含不匹配扰动非严格反馈系统的输出反馈补偿控制

针对一类非严格反馈非线性系统,系统中包含不确定函数和未知外部扰动,提出一种带不匹配扰动补偿的输出反馈模糊控制器.采用模糊逻辑系统逼近未知的非线性函数,同时构造模糊状态观测器观测系统未知状态.考虑观测器和控制器会受到外部扰动和模糊逼近误差构成的不匹配总扰动信号影响,采用改进的扰动观测器对不匹配扰动进行估计和补偿,使扰动观测误差能够在有限时间内平缓地收敛到任意小的范围,消除不匹配扰动信号对模糊观测器设计的影响.同时在控制器设计中进行扰动的精确补偿,提高系统的抗扰动性.通过Lyapunov函数证明了闭环系统所有信号都是有界的.最后,通过数值仿真进一步验证了所提出方法的有效性.     

输出受限的不确定非线性系统的自适应固定时间控制

针对具有非对称输出约束和外界干扰的不确定非线性系统,提出自适应固定时间反步控制策略.首先,采用非对称障碍Lyapunov函数处理系统的输出约束问题;其次,通过构造固定时间干扰观测器估计外界干扰,设计自适应固定时间滤波器,解决传统反步控制的“计算爆炸”问题,通过自适应律估计虚拟控制输入导数的未知上界;再次,基于Lyapunov稳定性理论证明闭环系统在固定时间内有界稳定且输出保持在约束范围内;最后,通过永磁同步电机的仿真验证所设计的控制策略的有效性.     

带有海浪滤波器的船舶航向反步自适应输出反馈控制

针对复杂海况下船舶航向控制中的模型非线性、参数不确定和海浪扰动问题,提出了一种基于反步法的非线性自适应输出反馈控制算法.首先基于无源理论设计了一种状态观测器以实现海浪滤波和状态估计,这种观测器无需海浪扰动的方差信息从而减少了观测器参数数量.然后假定系统模型参数未知,基于反步法给出了非线性控制律和参数自适应律.利用Lyapunov理论证明了这种自适应输出反馈控制系统的稳定性.仿真结果表明本文所提控制器具有较好的控制性能,对不确定性模型参数具有良好的自适应性.     

一类严格反馈系统变比例增益精确微分补偿控制

针对包含不确定函数和未知外部扰动的一类严格反馈型非线性系统,提出基于精确扰动观测器的变比例增益自适应模糊控制器.系统中的未知不确定函数由模糊逻辑系统在线逼近,同时将模糊逻辑系统的逼近误差和未知外部扰动定义为总扰动,利用精确扰动观测器进行精确微分补偿控制. 将非线性函数应用于设计可调节的输出反馈增益,有效消除系统的稳态误差,使得系统跟踪误差可以控制在零的任意小邻域内.最后,通过Lyapunov定理证明闭环系统中所有信号均是有界的.数值仿真表明了所提出方案的有效性.     

基于输出反馈和滑模控制的一类二阶非线性系统有限时间镇定方法

本文研究了一类具有不确定非线性动力学和未知外部扰动的二阶非线性系统的全局有限时间输出镇定问 题. 首先, 提出了一种全局状态反馈有限时间控制器, 实现了二阶非线性系统的有限时间镇定. 为了解决只有系统输 出可用这种更有挑战性的情况, 采用了一种新颖的设计思想, 即非分离原理. 构造了一个有限时间收敛的状态观测 器来估计未知状态. 在此观测器的基础上, 提出了一种基于输出的有限时间复合控制器. 基于李雅普诺夫方法, 证明 了整个闭环系统的全局有限时间稳定性. 仿真结果表明了理论的有效性.     

一类非线性系统的神经网络自适应区间观测器设计

本文研究了一类单输入单输出非线性系统的神经网络自适应区间观测器设计问题. 针对由状态和输入所描述的未知非线性函数的界不可测, 现有的区间观测器方法并未有效地处理系统含有参数不确定性的未知非线性函数. 首先, 本文构造两个径向基函数神经网络来逼近未知非线性部分, 进而分别估计系统状态的上下界; 然后, 选择合适的Lyapunov函数, 采用网络权值校正和网络误差选择机制确保所设计的误差动态系统有界和非负性, 并证明了神经网络自适应区间观测器的稳定性; 最后, 通过仿真实例验证了所提出的神经网络自适应区间观测器的有效性.     

具有输入和输出约束的高阶随机系统神经网络控制

针对高阶非线性系统,开展自适应神经网络跟踪控制器设计,系统受到随机扰动的影响.首次把输入和输出约束问题引入到高阶系统的跟踪控制中,并假定系统动态是未知.首先借用高斯误差函数表达连续可微的非对称饱和模型以实现输入约束,和障碍Lyapunov函数保证系统输出受限;其次,针对高阶非线性系统,径向基函数(RBF)神经网络用来克服未知系统动态和随机扰动.在每一步的backstepping计算中,仅用到单一的自适应更新参数,从而克服了过参数问题;最后,基于Lyapunov稳定性理论提出自适应神经网络控制策略,并减少了学习参数.最终结果表明设计的控制器能保证所有闭环信号半全局最终一致有界,并能使跟踪误差收敛到零值小的邻域内.仿真研究进一步验证了提出方法的有效性.     

