Adaptive Observer‐Based Global Sliding Mode Control for Uncertain Discrete‐Time Nonlinear Systems with Time‐Delays and Input Nonlinearity

A new discrete‐time adaptive global sliding mode control (SMC) scheme combined with a state observer is proposed for the robust stabilization of uncertain nonlinear systems with mismatched time delays and input nonlinearity. A state observer is developed to estimate the unmeasured system states. By using Lyapunov stability theorem and linear matrix inequality (LMI), the condition for the existence of quasi‐sliding mode is derived and the stability of the overall closed‐loop system is guaranteed. Finally, simulation results are presented to demonstrate the validity of the proposed scheme.     

LMI optimization approach to robust decentralized controller design

A new approach for design of robust decentralized controllers for continuous linear time‐invariant systems is proposed using linear matrix inequalities (LMIs). The proposed method is based on closed‐loop diagonal dominance. Sufficient conditions for closed‐loop stability and closed‐loop block‐diagonal dominance are obtained. Satisfying the obtained conditions is formulated as an optimization problem with a system of LMI constraints. By adding an extra LMI constraint to the system of LMI constraints in the optimization problem, the robust control is addressed as well. Accordingly, the decentralized robust control problem for a multivariable system is reduced to an optimization problem for a system of LMI constraints to be feasible. An example is given to show the effectiveness of the proposed method. Copyright © 2010 John Wiley & Sons, Ltd.     

Robust controller design for input‐delayed systems using predictive feedback and an uncertainty estimator

This paper deals with the problem of stabilizing a class of input‐delayed systems with (possibly) nonlinear uncertainties by using explicit delay compensation. It is well known that plain predictive schemes lack robustness with respect to uncertain model parameters. In this work, an uncertainty estimator is derived for input‐delay systems and combined with a modified state predictor, which uses current available information of the estimated uncertainties. Furthermore, based on Lyapunov–Krasovskii functionals, a computable criterion to check robust stability of the closed‐loop is developed and cast into a minimization problem constrained to an LMI. Additionally, for a given input delay, an iterative‐LMI algorithm is proposed to design stabilizing tuning parameters. The main results are illustrated and validated using a numerical example with a second‐order dynamic system. Copyright © 2016 John Wiley & Sons, Ltd.     

Prediction‐based Adaptive Robust Tracking Control of an Uncertain First‐Order Time‐Delay System

This paper considers the tracking problem of a delayed uncertain first‐order system which is simultaneously subject to (possibly large) known input delay, unknown but bounded time‐varying disturbance, and unknown plant parameter. The proposed predictor adaptive robust controller (PARC) involves prediction‐based projection type adaptation laws with model compensation and prediction‐based continuous robust feedback such that the closed loop system has global exponential convergence with an ultimate bound proportional to delay, disturbance bound, and switching gain. Further, if there are only delay and parameter uncertainties after some finite time, then semi‐global asymptotic tracking is guaranteed. The proposed design is shown to have significant closed loop performance improvement over the baseline controller.     

采用还原方法的不确定关联时滞系统的鲁棒分散镇定

针对一类具有多输入时滞项及互联时滞项的不确定关联系统，提出了系统可鲁棒分散镇定的充分条件，即一组线性矩阵不等式(LMI)有解．系统的不确定性是未知时变且范数有界的，基于还原方法及LMI技术给出系统设计状态反馈分散控制器的方法．该控制器保证闭环系统全局渐近稳定，且设计简单，计算量小，易于工程实现．最后通过仿真例子说明了该方法的有效性．     

基于Delta算子系统TS模型的鲁棒稳定性研究

针对一类不确定Delta算子系统,建立其TS模糊模型,并讨论了闭环系统的鲁棒稳定性.首先将一类基于Delta算子描述的系统,表示成TS模糊动态不确定系统形式,然后利用Lyapunov函数法,给出了系统渐近稳定的充分条件.该条件是线性矩阵不等式(LMI)形式的,可以很方便地利用Matlab工具箱进行求解.所得的结果将连续和离散系统统一到Delta算子框架中.数值仿真表明了该方法的有效性和可行性.     

Aero‐Engine DCS Fault‐Tolerant Control with Markov Time Delay Based On Augmented Adaptive Sliding Mode Observer

With a focus on aero‐engine distributed control systems (DCSs) with Markov time delay, unknown input disturbance, and sensor and actuator simultaneous faults, a combined fault tolerant algorithm based on the adaptive sliding mode observer is studied. First, an uncertain augmented model of distributed control system is established under the condition of simultaneous sensor and actuator faults, which also considers the influence of the output disturbances. Second, an augmented adaptive sliding mode observer is designed and the linear matrix inequality (LMI) form stability condition of the combined closed‐loop system is deduced. Third, a robust sliding mode fault tolerant controller is designed based on fault estimation of the sliding mode observer, where the theory of predictive control is adopted to suppress the influence of random time delay on system stability. Simulation results indicate that the proposed sliding mode fault tolerant controller can be very effective despite the existence of faults and output disturbances, and is suitable for the simultaneous sensor and actuator faults condition.     

