A novel Takagi-Sugeno-based robust adaptive fuzzy sliding-mode controller

In this paper, a nonlinear dynamic system is first approximated by N fuzzy-based linear state-space subsystems. To track a trajectory dominant by a specific frequency, the reference models with desired amplitude and phase features are established by the same fuzzy sets of the system rule. Similarly, the same fuzzy sets of the system rule are employed to design robust fuzzy sliding-mode control (RFSMC) and adaptive fuzzy sliding-mode control (AFSMC). The difference between RFSMC and AFSMC is that AFSMC contains an updating law to learn system uncertainties and then an extra compensation is designed. It is different from the most previous papers to learn the whole nonlinear functions. As the norm of the sliding surface is inside of a defined set, the updating law starts; simultaneously, as it is outside of the other set, the updating law stops. For the purpose of smoothing the possibility of discontinuous control input, a transition between RFSMC and AFSMC is also assigned. Under the circumstances, the proposed control [robust adaptive fuzzy sliding-mode control (RAFSMC)] can automatically tune as a RFSMC or an AFSMC; then the advantages coming from the RFSMC and AFSMC are obtained. Finally, the stabilities of the overall system of RFSMC, AFSMC, and RAFSMC are verified by Lyapunov stability theory. The compared simulations among RFSMC, AFSMC, and RAFSMC are also carried out to confirm the usefulness of the proposed control scheme.     

基于模糊动态模型的多变量系统模糊控制

采用模糊动态模型对多变量复杂非线性系统进行模糊控制.首先针对局部线性动态模 型设计状态反馈控制器,然后利用模糊推理确定整个系统的控制;在一系列局部模型通过模糊 隶属函数连接得到的连续的全局模型中,全面考虑其它关联子系统对标称线性系统的摄动,并 利用大系统分散控制关联稳定性的概念和方法,得到了闭环模糊系统稳定的充分条件.仿真例 子验证了该设计方法的正确性.     

Universal Lyapunov-type fuzzy controllers

A new strategy for stabilization of one-dimensional dynamic objects with a priori unknown mathematical model is presented. For a given control law, the stabilization strategy consists in determination of the times when the control law changes and its reversal at these times, on the basis of a fuzzy knowledge base that takes into account the nature of the variation of the “distance” relative to an equilibrium point. The derivatives of the “distance” and such concepts as “approach” and “departure” are also used. Aggregation of the input phase variables and the use of generalized concepts of the theory of Lyapunov stability make it possible to construct a sufficiently general and, at the same time, simple fuzzy regulator with two aggregated inputs and piecewise-continuous output signals.     

模糊自适应Smith预估器在温室控制中的应用研究

该文以蒸汽管道为对象,采用机理分析法对温室加温时的温度对象进行分析,得到室内温度模型和蒸汽管道模型。采用模糊控制技术,组成温室温度的模糊控制系统。针对温室系统大延时滞后的特点,采用自适应Sm ith预估器对温室模糊控制系统进行补偿,组成模糊自适应Sm ith预估控制系统。运用MATLAB软件的S imu link建立温室控制系统的仿真模型,并分别用常规模糊控制技术和模糊自适应Sm ith预估控制技术对温室加温进行仿真试验,仿真结果表明在温室加温的模糊控制系统中增加自适应Sm ith预估器后,系统具有更强的适应能力,系统的动态特性都有了较大的改善。     

DF控制推理模型的研究

针对控制系统中对象的模糊性和动态性,基于动态模糊集(Dynamic Fuzzy Sets)及动态模糊逻辑(Dynamic FuzzyLogic)系统理论,给出DF控制推理模型的相关概念,如DF向量、DF语言变量、DF语言规则和DF蕴涵关系等,并在此基础上探讨基于DF语言规则的DF推理方法,最后通过实例说明这些概念和方法的应用。     

非线性离散时间系统的自适应模糊补偿控制

针对一类非线性离散时间系统,提出一种自适应模糊逻辑补偿控制方案.控制律由跟踪控制律和逼近误差补偿控制律两部分组成,利用模糊逻辑系统对系统参数扰动和外界干扰进行自适应补偿,由模糊滑模控制律实现对模糊逻辑系统逼近误差的进一步补偿.所设计的控制器可保证闭环系统一致最终有界.将该控制器用于月球探测车动态转向系统中,仿真结果表明了该方法的有效性.     

