不确定非线性系统自适应动态事件触发输出反馈镇定

本文研究了一类不确定非线性系统的动态事件触发输出反馈镇定问题. 显著不同的是系统具有依赖于不可测状态的增长且增长率为输出的未知多项式. 尽管已有一些连续自适应控制器, 但需要巧妙融合非线性状态观测器、系统未知性的动态补偿以及非线性的抵御, 因此这些控制器具有一定的脆弱性, 不能平凡地拓展到不连续情形 (采样误差导致). 为此, 首先通过引入动态高增益和基于高增益的观测器来分别抵御未知增长率和重构系统不可测状态. 进而, 意识到静态事件触发机制的无效性, 通过引入动态事件触发机制, 成功设计出了事件触发输出反馈控制器, 确保了系统状态的全局有界性和收敛性. 数值仿真验证了所设计控制器的有效性.     

不确定非线性系统自适应动态事件触发输出反馈镇定（英文）

本文研究了一类不确定非线性系统的动态事件触发输出反馈镇定问题.显著不同的是系统具有依赖于不可测状态的增长且增长率为输出的未知多项式.尽管已有一些连续自适应控制器,但需要巧妙融合非线性状态观测器、系统未知性的动态补偿以及非线性的抵御,因此这些控制器具有一定的脆弱性,不能平凡地拓展到不连续情形(采样误差导致).为此,首先通过引入动态高增益和基于高增益的观测器来分别抵御未知增长率和重构系统不可测状态.进而,意识到静态事件触发机制的无效性,通过引入动态事件触发机制,成功设计出了事件触发输出反馈控制器,确保了系统状态的全局有界性和收敛性.数值仿真验证了所设计控制器的有效性.     

基于神经网络的一类非线性系统自适应输出跟踪

针对一类未知非线性系统,提出了一种输出反馈控制方法.首先,在假设系统状态已 知情况下设计状态反馈控制器,实现跟踪性能;然后,在系统状态不完全可测的情况下,通过 设计高增益观测器对系统的状态进行估计,实现输出反馈控制器设计,证明了所设计的输出 反馈控制器可以获得状态反馈控制器的性能.     

船舶轨迹跟踪半全局一致指数稳定观测控制器

针对仅位置和艏向可测量的动力定位船舶非线性输出反馈轨迹跟踪问题,在大地坐标系中,建立同时包含科里奥力向心力和非线性阻尼的非线性船舶操纵性模型.基于一种具有半全局一致指数稳定性的非线性观测器,提出船舶轨迹跟踪非线性 Backstepping 观测控制器,并应用 Lyapunov 方法证明该观测控制器具有半全局一致指数稳定性.理论分析和仿真结果均表明,通过调整控制器增益,系统误差指数收敛到零.     

基于自适应滑模观测器的不匹配非线性系统执行器故障重构

针对一类含有未知干扰的不匹配非线性Lipschitz系统,提出了基于自适应滑模观测器的执行器故障重构方法.首先引入辅助输出矩阵,使得辅助输出系统的观测器匹配条件得以满足,同时设计了高增益观测器实现对未知辅助输出的精确估计;然后针对辅助输出系统建立故障重构滑模观测器,设计了自适应律在线修正滑模控制器增益,考虑故障上界未知的前提下,提出了观测器状态估计误差稳定的存在定理,运用Schur补引理将观测器反馈增益矩阵设计方法转化为求解线性矩阵不等式约束优化问题,同时引入线性变换矩阵,在故障上界未知的前提下设计了滑模控制增益,使得输出估计误差收敛稳定,确保了滑模运动在有限时间内发生,在此基础上利用等效控制输出误差注入原理实现了执行器故障重构;最后通过仿真算例验证了本文方法的有效性.     

一类严格反馈系统变比例增益精确微分补偿控制

针对包含不确定函数和未知外部扰动的一类严格反馈型非线性系统,提出基于精确扰动观测器的变比例增益自适应模糊控制器.系统中的未知不确定函数由模糊逻辑系统在线逼近,同时将模糊逻辑系统的逼近误差和未知外部扰动定义为总扰动,利用精确扰动观测器进行精确微分补偿控制. 将非线性函数应用于设计可调节的输出反馈增益,有效消除系统的稳态误差,使得系统跟踪误差可以控制在零的任意小邻域内.最后,通过Lyapunov定理证明闭环系统中所有信号均是有界的.数值仿真表明了所提出方案的有效性.     

基于观测器的输出反馈电子节气门控制器设计

针对电子节气门系统的状态变量不完全可测量, 设计了一个基于观测器的输出反馈电子节气门控制系统. 该系统由一个估计不可测量状态的降阶观测器和一个非线性状态反馈控制器组成. 同时在控制器中引入了跟踪误差的积分项以抑制跟踪静差. 将建模误差和观测器误差等不确定性看作外部扰动, 在输入到状态稳定性(Input to state stability, ISS)理论框架下分析了跟踪误差系统的鲁棒性, 并据此给出了选择控制器参数的指导性原则.仿真及实验结果表明, 基于观测器的输出反馈控制器能够很好地实现电子节气门的跟踪控制.     

