非线性奇异摄动系统的自适应模糊控制器设计

为解决模型未知情况下多输入多输出非线性奇异摄动系统的跟踪问题,提出一种新型的自适应模糊控制器。首先将被控系统分解为快慢子系统,对慢子系统,设计后件参数可调的直接型自适应模糊控制器,能保证系统的慢状态跟踪预定轨迹;对快子系统,则设计模糊控制器,能够保证快子系统的稳定,最终控制器为二者的合成。Lyapunov方法证明,只要摄动参数足够小,就能保证整个系统的稳定。仿真验证了所提方法的有效性。     

自适应模糊奇异摄动控制在航天器中的应用

带挠性附件航天器可以用含小摄动参数的多时标非线性系统进行描述,而目前的控制方法大多针对多时标线性系统,要求模型精确已知.为解决存在不确定性的带挠性附件航天器的跟踪问题,提出一种基于模糊奇异摄动模型的自适应控制器,采用鲁棒控制和自适应控制理论相结合的方法进行设计,由反馈项、自适应项和鲁棒控制项组成,反馈项的增益采用线性矩阵不等式(LMI)方法求解,自适应项用于减小系统的跟踪误差,鲁棒项用于保证系统的闭环稳定性.稳定性证明采用Lyapunov合成方法完成.该控制器适用于模型带有不确定性的多时标非线性系统的跟踪控制.由于采用了自适应方法消除系统不确定性,能够减少鲁棒控制方法带来的保守性.在带挠性附件航天器的跟踪控制中的应用验证了其有效性.     

模糊PID控制光电跟踪系统的抗干扰性分析

机载光电跟踪系统是一个复杂的非线性系统,影响其性能品质的因素很多。笔者建立的数学模型是略去很多非线性因素建立的线性模型,是没有外界干扰下的模型,和实际系统有一定的区别。为说明模糊自适应PID控制对不确定性系统有较强的鲁棒性,引入模型参数摄动方法,即增加外界干扰时进行仿真研究。最终得到了系统稳定的结论,为模糊自适应PID控制器的设计提供了理论依据。     

基于LMI的非线性模糊脉冲奇异摄动系统的鲁棒模糊控制

通过推广一般T-S模糊模型定义了一类非线性模糊脉冲奇异摄动系统,基于线性矩阵不等式(LMI)方法提出一种鲁棒模糊控制新方案,采用并行分布补偿(PDC)的基本思想设计状态反馈控制器,并利用Lyapunov理论证明闭环系统全局指数稳定.最后基于LMI方法,将鲁棒模糊控制器的设计问题转化为线性矩阵不等式问题(LMIP).仿真结果表明了该方法的有效性.     

模糊奇异摄动系统的鲁棒输出控制

本文研究了一类模糊奇异摄动系统的多目标控制问题。通过引用Schur补定理及相关引理,将控制器的设计转化为求解一组线性矩阵不等式的求解问题。该方法保证了对任意选取的ε∈(0,ε0](ε0是ε的上界),此系统存在具有ε依赖特性并且满足鲁棒H∞性能的动态输出反馈控制器。并且该控制器可使系统达到渐近稳定的效果。该方法避免了ε相关的数值刚性问题的出现以及"快慢分解"思想不适用于非标准奇异摄动系统的状况。仿真验证此方法的有效性。     

航空发动机模糊滑模变结构控制研究

针对航空发动机是一个具有时变不确定性的非线性系统,结合模糊控制和滑模变结构控制的特点,提出了一种基于模糊滑模变结构控制的航空发动机控制方法.采用线性滑模面和指数趋近律设计变结构控制器,应用模糊逻辑系统自适应调节切换增益,避免了传统滑模变结构控制系统在到达阶段对不确定性的敏感性,消除了滑模控制中的抖振.通过数字仿真,结果表明所设计的模糊滑模变结构控制器对系统的参数摄动和外部干扰具有不变性,使被控系统在整个控制阶段都具有较强的鲁棒性.     

自适应模糊滑模控制器设计

针对传统滑模控制的抖振问题,利用线性化反馈技术,将模糊自适应和滑模控制相结合,设计一种新型的模糊滑模控制器。通过模糊推理和基于Lyapunov函数的稳定性分析,获得模糊控制规则的自适应律,构成自适应模糊滑模控制器,有效解决了传统滑模控制中,需要确定参数摄动和外部干扰上确界不确定性问题,倒立摆上的运行结果表明该方法的有效性。     

