基于非脆弱控制器设计的不确定模糊系统稳定性研究

研究不确定动态模糊系统的稳定性问题.提出一类不确定T-S动态模糊系统的非脆弱控制问题,并进行了控制器设计.首先给出不确定T-S动态模糊系统的模型;然后利用Lyapunov函数方法,研究连续不确定动态模糊系统的非脆弱控制器设计,得到基于LMI的不确定动态模糊系统的全局渐近稳定性条件.通过对一级倒立摆的不确定模糊非脆弱控制器设计的实例,表明了设计方法的可行性和有效性.     

时滞状态反馈下离散时滞系统H∞控制器失效时间分析

针对控制器存在短暂失效的情形,研究一类时变时滞离散系统在时滞状态反馈控制下的H_∞控制器失效时间分析问题.本文的目标是寻求控制器正常工作时间与失效时间的比率应满足的条件以确保系统指数镇定且具有加权l_2增益.为此,基于切换的思想,所考虑的系统被转化为一个仅含有两个子系统的切换系统,其中一个子系统是控制器失效时的不稳定子系统,另一个是控制器未失效时的稳定子系统.通过使用多Lyapunov函数及平均驻留时间方法,给出问题可解的充分条件及时滞状态反馈H_∞切换控制器的设计方案.仿真算例表明了所得结果的有效性.     

Robustness analysis and synthesis of SISO systems under both plant and controller perturbations

In this paper, we consider the robustness analysis and synthesis problem for a class of control systems under both plant and controller perturbations. Necessary and sufficient conditions are given for robust stability of SISO systems subject to additive norm-bounded perturbations. Linear matrix inequality (LMI)-based controller design method is presented. Robust stability of systems with both plant and controller perturbations, and stability analysis of a class of multilinear disc polynomials are unified in the same framework, and can be solved by computing the largest norm of a second-order matrix along the imaginary axis.     

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.     

非线性大系统的分散线性化与分散控制

将非线性控制系统的精确线性化方法应用于非线性大系统,提出了非线性大系统 的分散线性化方法,并得到了非线性系统可分散线性化的充要条件.按照这个方法,可将难度 较大的一类非线性大系统分散控制器的设计转化为易于处理的线性大系统分散控制器的设 计.在得到该线性大系统的分散控制器后,可通过分散坐标变换的逆变换将线性大系统的控 制器变换为原非线性大系统的控制器.同时,控制器的分散性保持不变.该方法明显地降低了 该类非线性大系统分散控制器的设计难度.     

A novel fused neural network controller for lateral control of autonomous vehicles

We present a novel fused feed-forward neural network controller inspired by the notion of task decomposition principle. The controller is structurally simple and can be applied to a class of control systems that their control requires manipulation of two input variables. The benchmark problem of inverted pendulum is such example that its control requires availability of the angle as well as the displacement. We demonstrate that the lateral control of autonomous vehicles belongs to this class of systems and successfully apply the proposed controller to this problem. The parameters of the controller are encoded into real value chromosomes for genetic algorithm (GA) optimization. The neural network controller contains three neurons and six connection weights implying a small search space implying faster optimization time due to few controller parameters. The controller is also tested on two benchmark control problems of inverted pendulum and the ball-and-beam system. In particular, we apply the controller to lateral control of a prototype semi-autonomous vehicle. Simulation results suggest a good performance for all the tested systems. To demonstrate the robustness of the controller, we conduct Monte-Carlo evaluations when the system is subjected to random parameter uncertainty. Finally experimental studies on the lateral control of a prototype autonomous vehicle with different speed of operation are included. The simulation and experimental studies suggest the feasibility of this controller for numerous applications.     

一类高阶非线性不确定系统自适应稳定控制

研究了一类高阶非线性不确定性系统的自适应稳定控制设计问题.因该系统的非线性程度高,其控制系数不等同、符号已知、但数值未知,故在此之前其稳定控制设计问题没有得到解决.本文应用自适应技术,结合设计参数的适当选取,从而得到了设计该类非线性系统状态反馈稳定控制器的新方法,并基于反推技术,给出了稳定控制器的设计步骤.所设计的状态反馈控制器使得闭环系统的状态全局渐近收敛于零,其余闭环信号一致有界.最后通过一个仿真例子说明了控制设计方法的有效性.     

