Robust adaptive fuzzy control for a class of perturbed pure-feedback nonlinear systems

A new design scheme of direct adaptive fuzzy controller for a class of perturbed pure-feedback nonlinear systems is proposed. The design is based on backstepping and the approximation capability of the first type fuzzy systems. A continuous robust term is adopted to minify the influence of modeling errors or disturbances. By introducing the modified integral-type Lyapunov function, the approach is able to avoid the requirement of the upper bound of the first time derivation of the high frequency control gain. Through theoretical analysis, the closed-loop control system is proven to be semi-globally uniformly ultimately bounded, with tracking error converging to a residual set.

Adaptive fuzzy compensation based composite nonlinear feedback controller design for robot manipulators

In order to suppress the influence of uncertain factors on robot system and enable an uncertain robot system to track the reference input accurately,a strategy of combining composite nonlinear feedback(CNF)control and adaptive fuzzy control is studied,and a robot CNF controller based on adaptive fuzzy compensation is proposed.The key of this strategy is to use adaptive fuzzy control to approach the uncertainty of the system online,as the compensation term of the CNF controller,and make full use of the advantages of the two control methods to reduce the influence of uncertain factors on the performance of the system.The convergence of the closed-loop system is proved by feedback linearization and Lyapunov theory.The final simulation results confirm the effectiveness of this plan.

Direct Adaptive Fuzzy Based Backstepping Control of Semi Strict Feedback Nonlinear Systems

In this paper, a direct adaptive fuzzy tracking control is proposed for a class of uncertain single-input single-output nonlinear semi-strict feedback systems. Based on Takagi-Sugeno type fuzzy systems, a direct adaptive fuzzy tracking controller is developed by using the backstepping approach. The main advantage of the developed method is that for an n-th order system, only one parameter is needed to be adjusted online. It is proven that, under the appropriate assumptions, the developed scheme can achieve that the output system converges to a small neighborhood of the reference signal and all the signals in the closed-loop system remain bounded. The efficacy of the proposed algorithm is investigated by an illustrative simulation example of one link robot.

Adaptive Backstepping Output Feedback Control for SISO Nonlinear System Using Fuzzy Neural Networks

In this paper, a new fuzzy-neural adaptive control approach is developed for a class of single-input and single-output （SISO） nonlinear systems with unmeasured states. Using fuzzy neural networks to approximate the unknown nonlinear functions, a fuzzy- neural adaptive observer is introduced for state estimation as well as system identification. Under the framework of the backstepping design, fuzzy-neural adaptive output feedback control is constructed recursively. It is proven that the proposed fuzzy adaptive control approach guarantees the global boundedness property for all the signals, driving the tracking error to a small neighbordhood of the origin. Simulation example is included to illustrate the effectiveness of the proposed approach.

Fuzzy Robust H1 Control for UncertainNonlinear Systems via Output Feedback

This paper is concerned with a fuzzy robust H∞ control problem via output feedbackfor a class of uncertain nonlinear systems. The uncertain nonlinear systemsare represented by fuzzy Takagi-Sugeno （T-S） model, and a fuzzy controller is designedbased on the state observer. A sufficient condition for the existence of fuzzycontroller is given in terms of the linear matrix inequalities （LMIs） and the adaptivelaw. Based on Lyapunov stability theorem, the proposed fuzzy control scheme suchthat the desired H∞performance is achieved in the sense that all the closed-loopsignals are uniformly ultimately bounded （UUB）. Simulation results indicate theeffectiveness of the developed control scheme. In this paper, a less conservativefuzzy tracking controller is proposed, where the matching condition and the upperbound are avoided. Comparing with the existing works, the dimension of the LMIsof this paper is reduced.

Fuzzy Adaptive Tracking Control of Uncertain Strict-Feedback Nonlinear Systems with Disturbances Based on Generalized Fuzzy Hyperbolic Model

In this paper, a fuzzy adaptive tracking control for uncertain strict-feedback nonlinear systems with unknown bounded disturbances is proposed. The generalized fuzzy hyperbolic model (GFHM) with better approximation performance is used to approximate the unknown nonlinear function in the system. The dynamic surface control (DSC) is used to design the controller, which not only avoids the “explosion of complexity” problem in the process of repeated derivation, but also makes the control system simpler in structure and lower in computational cost because only one adaptive law is designed in the controller design process. Through the Lyapunov stability analysis, all signals in the closed loop system designed in this paper are semi-globally uniformly ultimately bounded (SGUUB). Finally, the effectiveness of the method is verified by a simulation example.