非线性系统的模糊自适应输出反馈控制

针对一类未知非线性系统,考虑系统状态不完全可测的情况,利用Lyapunov综合方法设计了一种基于高增益观测器的模糊鲁棒自适应输出反馈控制器,并证明在一定条件下,所设计的输出反馈控制器能获得状态反馈控制器的性能。     

参数未知的离散系统Q-学习优化状态估计与控制

控制系统的应用中存在状态不能直接测量或测量成本高的实际问题,给模型参数未知的系统完全利用状态数据学习最优控制器带来挑战性难题.为解决这一问题,首先构建具有状态观测器且系统矩阵中存在未知参数的离散线性增广系统,定义性能优化指标;然后基于分离定理、动态规划以及Q-学习方法,给出一种具有未知模型参数的非策略Q-学习算法,并设计近似最优观测器,得到完全利用可测量的系统输出和控制输入数据的非策略Q-学习算法,实现基于观测器状态反馈的系统优化控制策略,该算法的优点在于不要求系统模型参数全部已知,不要求系统状态直接可测,利用可测量数据实现指定性能指标的优化;最后,通过仿真实验验证所提出方法的有效性.     

MIMO非仿射非线性系统的自适应模糊控制

针对一类多输入多输出非仿射非线性系统,设计了一种自适应模糊H∞控制方案,该方案把自适应模糊控制和高增益观测器结合起来.利用多变量的隐函数定理,证明了非仿射系统控制器的存在性.通过设计高增益观测器,解决了系统的状态不可测量问题,实现系统的输出反馈控制,模糊自适应控制增强了系统在线逼近干扰及处理系统不确定的能力.仿真结果表明了控制方案的有效性及优越性.     

一类带不确定输入动态非线性系统的输出反馈鲁棒镇定

研究一类带不确定输入动态非线性系统的输出反馈鲁棒镇定问题.通过在高增益观测器引入新的设计参数,改进了通常的高增益反馈控制的设计方法.在输入动态满足零相对阶最小相位的假设下,基于非分离设计原则给出了动态输出反馈控制器的设计方法,所设计的控制器实现了对任意可允许不确定输入动态的全局鲁棒镇定.     

Cooperative Adaptive Fuzzy Output Feedback Control for Synchronization of Nonlinear Multi‐Agent Systems in the Presence of Input Saturation

This paper considers the leader‐following synchronization problem of nonlinear multi‐agent systems with unmeasurable states in the presence of input saturation. Each follower is governed by a class of strict‐feedback systems with unknown nonlinearities and the information of the leader can be accessed by only a small fraction of followers. An auxiliary system is introduced and its states are used to design the cooperative controllers for counteracting the effect of input saturation. By using fuzzy logic systems to approximate the unknown nonlinearities, local adaptive fuzzy observers are designed to estimate the unmeasurable states. Dynamic surface control (DSC) is employed to design distributed adaptive fuzzy output feedback controllers. The developed controllers guarantee that the outputs of all followers synchronize to that of the leader under directed communication graphs. Based on Lyapunov stability theory, it is proved that all signals in the closed‐loop systems are semiglobally uniformly ultimately bounded (SGUUB), and the tracking error converges to a small neighborhood of the origin. An example is provided to show the effectiveness of the proposed control approach.     

Adaptive output feedback tracking control of a nonholonomic mobile robot

An adaptive output feedback tracking controller for nonholonomic mobile robots is proposed to guarantee that the tracking errors are confined to an arbitrarily small ball. The major difficulties are caused by simultaneous existence of nonholonomic constraints, unknown system parameters and a quadratic term of unmeasurable states in the mobile robot dynamic system as well as their couplings. To overcome these difficulties, we propose a new adaptive control scheme including designing a new adaptive state feedback controller and two high-gain observers to estimate the unknown linear and angular velocities respectively. It is shown that the closed loop adaptive system is stable and the tracking errors are guaranteed to be within the pre-specified bounds which can be arbitrarily small. Simulation results also verify the effectiveness of the proposed scheme.     