含时变滞后的不确定系统的时滞相关型鲁棒控制设计

研究含时变滞后的不确定系统的控制综合问题. 基于Lyapunov方法提出了一种含滞后补偿的鲁棒控制设计方法. 闭环稳定性条件由一组线性矩阵不等式表示. 在这些条件中给出了稳定性和滞后以及其导数之间的关系. 实例显示, 利用提供的方法所给出的结果比以往文献给出的结果保守性小.     

线性时滞系统对时滞参数的自适应控制

针对实际中线性时滞系统的时滞常数往往不能精确已知的缺点,对具有状态滞后的线性时滞系统提出一种对时滞常数的自适应控制方案,其控制器存在的充分条件由一个线性矩阵不等式（LMI）的形式给出,并对整个闭环系统的稳定性进行了分析。     

Stability analysis of input constrained continuous time indirect adaptive control

Stability analysis of continuous time indirect pole placement adaptive control with input constraint is presented in this paper. It is shown that the closed loop system for a class of stable type-1 plants is globally stable in the sense that all the signals in the loop remain bounded, and that certain degree of robustness with respect to modelling uncertainties and disturbances can be achieved by implementing a simple fixed dead zone in the parameter estimator. It is also shown that if the plant is free from modelling uncertainties and disturbances, and the control input is not saturated for a finite period of time, then the closed loop system will asymptotically be characterized by the desired closed loop poles within this time period.     

Robust Adaptive Fractional‐Order Terminal Sliding Mode Control for Lower‐Limb Exoskeleton

This paper introduces a robust adaptive fractional‐order non‐singular fast terminal sliding mode control (RFO‐TSM) for a lower‐limb exoskeleton system subject to unknown external disturbances and uncertainties. The referred RFO‐TSM is developed in consideration of the advantages of fractional‐order and non‐singular fast terminal sliding mode control (FONTSM): fractional‐order is used to obtain good tracking performance, while the non‐singular fast TSM is employed to achieve fast finite‐time convergence, non‐singularity and reducing chattering phenomenon in control input. In particular, an adaptive scheme is formulated with FONTSM to deal with uncertain dynamics of exoskeleton under unknown external disturbances, which makes the system robust. Moreover, an asymptotical stability analysis of the closed‐loop system is validated by Lyapunov proposition, which guarantees the sliding condition. Lastly, the efficacy of the proposed method is verified through numerical simulations in comparison with advanced and classical methods.     

Delay‐dependent anti‐windup strategy for linear systems with saturating inputs and delayed outputs

This paper addresses the problem of the determination of stability regions for linear systems with delayed outputs and subject to input saturation, through anti‐windup strategies. A method for synthesizing anti‐windup gains aiming at maximizing a region of admissible states, for which the closed‐loop asymptotic stability and the given controlled output constraints are respected, is proposed. Based on the modelling of the closed‐loop system resulting from the controller plus the anti‐windup loop as a linear time‐delay system with a dead‐zone nonlinearity, constructive delay‐dependent stability conditions are formulated by using both quadratic and Lure Lyapunov–Krasovskii functionals. Numerical procedures based on the solution of some convex optimization problems with LMI constraints are proposed for computing the anti‐windup gain that leads to the maximization of an associated stability region. The effectiveness of the proposed technique is illustrated by some numerical examples. Copyright © 2004 John Wiley & Sons, Ltd.     

Adaptive neural network control of bilateral teleoperation with unsymmetrical stochastic delays and unmodeled dynamics

In this paper, adaptive NN control is proposed for bilateral teleoperation system with dynamic uncertainties, unknown external disturbances, and unsymmetrical stochastic delays in communication channel to achieve transparency and robust stability. Compared with previous passivity‐based teleoperation framework, the communication delays are unsymmetrical and stochastic. By partial feedback linearization using nominal dynamics, the nonlinear dynamics of the teleoperation system are transformed into two subsystems: local master/slave dynamics control and time‐delay motion tracking. By integrating Markov jump systems and adaptive parameters updating, adaptive NN control strategy is developed. The stability of the closed‐loop system and the boundedness of tracking errors are proved using Lyapunov–Krasovskii functional synthesis under specific linear matrix inequalities conditions. The proposed adaptive NN control is robust against motion disturbances, parametric uncertainties, and unsymmetrical stochastic delay, which effectiveness is validated by extensive simulation studies. Copyright © 2013 John Wiley & Sons, Ltd.     