Robust decentralized adaptive output feedback fuzzy controller design and application to AHS

A novel decentralized indirect adaptive output feedback fuzzy controller is developed for a class of large-scale uncertain nonlinear systems using error filtering.By the properly filtering of the observation error dynamics,the strictly positive-real condition is guaranteed to hold such that the proposed output feedback and adaptation mechanisms are practicable in practice owing to the fact that its implementation does not require the observation error vector itself any more,which corrects the impracticable schemes in the previous literature involved.The presented control algorithm can ensure that all the signals of the closed-loop large-scale system keep uniformly ultimately bounded and that the tracking error converges to zero asymptotically.The decentralized output feedback fuzzy controller can be applied to address the longitudinal control problem of a string of vehicles within an automated highway system（AHS） and the effectiveness of the design procedure is supported by simulation results.

Adaptive fuzzy control for uncertain nonlinear systems

In this paper,a survey of adaptive fuzzy for uncertain nonlinear systems is presented.The first part introduces adaptive fuzzy control emergence and some typical control methods for uncertain nonlinear systems with matching conditions(single-input singleoutput systems,multi-input multi-output systems).The last part presents the adaptive fuzzy state feedback and output-feedback control methods for uncertain nonlinear systems with non-matching conditions based on the backstepping technique,including strictfeedback systems,pure-feedback systems and non-strict-feedback systems.

Fuzzy Static Output Feedback H_∞ Control for Nonlinear Systems Subject to Parameter Uncertainties

This study is concerned with the stabilization issue of nonlinear systems subject to parameter uncertainties. An interval type-2 T-S fuzzy model is used to represent the nonlinear systems subject to parameter uncertainties. An interval type-2 fuzzy static output feedback controller is designed to synthesize the interval type-2 T-S fuzzy systems. The membership-function-dependent stability conditions are derived by utilizing the information of upper and lower membership functions. The proposed stability conditions are presented in the form of linear matrix inequalities（LMIs）. LMI-based stability conditions for interval type-2 fuzzy static output feedback H_∞ control synthesis are also developed.Several simulation examples are given to show the superiority of the proposed approach.

Event-Triggered Adaptive Fuzzy Finite Time Control of Fractional-Order Non-Strict Feedback Nonlinear Systems

In this article,the problem of event-triggered adaptive fuzzy finite time control of nonstrict feedback fractional order nonlinear systems is investigated.By using the property of fuzzy basis function,the obstacle caused by algebraic loop problems is successfully circumvented.Moreover,a new adaptive event-triggered scheme is designed under the unified framework of backstepping control method,which can largely reduce the amount of communications.The stability of the closed-loop system is ensured through fractional Lyapunov stability analysis.Finally,the effectiveness of the proposed scheme is verified by simulation examples.

Classical state feedback controller for nonlinear systems using mean value theorem： closed Ioop-FOC of PMSM motor application

The problem of state feedback controllers for a class of Takagi-Sugeno （T-S） Lipschitz nonlinear systems is investigated. A simple systematic and useful synthesis method is proposed based on the use of the differential mean value theorem （DMVT） and convex theory. The proposed design approach is based on the mean value theorem （MVT） to express the nonlinear error dynamics as a convex combination of known matrices with time varying coefficients as linear parameter varying （LPV） systems. Using the Lyapunov theory, stability conditions are obtained and expressed in terms of linear matrix inequalities （LMIs）. The controller gains are then obtained by solving linear matrix inequalities. The effectiveness of the proposed approach for closed loop-field oriented control （CL-FOC） of permanent magnet synchronous machine （PMSM） drives is demonstrated through an illustrative simulation for the proof of these approaches. Furthermore, an extension for controller design with parameter uncertainties and perturbation performance is discussed.

Output Feedback Dynamic Surface Controller Design for Airbreathing Hypersonic Flight Vehicle

This paper addresses issues related to nonlinear robust output feedback controller design for a nonlinear model of airbreathing hypersonic vehicle. The control objective is to realize robust tracking of velocity and altitude in the presence of immeasurable states, uncertainties and varying flight conditions. A novel reduced order fuzzy observer is proposed to estimate the immeasurable states. Based on the information of observer and the measured states, a new robust output feedback controller combining dynamic surface theory and fuzzy logic system is proposed for airbreathing hypersonic vehicle. The closedloop system is proved to be semi-globally uniformly ultimately bounded (SUUB), and the tracking error can be made small enough by choosing proper gains of the controller, filter and observer. Simulation results from the full nonlinear vehicle model illustrate the effectiveness and good performance of the proposed control scheme. © 2014 Chinese Association of Automation.