DF控制器的设计方法研究

基于动态模糊集（Dynamic Fuzzy Sets）理论和动态模糊控制推理模型的相关概念,提出了一种DF控制器的设计方法,给出了DF控制器结构,探讨了DF控制规则库、DF控制推理计算、DF化以及清晰化方法,解决了控制过程中的动态模糊性问题,更符合具有动态模糊性特点的控制系统的控制规律,并通过具体的应用实例体现了此设计方法的有效性和可操作性.     

电弧炉的反步自适应模糊控制

电弧炉是具有三相强耦合、高度非线性和不确定性的复杂被控对象,并且目前对电弧炉的控制要求越来越严格,为此将反步控制与自适应模糊控制相结合,应用于电弧炉电极调节系统中.给出了反步自适应模糊控制系统的详细设计过程.用递推法设计反步控制量,用自适应模糊控制逼近反步控制量中的不确定项,设计出自适应模糊控制律.通过李亚普诺夫函数推导了模糊规则参数调整的自适应律.最后引入监督控制以减少模糊逼近误差.仿真结果表明:所提出的控制算法能有效地抑制弧长的扰动,具有较强的鲁棒性,从而使电弧炉电极调节系统拥有较好的动静态性能.     

基于混合滑模控制器和反正切观测器的SPMSM直接转矩控制

针对基于传统PI控制的表贴式永磁同步电机(SPMSM)直接转矩控制系统抖振和相位延迟等问题,在转速环节设计新型趋近律,采用模糊自适应方法,实现趋近律参数的动态调节,并通过Lyapunov方法证明稳定性.利用super-twisting滑模策略生成参考电压矢量,完成混合滑模控制器的设计,建立基于反正切函数的滑模观测器,并对转子位置进行合理补偿.仿真实验表明,与PI控制、基于指数趋近律的滑模控制器相比,所设计的控制器在电机空载起动和外加干扰情况下均能有效提高系统响应,显著降低抖振,与其他模型参考自适应观测器相比,所设计观测器能有效减小相位延迟,转子位置辨识结果更准确.     

基于T-S模型的Chua混沌系统模糊变结构控制

针对Chua混沌系统这一复杂的非线性系统给出一种基于T-S模型的模糊变结构控制律设计。首先采用T-S模糊动态模型描述非线性系统,得到混沌系统的全局模糊模型;然后采用Lyapunov稳定性理论设计出确保模糊动态模型全局渐近稳定的变结构控制器,将模糊控制与成熟的线性变结构控制相结合,来解决非线性系统控制问题。仿真验证了方案的有效性。模糊控制器简单,规则少。     

A method for design of a hybrid neuro-fuzzy control system based onbehavior modeling

It is known that control signals from a fuzzy logic controller are determined by a response behavior of a controlled object rather than its analytical models. That implies that the fuzzy controller could yield a similar control result for a set of plants with a similar dynamic behavior. This idea lends to modeling of a plant with unknown structure by defining several types of dynamic behaviors. On the basis of dynamic behavior classification, a new method is presented for the design of a neuro-fuzzy control system in two steps: 1) we model a plant with unknown structure by choosing a set of simplified systems with equivalent behavior as “templates” to optimize their fuzzy controllers off-line; and 2) we use an algorithm for system identification to perceive dynamic behavior and a neural network to adapt fuzzy logic controllers by matching the “templates” online. The main advantage of this method is that convergence problem can be avoided during adaptation process. Finally, the proposed method is used to design neuro-fuzzy controllers for a two-link manipulator     

Design of output feedback proportional–integral controller for polynomial fuzzy systems

In this paper, the design of dynamic output feedback control law for polynomial fuzzy systems is studied. The main purpose is to design a tracker control law for fuzzy polynomial systems that are subject to external bounded disturbances. The structure of the control law is considered as fuzzy proportional–integral control. The conditions for deriving the control law are formulated in the form of a sum of square (SOS) feasibility problem. The designed control law will be able to force the system state vector to follow the state vector of a stable reference model in addition to guaranteeing the $H_{\infty }$ performance measure. The simulation results show the efficiency of the proposed method exposed to external disturbance.     

