对稳定的模糊自适应控制方案的研究与改进

对美国加州伯克利大学Li-Xin Wang1993年提出的模糊自适应控制方案的稳定性条件进行了研究,证明了两个新的结论:1)原来的监督控制可以取消;2)渐近稳定的条件可由w(t)平方可积放宽到w(t)→0.在此基础上,提出并证明了一种模糊自适应控制的新方案,它能在任何情况下保证闭环渐近稳定,并在一定条件下还能保证参数收敛.对一阶不稳定与二阶混沌两个控制对象的仿真实验结果表明,新方案的控制效果比Wang的方案有很大提高.     

基于观测器非线性不确定系统的自适应模糊控制

针对一类单输入单输出不确定非线性系统,提出一种稳定的自适应模糊控制方法,该方法不需要系统状态可测的条件,而是通过设计模糊状态观测器来估计系统的状态,证明了所提出的控制方法不但能使闭环系统稳定,而且输出误差可取得H∞跟踪控制性能,仿真结果进一步验证了该控制算法的实用性和有效性。     

Adaptive fuzzy observer backstepping control for a class of uncertain nonlinear systems with unknown time-delay

In this paper, a new adaptive fuzzy backstepping control approach is developed for a class of nonlinear systems with unknown time-delay and unmeasured states. Using fuzzy logic systems to approximate the unknown nonlinear functions, a fuzzy state observer is designed for estimating the unmeasured states. On the basis of the state observer and applying the backstepping technique, an adaptive fuzzy observer control approach is developed. The main features of the proposed adaptive fuzzy control approach not only guarantees that all the signals of the closed-loop system are semiglobally uniformly ultimately bounded, but also contain less adaptation parameters to be updated on-line. Finally, simulation results are provided to show the effectiveness of the proposed approach.     

一类确定性多变量非线性系统的自适应控制

本文研究了可用确定性多变量Hammerstein模型描述的一类多变量非线性系统的自适应控制,基于对一步最优控制律所产生的闭环系统的稳定性条件的分析,提出了一种适用于线性部分为具有任意关联矩阵的非最小相位系统的简单次优控制律及相应的直接自适应控制算法,并证明了算法的全局收敛性.     

一类非线性系统的自适应观测器

This paper investigates the means to design the ob- server for a class of nonlinear systems with Lipschitz conditions and unknown parameters.A new design approach of full-order state adaptive observer is proposed.The constructed observer could guarantee the error of state and the error of parameter estimation to asymptotically converge to zero.Furthermore,a numerical example is provided to verify the effectiveness of the observer.     

一类非线性系统的自适应观测器

研究一类非线性系统的观测器设计方法, 这类非线性系统满足 Lipschitz 条件且含有未知参数. 提出了全状态自适应观测器设计的新方法. 构造的观测器能保证状态估计误差及参数估计误差渐近收敛于零. 文中给出数值例验证了观测器的有效性.     

The simplest fuzzy controllers using different inference methods are different nonlinear proportional-integral controllers with variable gains

The author analytically proves that the simplest fuzzy controllers using different inference methods are different nonlinear proportional-integral (PI) controllers with proportional-gains and integral-gains changing with inputs of the controllers. The inference methods involved are Mamdani's minimum inference method, Larsen's product inference method, the drastic product inference method and the bounded product inference method. Configuration of the fuzzy controllers is minimal, which includes two input fuzzy sets, three output fuzzy sets, four control rules, Zadeh fuzzy logic AND, Lukasiewicz fuzzy logic OR and a center of gravity defuzzification algorithm. After analytically investigating properties of the nonlinear PI controllers, the author reveals that the bounded product inference method is inappropriate for the control purpose while the other three inference methods are appropriate. Dynamic and static control behaviors of the fuzzy controllers with the appropriate inference methods are analytically compared with each other, and are also compared with those of the linear PI controller. Finally, it is analytically proven that the fuzzy control systems have the same local stability at the equilibrium point as the corresponding linear PI control system does.     

Robust adaptive fuzzy backstepping output feedback tracking control for nonlinear system with dynamic uncertainties

In this paper, an adaptive fuzzy output feedback control approach based on backstepping design is proposed for a class of SISO strict feedback nonlinear systems with unmeasured states, nonlinear uncertainties, unmodeled dynamics, and dynamical disturbances. Fuzzy logic systems are employed to approximate the nonlinear uncertainties, and an adaptive fuzzy state observer is designed for the states estimation. By combining backstepping technique with the fuzzy adaptive control approach, a stable adaptive fuzzy...     

State observer-based adaptive fuzzy output-feedback control for a class of uncertain nonlinear systems

This paper aims to develop state observer-based adaptive fuzzy control techniques for controlling a class of uncertain nonlinear systems with bounded external disturbances. An adaptive fuzzy observer is proposed to estimate the system state variables. It is shown that the observation errors obtained from the observer are uniformly ultimately bounded. Applying the estimated system state for design of an output-feedback controller, the uniformly ultimate boundedness of the tracking errors for the resulting closed-loop system can be guaranteed. A typical robot arm system is employed in our simulation studies, and the results demonstrate the usefulness and effectiveness of the proposed techniques for controlling nonlinear systems with bounded external disturbances.     

Adaptive fuzzy decentralized control for nonlinear large-scale systems based on high-gain observer

An adaptive fuzzy decentralized backstepping output-feedback control approach is proposed for a class of nonlinear large-scale systems with completely unknown functions,the interconnections mismatched in control inputs,and without the measurements of the states.Fuzzy logic systems are employed to approximate the unknown nonlinear functions,and an adaptive high-gain observer is developed to estimate the unmeasured states.Using the designed high-gain observer,and combining the fuzzy adaptive control theory with backstepping approach,an adaptive fuzzy decentralized backstepping output-feedback control scheme is developed.It is proved that the proposed control approach can guarantee that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded(SUUB),and that the observer errors and the tracking errors converge to a small neighborhood of the origin by appropriate choice of the design parameters.Finally,a simulation example is provided to show the eectiveness of the proposed approach.