一类非线性系统的模糊变结构控制

研究了一类非线性系统的模糊变结构控制问题，并给出了稳定性证明。通过将非线性系统化为多个精确T—S模型来建立非线性系统精确的T—S模糊模型，将模糊理论与成熟的线性变结构控制理论相结合设计一种模糊变结构控制器，用Lyapunov稳定性理论证明该控制器能确保模糊动态模型全局渐近稳定，从而使非线性系统稳定。仿真结果表明了该设计方法的有效性。     

模糊双曲正切模型的建模方法与控制器设计

首先提出一种新型模糊双曲正切模型.这种模型是一种本质非线性模型,可以很容 易由一组模糊规则基构成.这种模型也可以看作是线性模型的扩展,因此可以应用线性控制 理论的成果来设计控制器.同时给出了基于此模型的两种控制器的设计方法及仿真实例.     

基于模糊双曲正切模型的一类稳定的模糊控制器设计

提出一种基于模糊双曲正切模型的模糊控制器的设计方法：首先针对模糊模型的每一条模糊规则（即每个子系统）根据专家经验设计模糊控制器，然后利用对角稳定性的概念给出了全局系统稳定的一个充分条件。     

多模型切换系统H_∞鲁棒控制器的设计与应用

基于H∞控制理论以及切换系统稳定性理论,对于多输入多输出(MIMO)多模型切换控制系统,提出了一种可以有效抑制抖动和改善瞬态响应性能的鲁棒镇定控制器设计方法.通过引入PI控制思想,根据模型跟踪方法设计了增广状态反馈控制器,并将控制器设计问题转化为方便求解的线性矩阵不等式(LMI).该方法的最大优点是可以很方便的保证多模型切换系统的全局稳定性,同时使得设计的控制器具有较强的鲁棒性.将本文提出的方法应用到某型BTT导弹自动驾驶仪设计中,仿真结果证明了此方法的有效性和优越性.     

SOPDT对象的预测PID控制及稳定性分析

提出了基于二阶非振荡及振荡加纯滞后的预测PID控制器的结构形式。这种控制器既具有PID控制器的优点；简单的结构形式、良好的鲁棒性和可靠性，又具有预测的功能；即可以根据以前的控制作用来预测以后的控制作用。通过仿真表明：在干扰、噪音存在和模型失配的情况下，预测PID控制器具有良好的控制性能，特别适合大纯滞后系统的控制。同时运用Monte-Carlo方法分析了其鲁棒稳定性，结果表明：它是一种值得在实际工程中推广应用的新型控制器。     

一种新的云模型控制器设计

首先提出一种新型的云模型控制器结构模型．这种结构模型是一种本质非线性模型，可以很容易由一组不确定性推理规则构成．文中分析了云模型的非线性映射特性，同时给出了基于此结构模型的智能控制器的设计方法及仿真实例．     

基于模糊控制策略的车辆主动悬架研究

建立了车辆整车7自由度模型的主动悬架控制的系统状态方程模型,设计了两种模糊控制策略,方法一针对整车模型,采用一种控制方法,方法二针对整车模型的运动方式,设计不同的模糊控制器,垂直振动模糊控制器,俯仰振动模糊控制器,侧倾振动模糊控制器和逻辑控制器,仿真结果表明,所设计的模糊控制器对提高车辆的舒适性与操纵稳定性有较好的效果.     

基于自适应和神经动力学的轮式移动机器人路径跟踪控制(英文)

本文提出一种自适应和神经动力学相结合的轮式移动机器人路径跟踪控制方法.首先,设计运动学控制器用来获得机器人期望速度;其次,考虑机器人动力学模型参数的不确定性,利用模型参考自适应方法来设计动力学控制规律,使得机器人实际速度渐近逼近期望值;再次,为克服速度和力矩的跳变,加入神经动力学模型对控制器进行优化,并且通过Lypunov理论来证明整个控制系统的稳定性;最后仿真结果表明该控制方法的有效性.     