Approximation-based adaptive fuzzy control for a class of non-strict-feedback stochastic nonlinear systems

This paper considers the problem of adaptive fuzzy control of a class of single-input/single-output （SISO） nonlinear stochastic systems in non-strict-feedback form. Fuzzy logic systems are used to approximate the uncertain nonlinearities and backstepping technique is utilized to construct an adaptive fuzzy controller. The proposed controller guarantees that all the signals in the resulting closed-loop system are bounded in probability. The main contribution of this note lies in providing a control strategy for a class of nonlinear systems in non- strict-feedback form. Simulation result is used to test the effectiveness of the suggested approach.     

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.     

一类控制系数未知但等同高阶非线性系统的稳定控制设计

本文研究了一类控制系数未知但等同高阶非线性系统的状态反馈稳定控制设计问题. 尽管该类系统具有不确定性, 即控制系数未知,但本文没有采用自适应技术, 而是通过选取适当的设计参数, 从而得到了设计该类非线性系统稳定控制器的新方法, 并基于反推技术, 给出了稳定控制器的设计步骤. 所设计的状态反馈控制器使得闭环系统全局渐近稳定, 并保持在原点的平衡性.     

Global output feedback tracking for nonlinear systems in generalized output-feedback canonical form

A global output feedback dynamic compensator is proposed for stabilization and tracking of a class of systems that are globally diffeomorphic into systems which are in generalized output-feedback canonical form. This form includes as special cases the standard output-feedback canonical form and various other forms considered previously in the literature. Output-dependent nonlinearities are allowed to enter both additively and multiplicatively. Under the assumption that a constant matrix can be found to achieve a certain property, it is shown that a reduced-order observer and a backstepping controller can be designed to achieve asymptotic tracking. For the special case of linear systems, the designed dynamic controller reduces to the standard reduced-order observer and linear controller. This is the first global output-feedback tracking results for this class of systems.     

Linear adaptive control of a class of SISO nonaffine nonlinear systems

This paper addresses the problem of linear adaptive control for a class of uncertain continuous-time single-input single-output (SISO) nonaffine nonlinear dynamic systems. Using the implicit function theory, the existence of an ideal controller which can achieve control objectives is firstly demonstrated. However, this ideal controller cannot be known and computed even if the system model is well known. The aim of our work is to construct this unknown ideal controller using a simple linear controller with the free parameters updated online by a stable adaptation mechanism designed to minimise the error between the unknown ideal controller and the used linear controller. Since the mathematical model of the system is assumed unknown in this work, the proposed control scheme can be regarded as a simple model free controller for the studied class of nonaffine systems. We prove that the closed-loop system is stable and all the signals are bounded. An application of the proposed linear adaptive controller for a nonaffine system is illustrated through the simulation results to demonstrate the effectiveness of the proposed control scheme.     

Passive actuator fault tolerant control for a class of MIMO nonlinear systems with uncertainties

Fault tolerant control of affine class of multi-input multi-output (MIMO) nonlinear systems has not received considerable attention of researchers compared to other class of nonlinear systems. Therefore, this paper proposes an adaptive passive fault tolerant control method for actuator faults of affine class of MIMO nonlinear systems with uncertainties using sliding mode control . The actuator fault is represented by a multiplicative factor of the control signal which reflects the loss of actuator effectiveness. The design of the controller is based on the assumption that the maximum loss level of the actuator effectiveness is known. Furthermore, since the proposed controller is adaptive, it does not require any a-priori knowledge of the uncertainty bounds. The closed-loop stability conditions of the controller are derived based on Lyapunov theory. The effectiveness of the proposed controller is demonstrated considering two examples: a two degree of freedom helicopter and a two-link robot manipulator and has been found to be satisfactory.     