基于GA-SVR模型的肌力康复电刺激系统的设计研究

为了实现康复电刺激系统治疗参数的个性化定制及实时调整,提出了一种基于调制中频电刺激的下肢肌力康复闭环电刺激系统。设计低频调制中频刺激电路,基于遗传算法建立了电刺激参数与膝关节角度之间的支持向量机回归预测模型,并搭建基于模糊内模控制PID的闭环反馈系统,以达到更精确稳定的参数设置效果。通过膝关节运动实验表明,被试者在无痛感的前提下更接近预期的关节运动轨迹,30组膝关节运动角度与预期值最大均方根误差为10.21°,最小均方根误差为5.48°。相比传统低频电刺激,肌电平均振幅具有20μV以上提升。本文提出的电刺激系统参数可实现因人而异,且可根据闭环反馈结果进行实时调整,该系统能有效活化肌肉、提升肌力,在肌力康复步态训练中有较好的应用前景。

旋转导向钻井系统Fuzzy-PID控制算法

旋转导向闭环钻井技术是国际石油行业的关键技术。该文提出在旋转导向钻井系统中采用Fuzzy-PID控制算法,建立液压系统模型并分析其具有非线性特性,搭建液压测试系统模拟真实钻井环境做相应测试和仿真。通过比较经典PID控制和Fuzzy-PID控制算法,得出Fuzzy-PID算法时延小、算法易实现、相对经典PID算法大大减少超调量的优点,从而为实际钻井系统的控制设计提供可靠性依据。

New Approach to Stability Analysis and Stabilization of Discrete-Time T-S Fuzzy Descriptor Systems

The problems of stability and state feedback control for a class of discrete-time T-S fuzzy descriptor systems are investigated in this paper. Based on fuzzy Lyapunov function,a set of slack variables is introduced to remove the basic semi-definite matrix inequality condition to check the regularity,causality and stability of discrete-time T-S fuzzy descriptor systems; a new sufficient condition for the discrete-time T-S fuzzy descriptor systems to be admissible is proposed in terms of strict linear matrix inequalities( LMIs). And a sufficient condition is proposed for the existence of state feedback controller in terms of a set of coupled strict LMIs.Finally,an illustrative example is presented to demonstrate the effectiveness of the proposed approach.

低渗灰岩油藏气水均衡驱替主控参数合理界限及开发效果评价

为制定中东低渗生屑灰岩油藏注气注水均衡驱替合理开发技术政策,设计开发因素正交试验模拟,运用组分模型数模技术,并通过二元次模型创建开发主控参数正交图版,明确气水协同注入均衡驱替的主控参数界限;在此基础上,构建基于数模预测的开发动态模糊综合评价体系,定量表征油井生产差异性,评价开发效果,指导矿场先导试验区优选。结果表明:注气注水开发主控参数对采出程度的影响由大到小排序为注气速度、注入时机、采油速度、井距、注水速度;实现油气油水前缘均衡驱替的合理采油速度为2.0%,注气速度为(34~45)×10^(4)m^(3)/d,注水速度为240~320 m^(3)/d,注采井距700 m,地层压力保持原始地层压力水平85%;指导优选开发等级区,实施注水注气矿场先导试验,取得较好试验效果。

一类时变非线性系统的参数反馈模糊控制器分析与设计

本文针对工业控制中一类常见的非线性时变系统 ,提出了一种利用参数反馈在线修正规则的模糊控制器 ;在全面介绍控制器结构与功能的同时 ,详细阐述了模糊规则修正器的原理和设计方法 ,并采用基于功能评价的方法进行系统分析 .在这个控制系统中 ,基本模糊控制器简单实用 ;模糊规则修正器能充分利用对被控对象的分析成果 ;GA寻优算法能进一步简化设计 ,提高性能 .仿真结果表明 ,这种控制器的效果是令人满意的 .

一种基于模糊逻辑的城市交叉口交通信号控制方法

提出了一种基于模糊逻辑的交叉口信号控制方法 ,此方法不需要建立复杂的交通流模型 ,可以有效地解决交通信号控制过程中复杂和随机性难题。同时应用加权系数的遗传算法对模糊逻辑控制器的参数进行了优化。仿真结果表明模糊逻辑控制可以成功地应用于城市交叉口交通信号控制中。

汽轮发电机组的鲁棒性控制

主要介绍了基于反馈线性化的非线性变结构控制、模糊变结构控制、带等效控制项的非线性变结构控制、非线性 PID控制等几种控制方式 ,以及它们在电力系统励磁、汽门及其综合控制中的应用。

基于T-S模糊模型的状态反馈预测控制

将T-S模糊模型和状态反馈预测控制相结合,提出了一种基于T-S模糊模型的预测控制算法.该算法把T-S模糊模型作为预测模型得到状态和输出的预估值,并利用可测的过程变量对输出预估值进行反馈修正,然后利用最优控制理论,由修正后的预估值和给定值计算出控制整个系统的控制律.本文还对串级CSTR控制系统的不同的初态、设定值及干扰情况下进行了仿真,仿真结果表明了该方法的有效性和可行性.