A finite-time fuzzy adaptive output-feedback fault-tolerant control for underactuated wheeled mobile robots systems

This paper investigates the adaptive fuzzy finite-time output-feedback fault-tolerant control (FTC) problemfor a class of nonlinear underactuated wheeled mobile robots (UWMRs) system with intermittent actuatorfaults. The UWMR system includes unknown nonlinear dynamics and immeasurable states. Fuzzy logic systems(FLSs) are utilized to work out immeasurable functions. Furthermore, with the support of the backsteppingcontrol technique and adaptive fuzzy state observer, a fuzzy adaptive finite-time output-feedback FTC scheme isdeveloped under the intermittent actuator faults. It is testifying the scheme can ensure the controlled nonlinearUWMRs is stable and the estimation errors are convergent. Finally, the comparison results and simulationvalidate the effectiveness of the proposed fuzzy adaptive finite-time FTC approach.

Adaptive Output-feedback Regulation for Nonlinear Delayed Systems Using Neural Network

A novel adaptive neural network （NN） output-feedback regulation algorithm for a class of nonlinear time-varying timedelay systems is proposed. Both the designed observer and controller are independent of time delay. Different from the existing results, where the upper bounding functions of time-delay terms are assumed to be known, we only use an NN to compensate for all unknown upper bounding functions without that assumption. The proposed design method is proved to be able to guarantee semi-global uniform ultimate boundedness of all the signals in the closed system, and the system output is proved to converge to a small neighborhood of the origin. The simulation results verify the effectiveness of the control scheme.

Output-feedback Dynamic Surface Control for a Class of Nonlinear Non-minimum Phase Systems

In this paper, an output-feedback tracking controller is proposed for a class of nonlinear non-minimum phase systems.To keep the unstable internal dynamics bounded, the method of output redefinition is applied to let the stability of the internal dynamics depend on that of redefined output, thus we only need to consider the new external dynamics rather than internal dynamics in the process of designing control law. To overcome the explosion of complexity problem in traditional backstepping design, the dynamic surface control(DSC) method is firstly used to deal with the problem of tracking control for the nonlinear non-minimum phase systems. The proposed outputfeedback DSC controller not only forces the system output to asymptotically track the desired trajectory, but also drives the unstable internal dynamics to follow its corresponding bounded and causal ideal internal dynamics, which is solved via stable system center method. Simulation results illustrate the validity of the proposed output-feedback DSC controller.

A new nonlinear output tracking controller via output-feedback

In this paper, the output tracking control is investigated for a class of nonlinear systems when only output is available for feedback. Based on the multivariable analog of circle criterion, an observer is first introduced. Then, the observer-based output tracking controller is constructively designed by using the integral backstepping approach together with completing square. It is shown that, under relatively mild conditions, all the closed-loop signals are uniformly bounded. Meanwhile the system output asymptotically tracks the desired output. A simulation example is given to illustrate the effectiveness of the theoretical results.

Adaptive output-feedback control for MIMO nonlinear systems with time-varying delays using neural networks

An adaptive neural network output-feedback regulation approach is proposed for a class of multi-input-multi-output nonlinear time-varying delayed systems.Both the designed observer and controller are free from time delays.Different from the existing results,this paper need not the assumption that the upper bounding functions of time-delay terms are known,and only a neural network is employed to compensate for all the upper bounding functions of time-delay terms,so the designed controller procedure is more simplified.In addition,the resulting closed-loop system is proved to be semi-globally ultimately uniformly bounded,and the output regulation error converges to a small residual set around the origin.Two simulation examples are provided to verify the effectiveness of control scheme.

Output-feedback adaptive stochastic nonlinear stabilization using neural networks

For the first time, an adaptive backstepping neural network control approach is extended to a class of stochastic non- linear output-feedback systems. Different from the existing results, the nonlinear terms are assumed to be completely unknown and only a neural network is employed to compensate for all unknown nonlinear functions so that the controller design is more simplified. Based on stochastic LaSalle theorem, the resulted closed-loop system is proved to be globally asymptotically stable in probability. The simulation results further verify the effectiveness of the control scheme.