非线性系统的自适应模糊控制器设计

针对非线性系统,为获得更好的控制控制效果,设计了模糊自适应控制器。在模糊控制器的基础上根据反馈控制和调整参数向量的自适应律的求解,综合李雅普诺夫稳定理论设计了模糊自适应控制器,以满足系统的稳定性和控制效果。为验证控制器的有效性,将该控制器应用到二级倒立摆系统的稳定控制,仿真结果表明该控制器的控制效果良好,并与传统的控制方法相比较,其控制效果更佳。     

基于模糊自适应PID控制的速度调节器设计与仿真

针对异步电动机非线性的特点,考虑到传统PID控制难以对其进行有效的控制的问题。文中设计了一种模糊自适应PID控制器,并将这种控制器应用到系统的转速调节的环节中。利用Matlab的Simulink工具搭建了模糊自适应PID控制的异步电机的仿真模型。仿真实验结果证明了设计的优越性,模糊自适应PID控制下的系统超调变小,反应速度变快,与原先的PID控制方式相比提高了系统的稳定性、动态响应性能以及鲁棒性能。     

惯性系统平台的自适应稳定回路研究

稳定回路在平台惯性系统中起着关键作用.但在设计稳定回路的控制器时,发现普通PID控制有抗干扰能力不强、控制参数易改变的缺点;因此设计了一种基于模糊控制原理的自适应模糊自抗扰控制器.该控制器充分结合了模糊控制器和自抗扰控制器的各自优势,利用模糊控制的推理能力,达到自动调整参数的目的.通过对光纤陀螺随动系统的仿真结果表明,在控制效果上,该控制器的自适应能力和抗干扰能力都优于经典PID控制器.说明自适应模糊自抗扰控制器在稳定回路中具有很好的应用前景.     

Adaptive neural network feedback control of a passive line-of-sight stabilization system

An adaptive neural network full-state feedback controller has been designed and applied to the passive line-of-sight (LOS) stabilization system. Model reference adaptive control (MRAC) is well established for linear systems. However, this method cannot be utilized directly since the LOS system is nonlinear in nature. Utilizing the universal approximation property of neural networks, an adaptive neural network controller is presented by generalizing the model reference adaptive control technique, in which the gains of the controller are approximated by neural networks. This removes the requirement of linearizing the dynamics of the system, and the stability properties of the closed-loop system can be guaranteed.     

Lyapunov-function-based design of fuzzy logic controllers and itsapplication on combining controllers

This paper presents the design of fuzzy logic controllers (FLCs) for nonlinear systems with guaranteed closed-loop stability and its application on combining controllers. The design is based on heuristic fuzzy rules. Although each rule in the FLC refers to a stable closed-loop subsystem, the overall system stability cannot be guaranteed when all these rules are applied together. In this paper, it is proved that if each subsystem is stable in the sense of Lyapunov (ISL) under a common Lyapunov function, the overall system is also stable ISL. Since no fuzzy plant model is involved, the number of subsystems generated is relatively small, and the common Lyapunov function can be found more easily. To probe further, an application of this design approach to an inverted pendulum system that combines a sliding-mode controller (SMC) and a state feedback controller (SFC) is reported. Each rule in this FLC has an SMC or an SFC in the consequent part. The role of the FLC is to schedule the final control under different antecedents. The stability of the whole system is guaranteed by the proposed design approach. More importantly, the controller thus designed can keep the advantages and remove the disadvantages of the two conventional controllers     

Robust stabilization of stochastic Markovian jumping systems via proportional-integral control

This paper studied the proportional-integral (PI) control problems of stochastic Markovian jump systems (MJSs) with uncertain parameters. Under complete access to the system states, the PI controller design procedure turns to static output feedback control problem that make the closed-loop dynamics of this class of uncertain MJSs be robustly stochastically stable. A sufficient condition on the existence of PI controller is presented and proved by means of linear matrix inequality techniques. The presented results are extended to the case when the system states are not accessible. In order to make the relative equations approximate with a satisfactory precision, we described the problem as a semidefinite programming one via disciplined convex optimization. Simulation results illustrate the validity of the proposed algorithms.     

Adaptive Fuzzy Output-Feedback Tracking Control for a Class of Switched Stochastic Nonlinear Time-Delay Systems

In this paper, a design scheme for an adaptive fuzzy tracking controller is proposed for a class of switched stochastic nonlinear time-delay systems via dynamic output-feedback. First, a reduced-order observer is introduced to estimate the unmeasurable states of the switched system. During the adaptive controller design procedure, an appropriate stochastic Lyapunov–Krasovskii functional deals with the time-delay terms, and fuzzy logic systems are employed to approximate the unknown nonlinearities. Based on the designed controller, the semi-globally uniform ultimate boundedness of all the closed-loop signals is guaranteed and the tracking error converges to a small neighborhood of the origin. Finally, a simulation example is given to illustrate the validity of the proposed approach.     