模糊聚类辨识算法

采用模糊输入聚类算法来辨识系统的模型,通过两个模糊聚类准则函数求得聚类中心和模糊规则数,然后求出各个子窨支态模型,再用隶属函数光滑地把他们连接成一个全局动态模糊模型,这种模型可以转化成状态空间模型,从而进行控制器的设计和稳定性分析。     

一类非线性系统的建模、辨识与控制研究

提出一种新型的双曲正切模型,这种模型是一种模糊模型,可以很容易由几条模型规则得出,同时此模型也是一和中神经网络模型,因此模型参数可以通过网络学习获得,而且这种模型可以看作是线性模型的扩展,因此许多线性控制理论的结果可用来分析闭环系统稳定性。最后给出了基于此模型的稳定H∞控制器的设计方法。仿真结果表明这了种模型的有效笥及其控制器设计方法的优良性能。     

具有时延的网络控制系统控制器设计

针对一类存在随机时延的网络控制系统,传感器采用时间驱动,控制器和执行器采用事件驱动,提出了一种新的具有随机时延的网络控制系统的建模方法-离散模糊T-S模型,在此模型的基础上应用并行分布补偿（PDC）原理设计了模糊控制器。应用Lyapunov定理和线性矩阵不等式（LMI）方法,研究了系统的稳定性问题,给出基于LMI的状态反馈模糊控制器的设计方法。通过仿真实例验证控制方法能够保证系统稳定。     

具有丢包的非线性奇异系统的网络脉冲控制器设计

针对给定的一类非线性奇异系统,设计了基于数据丢包的网络脉冲控制器.首先建立了非线性奇异网络脉冲控制系统的数学模型;然后根据李亚普诺夫稳定性理论,分别考虑系统在连续状态和脉冲时刻的指数稳定性条件,给出了基于数据丢包的网络脉冲控制器的设计方法,使网络脉冲控制器能够保证具有数据丢包的非线性奇异系统实现指数稳定;最后,以洛伦兹混沌系统为例表明了控制器设计方法的正确性.     

具有通信约束的网络控制系统动态调度与H∞控制协同设计

针对一类具有通信约束的随机时延网络控制系统,提出一种基于试一次丢弃(try-once-discard,TOD)动态调度策略与鲁棒H∞控制器协同设计的方法.考虑通信约束和随机时延的影响,将系统建模为一类具有参数不确定性的离散切换系统,并采用切换系统和Lyapunov稳定性理论,给出了TOD调度策略下使闭环系统渐近稳定的鲁棒H∞控制器设计方法.最后通过仿真验证了方法的有效性.     

Analysis and design of fuzzy control systems using dynamicfuzzy-state space models

A discrete-time fuzzy control system which is composed of a dynamic fuzzy model and a fuzzy-state feedback controller is proposed. Stability of the fuzzy control system is discussed and two sufficient conditions to guarantee the stability of the system are given in terms of uncertain linear system theory. An algorithm is developed to check the stability condition. The controller design method is divided into two procedures, one is to get the state feedback matrix by linear system theory in every local rule map; the other is to determine conditions of global stability by using a nonlinear analysis method. Two examples are used to show the design method     

Characteristic model based adaptive controller design and analysis for a class of SISO systems一类SISO系统基于特征模型的极点配置自适应控制设计与分析

The design of an adaptive controller and stability analysis of the corresponding closed loop system are discussed for a class of SISO systems based on the characteristic model method. The obtained characteristic model is a second-order slow time-varying linear system with a compress mapping function for the system modeling error. The pole placement method is used to design the controller, and sufficient conditions for the stability of the closed loop system are obtained based on the robust control theory of slow time-varying systems with perturbations. The effectiveness of the proposed method is illustrated by two numerical examples.     

Dynamic switching based fuzzy control strategy for a class of distributed parameter system

In this work, a dynamic switching based fuzzy controller combined with spectral method is proposed to control a class of nonlinear distributed parameter systems (DPSs). Spectral method can transform infinite-dimensional DPS into finite ordinary differential equations (ODEs). A dynamic switching based fuzzy controller is constructed to track reference values for the multi-inputs multi-outputs (MIMO) ODEs. Only a traditional fuzzy logic system (FLS) and a rule base are used in the controller, and membership functions (MFs) for different ODEs are adjusted by scaling factors. Analytical models of the dynamic switching based fuzzy controller are deduced to design the scaling factors and analyze stability of the control system. In order to obtain a good control performance, particle swarm optimization (PSO) is adopted to design the scaling factors. Moreover, stability of fuzzy control system is analyzed by using the analytical models, definition of the stability and Lyapunov stability theory. Finally, a nonlinear rod catalytic reaction process is used as an illustrated example for demonstration. The simulation results show that performance of proposed dynamic switching based fuzzy control strategy is better than a multi-variable fuzzy logic controller.     

