Robust control for nonlinear time-varying systems with application to a robotic manipulator

Sliding mode control methods have been used widely because they provide robustness against parameter variations and disturbances. This paper focuses on the problem of a robust output-sliding control design for a class of nonlinear time-varying systems. Output signals are used for the switching function definition. The control law formulation is emphasized. Input and output linearization is used. Output tracking can be achieved against a class of time-varying parameter variations and external disturbances. An application to a two-degree-of-freedom manipulator indicates that the proposed switching control law drives the system state trajectories onto the chosen sliding mode in finite time and the output tracking is guaranteed.     

一类仿射非线性系统的概率密度函数形状控制

针对一类仿射非线性有界动态随机系统,提出一种最优概率密度函数（PDF）跟踪控制算法,使得系统的输出PDF跟踪给定的PDF．首先利用线性B样条解耦得到仿射非线性状态方程和PDF逼近方程,使PDF跟踪转化为状态方程输出权值的跟踪;然后采用线性时变序列逼近方法将非线性系统转化为线性时变系统,通过对线性系统的迭代运算得到非线性系统的最优跟踪控制器,从而实现最优PDF跟踪．理论分析和仿真实验均表明了所提出算法的有效性．     

时变输出约束非完整系统的非缩放预设时间镇定控制设计（英文）

本文针对一类具有时变输出约束链式非完整系统的预设时间镇定问题,首先通过tan型障碍Lyapunov函数处理系统输出约束,然后基于所给的新型切换时变函数,直接应用于虚拟(实际)控制器设计,提出了系统状态反馈镇定的非缩放变换设计方案.本文所设计的控制器使得闭环系统状态不违反约束的同时,可在任意给定的有限时间内收敛到零点.与传统的基于缩放变换设计相比,本文所提出的控制策略既有效解决了控制器的计算奇异性问题,又减少了关于时变缩放函数的计算,使控制器设计更为简单.最后,通过仿真结果验证了所提设方法的有效性.     

控制方向未知的全状态约束非线性系统的鲁棒自适应跟踪控制

针对一类控制方向未知的含有时变不确定参数和未知时变有界扰动的全状态约束非线性系统,本文提出了一种基于障碍Lyapunov函数的反步自适应控制方法.障碍Lyapunov函数保证了系统状态在运行过程中始终保持在约束区间内;Nussbaum型函数的引入解决了系统控制方向未知的问题;光滑投影算法确保了不确定时变参数的有界性.障碍Lyapunov函数、Nussbaum型函数及光滑投影算法与反步自适应方法的有效结合首次解决了控制方向未知的全状态约束非线性系统的跟踪控制问题.所设计的自适应鲁棒控制器能在满足状态约束的前提下确保闭环系统的所有信号有界.通过恰当地选取设计参数,系统的跟踪误差将收敛于0的任意小的邻域内.仿真结果表明了控制方案的可行性.     

Set-valued observers and optimal disturbance rejection

A set-valued observer (also called guaranteed state estimator) produces a set of possible states based on output measurements and models of exogenous signals. We consider the guaranteed state estimation problem for linear time-varying systems with a priori magnitude bounds on exogenous signals. We provide an algorithm to propagate the set of possible states based on output measurements and show that the centers of these sets provide optimal estimates in an l^∞-induced norm sense. We then consider the utility of set-valued observers for disturbance rejection with output feedback and derive the following general separation structure. An optimal controller can consist of a set-valued observer followed by a static nonlinear function on the observed set of possible states. A general construction of this function is provided in the scalar control case. Furthermore, in the special case of full-control, i.e., the number of control inputs equals the number of states, optimal output feedback controllers can take the form of an optimal estimate of the full-state feedback controller     

控制方向未知的二阶时变非线性系统自适应迭代学习控制

对一类二阶严格反馈时变非线性系统的自适应迭代学习控制问题进行了研究.系统中含有非周期时变参数化不确定性且控制方向未知.首先,提出了一种神经网络估计器,实现了对未知非周期时变非线性函数的逼近.随后,用Nussbaum函数对未知控制方向进行了自适应估计,并综合应用baCkstcpping技术和自适应迭代学习控制技术设计了控制器.所设计的控制器能保证系统所有状态量在Lpe-范数意义下有界,且系统的输出量在LT2-范数意义下收敛到期望轨迹.最后的仿真研究证明了控制器设计方法的有效性.     

状态时滞时变不确定系统的鲁棒H∞ 输出反馈控制器设计

主要研究了存在状态滞后的线性时变不确定时滞系统的鲁棒H     

一类线性时变系统的输出反馈控制

基于线性时不变系统能控能观标准型变换及非线性系统高增益观测器方法,本文研究了一类线性时变系统 的输出反馈控制问题. 通过引入时变的状态变量坐标变换,分别设计了线性时变系统的状态反馈控制器、状态观测器以及基于 状态观测器的输出反馈控制器. 进一步地,本文分别证明了观测器动态误差是渐近收敛于零的,而状态反馈控制器以及输出反馈控制器可以 保证闭环系统的渐近稳定性.     