Nonlinear Adaptive Model Predictive Control of Constrained Systems with Offset‐Free Tracking Behavior

In this paper, a nonlinear model‐based predictive control strategy for constrained systems based on an adaptive neural network (NN) predictor is proposed. The proposed controller is robust against the model uncertainties and external bounded disturbances. Moreover, it provides offset‐free tracking behavior using the adaptive structure in the model. Based on the uncertainties bounds, the restriction of the system constraints causes robust feasibility and stability of the closed‐loop system. It is shown that the output of the NN predictor converges to the system output. Moreover, offset‐free behavior of the closed‐loop system is investigated using the Lyapunov theorem. Simulation results show the effectiveness of the proposed method as compared to the recently proposed model predictive control methods in the literature.     

ROBUST STABILITY AND STABILIZATION OF A CLASS OF SINGULAR SYSTEMS WITH MULTIPLE TIME‐VARYING DELAYS

This paper deals with the problem of robust stability and robust stabilization for uncertain continuous singular systems with multiple time‐varying delays. The parametric uncertainty is assumed to be norm bounded. The purpose of the robust stability problem is to give conditions such that the uncertain singular system is regular, impulse free, and stable for all admissible uncertainties. The purpose of the robust stabilization problem is to design a feedback control law such that the resulting closed‐loop system is robustly stable. This problem is solved via generalized quadratic stability approach. A strict linear matrix inequality (LMI) design approach is developed. Finally, a numerical example is provided to demonstrate the application of the proposed method.     

Adaptive Reinforcement Learning Strategy with Sliding Mode Control for Unknown and Disturbed Wheeled Inverted Pendulum

This paper develops a novel adaptive integral sliding-mode control (SMC) technique to improve the tracking performance of a wheeled inverted pendulum (WIP) system, which belongs to a class of continuous time systems with input disturbance and/or unknown parameters. The proposed algorithm is established based on an integrating between the advantage of online adaptive reinforcement learning control and the high robustness of integral sliding-mode control (SMC) law. The main objective is to find a general structure of integral sliding mode control law that can guarantee the system state reaching a sliding surface in finite time. An adaptive/approximate optimal control based on the approximate/adaptive dynamic programming (ADP) is responsible for the asymptotic stability of the closed loop system. Furthermore, the convergence possibility of proposed output feedback optimal control was determined without the convergence of additional state observer. Finally, the theoretical analysis and simulation results validate the performance of the proposed control structure.

     

Fault tolerant control using virtual actuator for continuous‐time Lipschitz nonlinear systems

In this brief, we extend the existing results on fault tolerant control via virtual actuator approach to a class of systems with Lipschitz nonlinearities to maintain the closed‐loop stability after actuator faults. This generalization is established by relying on the input‐to‐state stability properties of cascaded systems. The virtual actuator block, placed between faulty plant and nominal controller, generates useful input signals for faulty plant by using output signals of the nominal controller to guarantee the closed‐loop stability in the presence of actuator faults. This design problem is reduced to a matrix inequality that can be turned to an LMI by fixing a variable to a constant value and solving the resulting LMI feasibility problem. The proposed fault tolerant control method is successfully evaluated using a nonlinear system. Copyright © 2013 John Wiley & Sons, Ltd.     

Robust Mrac Of A Nonautonomous Parabolic System With Spatiotemporally Varying Coefficients And Bounded Disturbance

In this paper, a robust model reference adaptive control of a parabolic system with unknown spatiotemporally varying coefficients and disturbance is investigated. In the adaptive control of time‐varying plants, the derivative of a Lyapunov function candidate, which allows the derivation of adaptation laws, is not negative semi‐definite in general. Under the assumption that the disturbance is uniformly bounded, the proposed robust adaptive scheme guarantees the boundedness of all signals in the closed loop system and the asymptotic convergence of the state error near to zero. With an additional persistence of excitation condition, the parameter estimation errors are shown to converge near to zero as well. Simulation results are provided.     

Adaptive fault tolerant control for a class of input and state constrained MIMO nonlinear systems

In this work, we present a novel adaptive fault tolerant control (FTC) scheme for a class of control input and system state constrained multi‐input multi‐output (MIMO) nonlinear systems with both multiplicative and additive actuator faults. The input constraints can be asymmetric, and the state constraints can be time‐varying. A novel tan‐type time‐varying Barrier Lyapunov Function (BLF) is proposed to deal with the state constraints, and an auxiliary system is designed to analyze the effect of the input constraints. We show that under the proposed adaptive FTC scheme, exponential convergence of the output tracking error into a small neighbourhood of zero is guaranteed, while the constraints on the system state will not be violated during operation. Estimation errors for actuator faults are bounded in the closed loop. An illustrative example on a two degree‐of‐freedom robotic manipulator is presented to demonstrate the effectiveness of the proposed FTC scheme. Copyright © 2015 John Wiley & Sons, Ltd.