Output feedback control of switched nonlinear systems using multiple Lyapunov functions

This work presents a hybrid nonlinear control methodology for a broad class of switched nonlinear systems with input constraints. The key feature of the proposed methodology is the integrated synthesis, via multiple Lyapunov functions, of “lower-level” bounded nonlinear feedback controllers together with “upper-level” switching laws that orchestrate the transitions between the constituent modes and their respective controllers. Both the state and output feedback control problems are addressed. Under the assumption of availability of full state measurements, a family of bounded nonlinear state feedback controllers are initially designed to enforce asymptotic stability for the individual closed-loop modes and provide an explicit characterization of the corresponding stability region for each mode. A set of switching laws are then designed to track the evolution of the state and orchestrate switching between the stability regions of the constituent modes in a way that guarantees asymptotic stability of the overall switched closed-loop system. When complete state measurements are unavailable, a family of output feedback controllers are synthesized, using a combination of bounded state feedback controllers, high-gain observers and appropriate saturation filters to enforce asymptotic stability for the individual closed-loop modes and provide an explicit characterization of the corresponding output feedback stability regions in terms of the input constraints and the observer gain. A different set of switching rules, based on the evolution of the state estimates generated by the observers, is designed to orchestrate stabilizing transitions between the output feedback stability regions of the constituent modes. The differences between the state and output feedback switching strategies, and their implications for the switching logic, are discussed and a chemical process example is used to demonstrate the proposed approach.     

Separation results for the stabilization of nonlinear systems using different high-gain observer designs

High-gain observers have been used in the design of output feedback controllers due to their ability to robustly estimate the unmeasured states while asymptotically attenuating disturbances. The available techniques for the design of high-gain observers can be classified into three groups: pole-placement algorithms, Riccati equation-based algorithms, and Lyapunov equation-based algorithms. In [1], we presented separation results for globally bounded stabilizing state feedback controllers when the high-gain observer is designed using pole-placement so as to create a closed-loop system with two-time-scale structure. In this paper, we show that the separation results of [1] hold for the other observer designs.     

Adaptive regulation of uncertain nonlinear systems by output feedback: A universal control approach

The problem of global state regulation via output feedback is investigated for uncertain nonlinear systems. The class of uncertain systems under consideration is assumed to be dominated by a bounding system which is linear growth in the unmeasurable states but can be a polynomial function of the system output, with unknown growth rates. To achieve global state regulation in the presence of parametric uncertainty, we propose a non-identifier based output feedback control scheme by employing the idea of universal control integrated with the design of a linear high-gain observer, whose gains are composed of two components, both of them are not constant and need to be dynamically updated. In particular, we explicitly design a universal output feedback controller which globally regulates all the states of the uncertain system while maintaining global boundedness of the closed-loop system.     

Observers and output feedback stabilising controllers for nonlinear strict-feedback systems with sampled observation

The design of observers and output feedback stabilising controllers for continuous-time strict-feedback systems with sampled observation is considered. First two types of observers are designed. One is a discrete-time semiglobal and practical reduced-order observer for the exact model and the other is a continuous-time semiglobal and practical full-order observer for continuous-time strict feedback systems with sampled observation. Then by combining the designed continuous-time observers and continuous-time state feedback laws that are continuous, zero at the origin, and uniformly globally asymptotically stabilise continuous-time systems, output feedback semiglobally practically uniformly asymptotically stabilising controllers are constructed. Numerical examples are given to illustrate the proposed design of observers and output feedback controllers.     

A simple adaptive PI controller for linear systems with constantdisturbances

It is known that an adaptive controller via high-gain output feedback can globally stabilize a class of minimum phase systems with relative degree one. However, exact output regulation is difficult for systems with disturbances. In this paper, we consider linear single-input/single-output (SISO) systems with unknown constant disturbances. We present a simple adaptive output feedback controller with an integral action and show that it can asymptotically stabilize those disturbed systems. The proposed PI type adaptive controller can also deal with the output tracking problem of a step reference     

Model‐free adaptive formation control for unknown multiinput‐multioutput nonlinear heterogeneous discrete‐time multiagent systems with bounded disturbance

Based on the model‐free adaptive control, the distributed formation control problem is investigated for a class of unknown heterogeneous nonlinear discrete‐time multiagent systems with bounded disturbance. Two equivalent data models to the unknown multiagent systems are established through the dynamic linearization technique considering the circumstances with measurable and unmeasurable disturbances. Based on the obtained data models, two distributed controllers are designed with only using the input/output and disturbance data of the neighbor agents system. The tracking error of the closed‐loop system driven by the proposed controllers is shown to be bounded by the contraction mapping principle and inductive methods. An example illustrates the effectiveness of the proposed two distributed controllers.     

Output synchronization control of ship replenishment operations: Theory and experiments

A leader–follower synchronization output feedback control scheme is presented for the ship replenishment problem where only positions are measured. No mathematical model of the leader ship is required, and the control scheme relies on nonlinear observers to estimate velocity and acceleration of all ships to realize the feedback control law. The scheme yields semi-global uniform ultimate boundedness of the closed-loop errors. The bound is a function of the main ship acceleration, and under the assumption of zero main ship acceleration the closed-loop errors are semi-globally exponentially converging. The results are verified through experiments on a model-scale ship.