控制方向未知的全状态约束非线性系统的鲁棒自适应跟踪控制

针对一类控制方向未知的含有时变不确定参数和未知时变有界扰动的全状态约束非线性系统,本文提出了一种基于障碍Lyapunov函数的反步自适应控制方法.障碍Lyapunov函数保证了系统状态在运行过程中始终保持在约束区间内;Nussbaum型函数的引入解决了系统控制方向未知的问题;光滑投影算法确保了不确定时变参数的有界性.障碍Lyapunov函数、Nussbaum型函数及光滑投影算法与反步自适应方法的有效结合首次解决了控制方向未知的全状态约束非线性系统的跟踪控制问题.所设计的自适应鲁棒控制器能在满足状态约束的前提下确保闭环系统的所有信号有界.通过恰当地选取设计参数,系统的跟踪误差将收敛于0的任意小的邻域内.仿真结果表明了控制方案的可行性.     

非线性系统的模糊自适应输出反馈控制

针对一类未知非线性系统,考虑系统状态不完全可测的情况,利用Lyapunov综合方法设计了一种基于高增益观测器的模糊鲁棒自适应输出反馈控制器,并证明在一定条件下,所设计的输出反馈控制器能获得状态反馈控制器的性能。     

基于预估器的一类多智能体系统神经动态面输出一致控制

本文针对一类含未知扰动与非对称输入饱和的非线性多智能体系统,提出基于预估器的神经动态面输出一致控制策略.在设计预估器的基础上构造预估误差,驱动神经网络更新权值估计系统未知动态,并将预估器与神经网络应用于非线性扰动观测器来补偿广义扰动.本文所提出的控制策略采用神经网络权值范数学习方法,减少学习参数数目.对于非对称的输入饱和,设计辅助系统,其生成的辅助变量与反步法相结合补偿输入限制.结合图论知识和Lyapunov函数等技术,证明多智能体系统的输出一致跟踪误差以及闭环系统中的所有信号最终有界.最后通过一组四旋翼飞行器和数值仿真验证提出控制策略的有效性.     

Type-2 Fuzzy Adaptive Output Feedback Saturation Control for Photovoltaic Grid-connected Power Systems

The adaptive interval type-2 (IT2) fuzzy output feedback control problem is studied for a single-phase photovoltaic grid-connected power system. The equivalent resistors of the inductors in the system are unknown and the part states are not available. Interval type-2 fuzzy logic systems (IT2FLSs) are utilized to approximate the uncertain nonlinear dynamics, and an IT2 fuzzy state observer is designed to estimate the unavailable states. By introducing a command filter method and using a backstepping control design technique, an IT2 fuzzy output feedback control scheme is investigated, in which the constraint conditions of pulse width modulation are ensured via mean-value theorem. It is proved that all the variables of the closed-loop photovoltaic system are uniformly ultimately bounded. The simulation and comparison results demonstrate the validity of the proposed control scheme.

     

Fuzzy adaptive output feedback control for a class of switched non-triangular structure nonlinear systems with time-varying delays

This paper investigates an adaptive fuzzy output feedback control design problem for switched nonlinear system in non-triangular structure form. The discussed system contains unknown nonlinear dynamics, unmeasured states and unknown time-varying delays under a batch of switching signals. Fuzzy logic systems are utilised to learn unknown nonlinear dynamics and construct a fuzzy switched nonlinear observer. By combining the property of fuzzy basis function with Lyapunov–Krasovskii functional and the command filter, a novel observer-based fuzzy adaptive backstepping schematic design algorithm is presented. Furthermore, the stability of the closed-loop control system is proved via Lyapunov stability theory and average dwell time method. The simulation results are presented to verify the validity of the proposed control scheme.     

Adaptive dynamic surface control using disturbance observer for nonlinear systems with input saturation and output constraints

An adaptive dynamic surface control (DSC) approach using fuzzy approximation and nonlinear disturbance observer (NDO) for uncertain nonlinear systems in the presence of input saturation, output constraint and unknown external disturbances is proposed in this paper. The issue of input saturation is addressed by introducing a lower bound assumption on the approximation function of saturation. The output constraint is handled by introducing an appropriate barried Lyapunov function. The nonlinear disturbance observer (NDO) is employed to estimate the unknown unmatched disturbances. It is manifested that the ultimately bounded convergence of all the variables in the closed-loop system is guaranteed and the tracking error can be made farely small by tuning the design parameters. Finally, two simulation examples illustrate the effectiveness and feasibility of the proposed approach.     