Robust output-feedback stabilization of a class of nonlinear systems with the nonlinearities of varied form

The back-stepping designs based on confine functions are suggested for the robust output-feedback global stabilization of a class of nonlinear continuous systems; the proposed stabilizer is efficient for the nonlinear continuous systems confined by a bound function, the nonlinearities of the systems may be of varied forms or uncertain; the designed stabilizer is robust means that a class of nonlinear continuous systems can be stabilized by the same output feedback stabilization schemes; numerical simulation examples are given.

Output-feedback Adaptive Control for a Class of Nonlinear Systems with Unknown Control Directions

在这份报纸，产量反馈适应稳定与未知控制方向为非线性的系统的一个班被调查。首先通过线性州的转变，未知控制系数在一起是 lumped，原来的系统被转变到控制设计为变得可行的一个新系统。在为状态和参数估计的一个观察员和一个评估者的介绍以后，分别地，然后，一个建设性的设计过程为产量反馈被给使用综合者 backstepping 并且调节功能技术的适应稳定控制器。而所有另外的靠近环的系统状态被围住，设计的控制器保证状态集成到起源的原来的系统，这被显示出而所有另外的靠近环的系统状态被围住。模拟结果被说明显示出建议途径的有效性。

Observer-based Output-feedback Stabilization Control Design for a Class of Nonlinear Uncertain Systems

The output-feedback stabilization control problem is investigated for a class of nonlinear uncertain systems. Based on the multivariable analog of circle criterion, an observer is designed to estimate the system states and hence the dynamical equations that the estimation error satisfies are derived first. Then, by using integral backstepping approach together with completing square technique, the output-feedback stabilization control is constructively designed such that the closed-loop system is asymptotically stable. Finally, an example is given to illustrate the main results of this paper.

Semiglobal Stabilization via Output-feedback for a Class of Uncertain Nonlinear Systems

这份报纸为不明确的非线性的系统的一个班经由产量反馈认为 semiglobal 是稳定。与存在结果不同，在调查下面的系统拥有更严肃的非线性和实质地增加产量反馈的困难的未知控制系数控制器设计。联合 backstepping 方法和产量反馈支配途径，稳定控制器的 semiglobal 明确地被给，它能保证靠近环的系统在设计参数的适当选择下面完成 semiglobal asymptotic 稳定性。一个模拟例子验证理论结果和建议途径。

含有输入时滞的非线性系统的输出反馈采样控制

针对含有输入时滞和低阶非线性项的非线性系统,提出一种基于采样机制的无记忆输出反馈控制方法.该方法移除了传统预测控制方法预测映射难以确定的限制,同时避免了时滞依赖方法对过去时刻状态信息的依赖性,在实际中更易实现.首先,根据系统输出在采样时刻的信息,利用加幂积分技术和齐次占优思想设计了无记忆输出反馈采样控制器.然后,利用齐次系统理论提出了闭环系统的稳定性条件.最后,仿真结果验证了所提方法的有效性和优越性.

Ultimately Bounded Output Feedback Control for Networked Nonlinear Systems With Unreliable Communication Channel: A Buffer-Aided Strategy

This paper concerns ultimately bounded output-feedback control problems for networked systems with unknown nonlinear dynamics. Sensor-to-observer signal transmission is facilitated over networks that has communication constraints.These transmissions are carried out over an unreliable communication channel. In order to enhance the utilization rate of measurement data, a buffer-aided strategy is novelly employed to store historical measurements when communication networks are inaccessible. Using the neural network technique, a novel observer-based controller is introduced to address effects of signal transmission behaviors and unknown nonlinear dynamics.Through the application of stochastic analysis and Lyapunov stability, a joint framework is constructed for analyzing resultant system performance under the introduced controller. Subsequently, existence conditions for the desired output-feedback controller are delineated. The required parameters for the observerbased controller are then determined by resolving some specific matrix inequalities. Finally, a simulation example is showcased to confirm method efficacy.