Adaptive Neural Network-Based Control for a Class of Nonlinear Pure-Feedback Systems With Time-Varying Full State Constraints

In this paper, an adaptive neural network (NN) control approach is proposed for nonlinear pure-feedback systems with time-varying full state constraints. The pure-feedback systems of this paper are assumed to possess nonlinear function uncertainties. By using the mean value theorem, pure-feedback systems can be transformed into strict feedback forms. For the newly generated systems, NNs are employed to approximate unknown items. Based on the adaptive control scheme and backstepping algorithm, an intelligent controller is designed. At the same time, time-varying Barrier Lyapunov functions (BLFs) with error variables are adopted to avoid violating full state constraints in every step of the backstepping design. All closedloop signals are uniformly ultimately bounded and the output tracking error converges to the neighborhood of zero, which can be verified by using the Lyapunov stability theorem. Two simulation examples reveal the performance of the adaptive NN control approach.      

H∞ control via output feedback for linear systems with time-varying delays in state and control input

In this paper, an observer-based H_∞ controller for systems with time-varying delays in state and control input is proposed. Using the solution of proposed modified algebraic Riccati equation, we can construct a controller which depends on the maximum value of the time derivative of time-varying delay and guarantees a prescribed H_∞ norm bound of the closed-loop transfer matrix from the disturbance to the controlled output. A given example illustrates the availability of the proposed design method.     

带有输出约束的柔性关节机械臂预设性能自适应控制

针对带有输出约束和模型不确定的柔性关节机械臂系统,提出一种基于时变障碍李雅普诺夫函数的预设性能自适应控制方法.通过构造指数衰减的时变约束边界,提出时变正切型障碍李雅普诺夫函数,能够同时适用于约束与非约束情况,进而拓宽传统对数型障碍李雅普诺夫函数的适用范围.此外,通过预先设置时变边界函数的相关参数,使得系统输出在初始阶段具有较小的超调量和较快的跟踪速度,并能够满足系统的稳态性能要求.在此基础上,结合反演法设计反馈控制律,保证系统的输出约束性能和轨迹跟踪精度.最后,基于李雅普诺夫稳定性定理证明所有闭环信号能够达到一致最终有界,并给出数值仿真对比验证所提出方法的有效性.     

Dynamic Output Feedback H∞ Control Problem for Linear Neutral Systems

This note presents the solvability conditions of the dynamic output feedback H_infin control problem for linear neutral systems with time- varying state delays in the delay-dependent case, where the delay is assumed to be time-varying continuous or differentiable uniformly bounded function, but no restriction on the derivative of the delay is needed, which means that the delay may be the fast time-varying function. An improved delay-dependent bounded real lemma (BRL) for a closed-loop system is established. Based on the obtained BRL, the dynamic output feedback H_infin controller is designed in terms of the linear matrix inequalities with inverse constraints. An iterative algorithm involving convex optimization methods is used to satisfy these constraints. The proposed results are illustrated in the examples.     

Control of nonlinear systems with time-varying output constraints

This paper presents control design for strict feedback nonlinear systems with time-varying output constraints. An asymmetric time-varying Barrier Lyapunov Function (BLF) is employed to ensure constraint satisfaction. By allowing the barriers to vary with the desired trajectory in time, the initial condition requirements are relaxed. Through a change of tracking error coordinates, we eliminate the explicit dependence of the BLF on time, thereby simplifying the analysis of constraint satisfaction. We show that asymptotic output tracking is achieved without violation of the output constraint, and also quantify the transient performance bound as a function of time that converges to zero. To handle parametric model uncertainty, we present an adaptive controller that ensures constraint satisfaction during the transient phase of online parameter adaptation. The performance of the proposed control is illustrated through a simulation example.     

Parametric control to a type of quasi-linear second-order systems via output feedback

This paper considers the design of output feedback control for a type of quasi-linear second-order systems with the time-varying coefficient matrices containing the state variables and a time-varying parameter vector. Based on the solution to a type of second-order generalised Sylvester matrix equations, general complete parameterisation of a quasi-linear output feedback controller is established with respect to the state variables, the time-varying parameter vector, the constant closed-loop system and another two groups of arbitrary parameters, and also for the left and right closed-loop eigenvectors matrices. With the proposed parametric output feedback control, the closed-loop system can be transformed into a constant linear system with desired eigenstructure. Finally, simulation results are provided to illustrate the convenience and effectiveness of application in the general spacecraft rendezvous problem.     