Neural predictive controller for insulin delivery using thesubcutaneous route

A neural predictive controller for closed-loop control of glucose using subcutaneous (s.c.) tissue glucose measurement and s.c. infusion of monomeric insulin analogs was developed and evaluated in a simulation study. The proposed control strategy is based on off-line system identification using neural networks (NNs) and nonlinear model predictive controller design. The system identification framework combines the concept of nonlinear autoregressive model with exogenous inputs (NARX) system representation, regularization approach for constructing radial basis function NNs, and validation methods for nonlinear systems. Numerical studies on system identification and closed-loop control of glucose were carried out using a comprehensive model of glucose regulation and a pharmacokinetic model for the absorption of monomeric insulin analogs from the s.c. depot. The system identification procedure enabled construction of a parsimonious network from the simulated data, and consequently, design of a controller using multiple-step-ahead predictions of the previously identified model. According to the simulation results, stable control is achievable in the presence of large noise levels, for unknown or variable time delays as well as for slow time variations of the controlled process. However, the control limitations due to the s.c. insulin administration makes additional action from the patient at meal time necessary     

部分转移概率离散奇异Markov跳变系统的镇定

针对具有更广泛意义的部分转移概率未知情况下的离散时间奇异 Markov跳变线性系统,给出了使开环系统正则、因果、随机稳定的充分条件,并表示为严格线性矩阵不等式形式,且消除了等式约束条件。部分转移概率未知的条件包括了完全开关系统和随机跳变转移概率完全未知的情况,适用范围更广泛;在此基础上,通过求解严格线性矩阵不等式的可行解,设计了模式依赖状态反馈控制器,使闭环系统正则、因果、随机稳定,实现了系统的镇定;最后,给出一个仿真算例验证了所提方法的有效性。     

On the stability of MIMO EWMA run-to-run controllers with metrology delay

As production requirements in semiconductor manufacturing continue to escalate, it is rarely possible to perform quality measurements on a product before subsequent process operations are performed. This delay between manufacturing and metrology coupled with inaccurate process models can lead to closed-loop instabilities. This paper investigates the effect of metrology delay on the closed-loop stability of a multiple input-multiple output exponentially weighted moving average run-to-run controller. The generalized Routh-Hurwitz stability criteria are used to derive the necessary and sufficient conditions for stability. A sufficient condition for stability is then derived for systems with any length of metrology delay. This condition states that if all of the eigenvalues of a model-mismatch matrix fall inside a circle with unit radius and centered at {1,0} on the complex plane, then the closed-loop system is stable.     

Adaptive control of time-varying mechanical systems: analysis andexperiments

A new adaptive controller for time-varying mechanical systems is proposed based on two assumptions: 1) the dynamics of time-varying mechanical systems is derived under the assumption that the generalized constraints on the system do not depend on time but the system parameters, such as masses and payloads are time-varying; and 2) the time-varying parameters are given by a group of known bounded time functions and unknown constants. It is shown that the proposed adaptive controller results in a stable closed-loop system. Further, if the desired trajectory of the system is periodic, a time-scaling technique of mapping one cycle period of the desired trajectory into a unit interval is proposed to provide robustness to the parameter adaptation algorithm. An experimental platform consisting of a two-link robot with a time-varying payload is developed to test the proposed adaptive controller. Comparative experimental results demonstrate the effectiveness of the proposed design     

Quantized Observer-Based Sliding Mode Control for Networked Control Systems Via the Time-Delay Approach

This paper investigates the sliding mode control problem for networked control systems, which are influenced by the non-ideal network environment, such as network-induced delays, packet dropouts and quantization errors. The states of the system are assumed to be unavailable, and an observer is designed to estimate the state of the system, based on which a sliding mode controller is given to guarantee the closed-loop system to be stable. Furthermore, it is shown that the proposed control scheme ensures the reachability of the sliding surfaces in both the state estimate space and the estimation error space. Finally, a numerical example is given to illustrated the effectiveness of the proposed methodology.     

A Decentralized Model Reference Adaptive Controller for Large-Scale Systems

A decentralized model reference adaptive controller (MRAC) for a class of large-scale systems with unmatched interconnections is developed in this paper. A novel reference model is proposed for the class of large-scale systems considered and a decentralized, full-state feedback adaptive controller is developed for each subsystem of the large-scale system. It is shown that with the proposed decentralized adaptive controller, the states of the subsystems can asymptotically track the desired reference trajectories. To substantiate the performance of the proposed controller, a large web processing line, which mimics most of the features of an industrial web process line, is considered for experimental study. Extensive experiments were conducted with the proposed decentralized adaptive controller and an often used decentralized industrial proportional-integral (PI) controller. A representative sample of the comparative experimental results is shown and discussed