参数不确定连续系统的预见重复控制器设计

针对一类参数不确定连续时间系统,本文提出一种具有预见补偿的重复控制器.首先,引入重复控制器,采用预见控制理论中误差系统的方法,构造出包含未来目标值信号信息的扩大误差系统,将原系统的预见重复控制问题转化为扩大误差系统的反馈控制问题;然后,针对扩大误差系统,利用Lyaounov方法和线性矩阵不等式技巧给出闭环系统渐近稳定的条件.并基于此,设计预见重复控制器.最后,数值仿真表明本文结果的有效性.

DoS攻击下抛物型多智能体系统的输出反馈领导-跟随一致性

为了解决抛物型多智能体系统(MASs)在拒绝服务(DoS)攻击下的一致性问题,提出了一种基于输出反馈方法的MASs领导-跟随一致性控制协议来应对恶意攻击者发起的DoS攻击,从而实现智能体在无向通信拓扑图上的领导-跟随一致性。对DoS攻击的频率和持续时间进行了分析,利用Lyapunov稳定性定理推导了抛物型偏微分系统的稳定条件,证明了触发时间间隔不为零,避免了芝诺行为的发生,并通过仿真算例验证了理论结果的有效性。

VSC输出电流反馈型虚拟同步控制技术

基于输出功率反馈的虚拟同步机(VSG)技术在网侧故障时,难以保持电压源暂态特性并实现精准暂态冲击电流限制,同时极易出现暂态同步失稳问题。为解决上述问题,提出一种基于电压源型变流器(VSC)输出电流反馈型VSG技术。外环控制直接采用VSC输出电流作为反馈控制量,不仅能实现构网和电压/频率主动支撑功能,还能保证在故障状态下外环控制具备稳定平衡点,降低暂态同步失稳风险,同时还能实现稳态下的电流限幅控制。电压内环采用基于相量分析的虚拟阻抗自适应选取方法,依赖就地量测信息进行虚拟阻抗快速自适应调整,以抑制故障瞬间暂态冲击电流。在PSCAD/EMTDC中搭建详细电磁暂态仿真模型,并构建相应的物理验证平台,仿真和实验结果表明,所提方法可以较好地抑制故障瞬间暂态冲击电流。

考虑输入时滞的舵机伺服系统自适应指令滤波输出反馈控制

针对舵机伺服系统运行过程中存在复杂非线性以及信号输入时滞、使系统的精度降低,严重时甚至造成系统失稳的问题,提出了一种考虑输入时滞的自适应指令滤波输出反馈控制策略。首先,将系统中存在的输入时滞考虑为控制器信号输入时滞,给出舵机伺服系统状态方程,选用梯度下降法设计时滞估计律对未知时滞进行估计;其次,将系统中存在的复杂非线性统一为扰动,选用扩展状态观测器(ESO)加以估计,将观测的系统状态值用于设计控制量实现输出反馈控制;然后,选用指令滤波将高阶求导过程转化为求积分,实现信号滤波以抑制微分噪声;最后,基于Lyapunov-Krasovskii泛函稳定性定理证明控制器实现系统有界稳定。仿真及实验表明,所提的控制方法与传统反步控制方法、自抗扰控制和比例微分积分(PID)控制方法相比,响应时间分别提升了92%、88%和51%,跟踪精度分别提升了90%、84%和26%。

一类不确定级联链式非完整系统的自适应镇定控制

本文研究一类带有未建模动态及未知参数的级联链式非完整系统的自适应输出反馈镇定问题.通过构造动态增益观测器与自适应估计器,借助反步递推方法提出了一种新的自适应输出反馈镇定控制方案.本文应用切换控制策略克服了非完整系统不能够通过连续反馈实现镇定控制的困难.文中设计的控制律保证了闭环系统在原点渐近镇定且状态渐近收敛于零.仿真结果验证了算法的有效性.