unknown external disturbances, we incorporate an EID estimator into the PRC controller. Then, by employing the 2D system theory together with the linear matrix inequality (LMI) approach, we derive a sufficient condition to ensure the robust stability of the closed-loop system. By solving an LMI, the gains of the controller and state observer can be obtained. The results obtained in this paper generalize and include some results in the existings. literature. Finally, a numerical simulation demonstrates the effectiveness and superiority of the proposed method.     

基于动力学模型的四轮全向机器人滑模轨迹跟踪控制

四轮全向机器人是一个复杂的四维冗余系统,其轨迹跟踪控制性能极易受到模型不确定性及外界干扰的影响。针对这一问题,本文提出一种基于动力学模型的四轮全向机器人滑模轨迹跟踪控制方法。首先,通过输入变换将复杂的四维冗余机器人系统模型转化为三维模型,然后针对模型不确定性及外界扰动,采用滑模控制算法进行轨迹跟踪控制。仿真结果表明,该方法能够有效抑制外界干扰,同时降低模型不确定性的影响,机器人能够很好地跟踪期望轨迹,跟踪速度快,跟踪精度高。     

Quantized asynchronous extended dissipative observer-based sliding mode control for Markovian jump TS fuzzy systems

This article is dedicated to the issue of asynchronous adaptive observer-based sliding mode control for a class of nonlinear stochastic switching systems with Markovian switching. The system under examination is subject to matched uncertainties, external disturbances, and quantized outputs and is described by a TS fuzzy stochastic switching model with a Markovian process. A quantized sliding mode observer is designed, as are two modes-dependent fuzzy switching surfaces for the error and estimated systems, based on a mode dependent logarithmic quantizer. The Lyapunov approach is employed to establish sufficient conditions for sliding mode dynamics to be robust mean square stable with extended dissipativity. Moreover, with the decoupling matrix procedure, a new linear matrix inequality-based criterion is investigated to synthesize the controller and observer gains. The adaptive control technique is used to synthesize asynchronous sliding mode controllers for error and SMO systems, respectively, so as to ensure that the pre-designed sliding surfaces can be reached, and the closed-loop system can perform robustly despite uncertainties and signal quantization error.Finally, simulation results on a one-link arm robot system are provided to show potential applications as well as validate the effectiveness of the proposed scheme.