A robust stabilization problem of fuzzy control systems and itsapplication to backing up control of a truck-trailer

A robust stabilization problem for fuzzy systems is discussed in accordance with the definition of stability in the sense of Lyapunov. We consider two design problems: nonrobust controller design and robust controller design. The former is a design problem for fuzzy systems with no premise parameter uncertainty. The latter is a design problem for fuzzy systems with premise parameter uncertainty. To realize two design problems, we derive four stability conditions from a basic stability condition proposed by Tanaka and Sugeno: nonrobust condition, weak nonrobust condition, robust condition, and weak robust condition. We introduce concept of robust stability for fuzzy control systems with premise parameter uncertainty from the weak robust condition. To introduce robust stability, admissible region and variation region, which correspond to stability margin in the ordinary control theory, are defined. Furthermore, we develop a control system for backing up a computer simulated truck-trailer which is nonlinear and unstable. By approximating the truck-trailer by a fuzzy system with premise parameter uncertainty and by using concept of robust stability, we design a fuzzy controller which guarantees stability of the control system under a condition. The simulation results show that the designed fuzzy controller smoothly achieves backing up control of the truck-trailer from all initial positions     

Switching fuzzy controller design based on switching Lyapunov function for a class of nonlinear systems

This paper presents a switching fuzzy controller design for a class of nonlinear systems. A switching fuzzy model is employed to represent the dynamics of a nonlinear system. In our previous papers, we proposed the switching fuzzy model and a switching Lyapunov function and derived stability conditions for open-loop systems. In this paper, we design a switching fuzzy controller. We firstly show that switching fuzzy controller design conditions based on the switching Lyapunov function are given in terms of bilinear matrix inequalities, which is difficult to design the controller numerically. Then, we propose a new controller design approach utilizing an augmented system. By introducing the augmented system which consists of the switching fuzzy model and a stable linear system, the controller design conditions based on the switching Lyapunov function are given in terms of linear matrix inequalities (LMIs). Therefore, we can effectively design the switching fuzzy controller via LMI-based approach. A design example illustrates the utility of this approach. Moreover, we show that the approach proposed in this paper is available in the research area of piecewise linear control.     

输入饱和与姿态受限的四旋翼无人机反步姿态控制

本文针对四旋翼无人机研究了鲁棒反步姿态控制策略.由于四旋翼无人机结构复杂,其非线性数学模型难以精确建立,因此在控制器设计过程中需要综合考虑模型不确定性、未知外部干扰、输入饱和以及姿态受限等因素.针对模型中的不确定项,使用神经网络进行逼近;对于外部未知干扰,使用非线性干扰观测器进行补偿;使用双曲正切函数逼近饱和函数,解决输入饱和问题;同时使用界限Lyapunov函数设计控制器,确保姿态满足限制条件.最后,设计四旋翼无人机反步姿态控制器,并根据Lyapunov稳定性定理证明了闭环控制系统的有界稳定.仿真结果表明了所研究控制方法的有效性.     

计及铁损时电动汽车用感应电机的Hamilton建模及无源控制

针对电动汽车电驱动系统的非线性特点,采用端口受控Hamilton系统理论与无源性控制原理研究了计及铁损的电动汽车用感应电机系统的建模和控制问题.首先,选取系统的总能量作为Hamilton函数,推导出考虑铁损的感应电机端口受控Hamilton模型,然后利用系统的互联和阻尼配置以及能量成形对闭环电动汽车电驱动系统进行无源控制,并分析了闭环系统的稳定性.由于闭环系统的Hamilton函数可作为Lyapunov存储函数,从而使控制器设计和稳定性分析更容易,控制器更加简单和易于实现.仿真结果验证了新控制策略的有效和快速性.