拟人控制二维单倒立摆

以二维单极倒立摆为被控对象，利用拟人控制的思想形成非线性控制律，并确定出反馈系数间的相对关系。通过在线调试实现定性控制律的量化，从而成功地控制了二维单级倒立摆的稳定。与传统的控制系统设计相比，不依赖于数学模型，不受线性约束；与模糊控制相比，不需要人类直接被控对象的经验。拟人控制方法设计简单易行，且得到的控制系统具有较强的鲁棒性。     

基于模糊自适应滑模的非线性系统的故障调节

对于非线性系统提出故障调节控制的设计方法,通过附加控制律补偿故障所带来的影响．利用模糊逻辑系统估计故障并提供故障的修正行为,即主动容错．引入滑模控制抵消模糊逼近误差,经故障调节后闭环系统是稳定的．通过仿真算例证明了该方法的有效性．     

Improving asynchronous motor speed and flux loop control by using hybrid fuzzy-SMC controllers

This paper presents a new method combining sliding mode control (SMC) and fuzzy logic control (FLC) to enhance the robustness and performance for a class of non-linear control systems. This fuzzy sliding mode control (FSMC) is developed for application in the area for controlling the speed and flux loops of asynchronous motors. The proposed control law can solve those problems associated with the conventional control by sliding mode control, such as high current, flux and torque chattering, variable switching frequency and variation of parameters, in which a robust fuzzy logic controller replaces the discontinuous part of the classical sliding mode control law. Simulation results of the proposed FSMC technique on the speed and flux rotor controllers present good dynamic and steady-state performances compared to the classical SMC in terms of reduction of the torque chattering, quick dynamic torque response and robustness to disturbance and variation of parameters.     

Hinfinity controller design of fuzzy dynamic systems based on piecewise Lyapunov functions.

This paper presents a controller design method for fuzzy dynamic systems based on a piecewise smooth Lyapunov function. The basic idea of the proposed approach is to construct controllers for the fuzzy dynamic systems in such a way that a piecewise continuous Lyapunov function can be used to establish the global stability with Hinfinity performance of the resulting closed loop fuzzy control systems. It is shown that the control law can be obtained by solving a set of Linear Matrix Inequalities (LMI) that is numerically feasible with commercially available software. An example is given to illustrate the application of the proposed method.     

Fault accommodation for nonlinear systems using fuzzy adaptive sliding control

An active fault accommodation control law is developed for a class of nonlinear systems to guarantee the closed-loop stability in the presence of a fault, based on a fuzzy logic system representation of the dynamics due to faults. It uses fuzzy logic system to approximate the dynamic caused by the fault. Through the adaptive process of the parameters, the dynamics caused by the fault is counteracted. The fuzzy sliding mode control is introduced to attenuate the fuzzy approximation error. Simultaneity, the closed-loop system is stable in Lyapunov sense and the tracking error converges to a neighbourhood of zero. The example of the proposed design indicates that the fault accommodation control law is effective for a nonlinear system.     

An approach to adaptive control of fuzzy dynamic systems

This paper discusses adaptive control for a class of fuzzy dynamic models. The adaptive control law is first designed in each local region and then constructed in the global domain. It is shown that the resulting fuzzy adaptive control system is globally stable. Robustness issues of the adaptive control system are also addressed. A simulation example is given for demonstration of the application of the approach     

一种新型时滞系统鲁棒控制器设计方法

针对一类用模糊动态模型描述的非线性时滞系统，提出一种基于模糊性能评估器的新型鲁棒控制方案，模糊性能评估器用于检验模糊模型及其控制率的有效性，以线性矩阵不等式的形式，给出了模糊性能评估器和模糊控制器存在的充分条件；分析了闭环控制效果与模糊性能评估器性能之问的关系，从而说明该方法为模糊控制系统提供了一种无损调试方法，最后以CSTR系统为例，通过仿真验证了该方法的有效性。     

变风量空调系统中的室温模糊自适应控制

本文提出了变风量空调系统中室温控制方案。针对控制对象的大惯性、大时延特点,采用了串级控制策略;针对对象的非线性和不确定性,主控器采用了一种新的模糊自整定PID参数的方式,经仿真验证,该主控器具有良好的动、静态性能,特别是在鲁棒性方面大大优于常规PID控制器。