Observer‐based adaptive control for nonlinear strict‐feedback stochastic systems with output constraints

In this paper, an adaptive output‐feedback control problem is investigated for nonlinear strict‐feedback stochastic systems with input saturation and output constraint. A barrier Lyapunov function is used to solve the problem of output constraint. Then, fuzzy logic systems are used to approximate the unknown nonlinear functions, and a fuzzy state observer is designed to estimate the unmeasured states. To overcome the difficulties in designing the control signal in the saturation, we introduce an auxiliary signal in the n + 1th step in the deduction. By combining Nussbaum technique and the adaptive backstepping technique, an adaptive output‐feedback control method is developed. The proposed control method not only overcomes the problem of the compensation for the nonlinear term from the input saturation but also overcomes the problem of unavailable state measurements. It is proved that all the signals of the closed‐loop system are semiglobally uniformly ultimately bounded. Finally, the effectiveness of the proposed method is verified by the simulation results.     

Design of interval type-2 fuzzy sliding-mode controller

In this paper, an interval type-2 fuzzy sliding-mode controller (IT2FSMC) is proposed for linear and nonlinear systems. The proposed IT2FSMC is a combination of the interval type-2 fuzzy logic control (IT2FLC) and the sliding-mode control (SMC) which inherits the benefits of these two methods. The objective of the controller is to allow the system to move to the sliding surface and remain in on it so as to ensure the asymptotic stability of the closed-loop system. The Lyapunov stability method is adopted to verify the stability of the interval type-2 fuzzy sliding-mode controller system. The design procedure of the IT2FSMC is explored in detail. A typical second order linear interval system with 50% parameter variations, an inverted pendulum with variation of pole characteristics, and a Duffing forced oscillation with uncertainty and disturbance are adopted to illustrate the validity of the proposed method. The simulation results show that the IT2FSMC achieves the best tracking performance in comparison with the type-1 Fuzzy logic controller (T1FLC), the IT2FLC, and the type-1 fuzzy sliding-mode controller (T1FSMC).     

Backstepping sliding mode control with FWNN for strict output feedback non-smooth nonlinear dynamic system

An output feedback backstepping sliding mode control scheme was developed for precision positioning of a strict single-input and single-output (SISO) non-smooth nonlinear dynamic system that could compensate for deadzone, dynamic friction, uncertainty and estimations of immeasurable states. An adaptive fuzzy wavelet neural networks (FWNNs) technique was used to provide improved approximation ability to the system uncertainty. The adaptive laws were derived for application to estimate the deadzone and friction parameters using recursive backstepping controller design procedures. In addition, the sliding mode control method was also combined to enforce the robustness of the output feedback backstepping controller against disturbance. The Lyapunov stability theorem was used to prove stability of the proposed control system. The usefulness of the proposed control system was verified by simulations and experiments on a robot manipulator in the presence of a deadzone and friction in the actuator.     

控制方向未知的SISO非仿射系统间接自适应模糊输出反馈控制

针对一类单输入单输出(SISO)非仿射非线性系统控制方向未知时出现的控制器奇异问题,提出了一种间接自适应模糊控制方案.利用中值定理将非仿射系统转化为仿射系统,通过模糊逻辑系统逼近该仿射系统中的未知函数,并构造模糊控制器,同时利用Lyapunov稳定性定理设计自适应律,最终克服了控制器的奇异问题;在此基础上,通过构造观测器估计跟踪误差,设计输出反馈自适应模糊控制器,解决了状态不可测时系统控制器设计难题,采用Lyapunov稳定性定理证明控制器能使得跟踪误差收敛同时闭环系统所有信号均有界.仿真结果验证了所设计控制方案的可行性与有效性.     

Fire-rule-based direct adaptive type-2 fuzzy H tracking control

This paper presents a novel H^∞ tracking-based direct adaptive fuzzy controller (HDAFC) for a class of perturbed uncertain affine nonlinear systems involving external disturbances and measurement noise. A practical interval type-2 (IT2) fuzzy logic system (FLS) is introduced to approximate the ideal control law. To eliminate the tradeoff between H^∞ tracking performance and high gain at the control input, a modified output tracking error is introduced. Based on the proposed fired-rule-determination algorithm, a practical average defuzzifier expressed in parameterized and closed formula is developed for the IT2 FLS. Without the restriction that the control gain function is exactly known, the IT2 HDAFC is constructed and its adaptive law is derived by virtue of the Lyapunov synthesis. To improve control performance under measurement noise, the recursive linear smoothed Newton predictor is further introduced as a delayless output filter. Simulated application of a single-link robot manipulator demonstrates the superiority of the proposed approach over the previous approach in terms of the settling time, tracking accuracy, energy consumption and smoothness of the control input.