Decentralized adaptive control of a class of large-scaleinterconnected nonlinear systems

Decentralized adaptive control design for a class of large-scale interconnected nonlinear systems with unknown interconnections is considered. The motivation behind this work is to develop decentralized control for a class of large-scale systems which do not satisfy the matching condition requirement. To this end, large-scale nonlinear systems transformable to the decentralized strict feedback form are considered. Coordinate-free geometric conditions under which any general interconnected nonlinear system can be transformed to this form are obtained. The interconnections are assumed to be bounded by polynomial-type nonlinearities. Global stability and asymptotic regulation are established using classical Lyapunov techniques. The controller is shown to maintain robustness for a wide class of systems obtained by perturbation in the dynamics of the original system. Furthermore, appending additional subsystems does not require controller redesign for the original subsystems. Finally, the scheme is extended to the model reference tracking problem when global uniform boundedness of the tracking error to a compact set is established     

A unified approach to LMI-based reduced order self-scheduling control synthesis

We consider a reduced order controller synthesis for a general class of control specifications for linear parameter-varying (LPV) systems, when some of state variables are exactly available. The class is defined in an abstract manner so that it uniformly deals with many significant specifications. A necessary and sufficient condition for the existence of a reduced order controller is given in terms of linear matrix inequalities (LMIs). We also show that the order of the controller can be reduced by the number of the state variables exactly available in the measurements. Moreover, in the case of linear time invariant (LTI) systems, a parameterization of all desirable reduced order LTI controllers is given by means of solutions of LMIs. The results in this paper generalize the class of control specifications in which a reduced order controller exists, making it possible to synthesize a reduced order controller based on LMIs for multi-objective control specifications. Furthermore, these results uniformly describe and generalize the existing results on synthesis of a constant state and a full order output feedback controller for LTI and LPV systems such that the specification is given by the existence of a constant positive definite matrix.     

State Feedback Control of Uncertain Networked Control Systems With Random Time Delays

This note investigates the stabilization problem for a class of linear uncertain networked control systems with random communication time delays. Both sensor-to-controller and controller-to-actuator random-network-induced delays are considered. Markov processes are used to model these random-network-induced delays. Based on the Lyapunov-Razumikhin method a mode-dependent state feedback controller is proposed to stabilize this class of systems. The existence of such a controller is given in terms of the solvability of bilinear matrix inequalities, which are to be solved by a newly proposed algorithm. A numerical example is used to illustrate the validity of the design methodology.     

Robust backstepping control for a class of time delayed systems

In this note, the problem of robust output feedback control for a class of nonlinear time delayed systems is considered. The systems considered are in strict-feedback form. State observer is first designed, then based on the observed states the controller is designed via backstepping method. Both the designed observer and controller are independent of the time delays. Based on Lyapunov stability theory, we prove that the constructed controller can render the closed-loop system asymptotically stable. Simulation results further verify the effectiveness of the proposed approach.     

Control of a Class of Underactuated Mechanical Systems Using Sliding Modes

In this paper, we present a sliding mode control algorithm to robustly stabilize a class of underactuated mechanical systems that are not linearly controllable and violate Brockett's necessary condition for smooth asymptotic stabilization of the equilibrium, with parametric uncertainties. In defining the class of systems, a few simplifying assumptions are made on the structure of the dynamics; in particular, the damping forces are assumed to be linear in velocities. We first propose a switching surface design for this class of systems, and subsequently, a switched algorithm to reach this surface in finite time using conventional and higher order sliding mode controllers. The stability of the closed-loop system is investigated with an undefined relative degree of the sliding functions. The controller gains are designed such that the controller stabilizes the actual system with parametric uncertainty. The proposed control algorithm is applied to two benchmark problems: a mobile robot and an underactuated underwater vehicle. Simulation results are presented to validate the proposed scheme.     

Control of a class of nonlinear discrete-time systems usingmultilayer neural networks

A multilayer neural-network (NN) controller is designed to deliver a desired tracking performance for the control of a class of unknown nonlinear systems in discrete time where the system nonlinearities do not satisfy a matching condition. Using the Lyapunov approach, the uniform ultimate boundedness of the tracking error and the NN weight estimates are shown by using a novel weight updates. Further, a rigorous procedure is provided from this analysis to select the NN controller parameters. The resulting structure consists of several NN function approximation inner loops and an outer proportional derivative tracking loop. Simulation results are then carried out to justify the theoretical conclusions. The net result is the design and development of an NN controller for strict-feedback class of nonlinear discrete-time systems.     

Effects of controller dynamics on the stability of a class of optimal control systems†

In this paper, the effects of controller dynamics on the stability characteristics of a class of multivariate optimal control systems are investigated. The results of this investigation indicate that the asymptotic stability of systems of this class may well be lost because of the practical impossibility of implementing control laws derived on the basis of the classical optimal control theory of Kalman (1960),