Approximation-based adaptive tracking control of nonlinear pure-feedback systems with time-varying output constraints

An adaptive neural network control problem of completely non-affine pure-feedback systems with a time-varying output constraint and external disturbances is investigated. For the controller design, we presents an appropriate Barrier Lyapunov Function (BLF) considering both the time-varying output constraint and the control direction nonlinearities induced from the implicit function theorem and mean value theorem. From an error transformation, the BLF dependent on the time-varying constraint is transformed into the explicitly time-independent BLF. Based on the explicitly time-independent BLF, an adaptive dynamic surface control scheme using the function approximation technique is designed to ensure both the constraint satisfaction and the desired tracking ability. It is shown that all signals in the closed-loop system are semi-globally uniformly ultimately bounded and the tracking error converges to an adjustable neighborhood of the origin while the time-varying output constraint is never violated.     

非线性时滞系统基于降阶观测器的反步镇定控制

针对一类状态未知的非线性严格反馈时滞系统, 本文提出了一种基于静态增益函数的输出反馈控制方案. 首先构造了降阶观测器以估计非线性系统的未知状态. 然后在Backstepping设计的每一步定义了具有控制增益函数 的新型Lyapunov-Krasovskii泛函以补偿未知时变时滞, 定义新的选择不唯一的连续控制增益函数以补偿非匹配项 以及Lyapunov-Krasovskii泛函补偿时滞时产生的非负项. 提出了一种无记忆输出反馈控制方案. 理论分析表明: 该 控制方案消除了未知时滞的影响, 保证了闭环系统所有信号的有界性, 并使系统实现渐近稳定. 最后仿真结果验证 了此控制方案的有效性.     

Fuzzy guaranteed cost control for nonlinear systems with time-varying delay

This paper focuses on the problem of guaranteed cost control for Takagi-Sugeno (T-S) fuzzy systems with time-varying delayed state. A linear quadratic cost function is considered as a performance index of the closed-loop fuzzy system. Then, the guaranteed cost control of the closed-loop fuzzy system is discussed, and the sufficient conditions are provided for the construction of a guaranteed cost controller via state feedback and observer-based output feedback. When these conditions, which are given in terms of the feasibility of linear matrix inequalities (LMIs), are satisfied, the designed state feedback controller and observer-based controller gain matrices can be obtained via a convex optimization problem. Two illustrative examples are provided to demonstrate the effectiveness of the approaches proposed in this paper.     

Output feedback receding horizon control of constrained systems

This paper considers output feedback control of linear discrete-time systems with convex state and input constraints which are subject to bounded state disturbances and output measurement errors. We show that the non-convex problem of finding a constraint admissible affine output feedback policy over a finite horizon, to be used in conjunction with a fixed linear state observer, can be converted to an equivalent convex problem. When used in the design of a time-varying robust receding horizon control law, we derive conditions under which the resulting closed-loop system is guaranteed to satisfy the system constraints for all time, given an initial state estimate and bound on the state estimation error. When the state estimation error bound matches the minimal robust positively invariant (mRPI) set for the system error dynamics, we show that this control law is time-invariant, but its calculation generally requires solution of an infinite-dimensional optimization problem. Finally, using an invariant outer approximation to the mRPI error set, we develop a time-invariant control law that can be computed by solving a finite-dimensional tractable optimization problem at each time step that guarantees that the closed-loop system satisfies the constraints for all time.     

异构集群系统分布式自适应输出时变编队跟踪控制

提出了一种能够解决高阶异构集群系统输出时变编队跟踪问题的控制方法. 集群系统中的智能体分为领导者和跟随者, 领导者和跟随者的动力学模型可以完全不同. 跟随者的输出在跟踪领导者输出的同时保持时变编队实现协同运动. 考虑了领导者存在已知或未知控制输入、领导者和跟随者均存在未知扰动、有向通信拓扑存在切换等多种因素并存的情况, 结合观测器理论、自适应控制理论和滑模控制理论设计了完全分布式的输出时变编队跟踪控制协议, 摆脱了对领导者控制输入上界值、与通信拓扑相关的拉普拉斯矩阵的特征值以及时变编队函数等全局信息的依赖. 利用Lyapunov理论证明了在有向拓扑切换条件下异构集群系统的闭环稳定性. 最后通过数值仿真对理论结果的有效性进行了验证.     

Tracking trajectories of feedforward systems

The objective of this paper is to solve the problem of tracking trajectories of feedforward systems. A family of time-varying state feedbacks that globally, uniformly, asymptotically and locally exponentially stabilize trajectories which are not necessarily periodic functions of time is exhibited. The control design is based on the construction of a strict Lyapunov function.