一类非线性MIMO系统的自适应模糊输出反馈控制

针对一类多输入多输出非线性系统设计了自适应模糊观测器和控制器。该方法不需要系统状态完全可测的条件，而是通过自适应模糊观测器估计系统的状态。采用基于状态估计的模糊基函数模型的模糊逻辑系统逼近非线性函数，并对模糊建模误差和外扰的存在采用了鲁棒补偿控制项以保证良好的观测与跟踪性能，该控制器保证了跟踪误差和观测误差的一致最终有界性。仿真结果表明所提出的方法具有良好的观测效果与跟踪效果。     

一类不确定非线性系统的鲁棒自适应控制

针对一类具有未知控制方向、未知参数以及未建模动态的非线性系统,提出了一种带有死区修正的鲁棒自适应递推控制策略.该策略不需要控制方向符号的先验知识.根据参数的上下界先验信息,分别将光滑投影算法和非连续投影算法与参数自适应律结合起来,既抑制了参数的漂移,又使估计参数达到了最小.算法保证了闭环系统所有信号的有界性,同时使得跟踪误差收敛于零的任意小邻域内.     

一类不确定非线性系统的鲁棒输出跟踪控制器

研究了一类不确定非线性系统的鲁棒输出跟踪问题 ,目的是在未满足不确定性匹配条件的情况下设计精确跟踪参考轨迹的状态反馈控制器。为了补偿不确定性 ,将鲁棒输出跟踪控制器的设计问题转化为最优控制器的设计问题。证明了鲁棒输出跟踪问题的解可通过最优控制的解而得到 ,通过仿真说明了这种设计方法是行之有效的。     

ADAPTIVE PRACTICAL OUTPUT MANEUVERING CONTROL FOR A CLASS OF NONLINEAR SYSTEMS

This paper deals with the adaptive practical output maneuvering control problems for a class of nonlinear systems with uncontrollable unstable linearization. The objective is to design a smooth adaptive maneuvering controller to solve the geometric and dynamic tasks with an arbitrary small steady tracking error. The method of adding a power integrator and the robust recursive design technique are employed to force the system output to track a desired path and make the tracking speed to follow a desired speed along the path. An example is considered and simulation results are given. The proposed design procedure can be illustrated by the use of this example.     

Sampled-Data Semi-Global Robust Output Regulation for a Class of Nonlinear Systems

This paper investigates the semi-global robust output regulation problem for a class of uncertain nonlinear systems via a sampled-data output feedback control law. What makes the results interesting is that the nonlinearities of the proposed system do not have to satisfy linear growth condition and the uncertain parameters of our system are allowed to belong to some arbitrarily large prescribed compact subset. Two cases are considered. The first case is that the exogenous signal is constant. The second case is that the exogenous signal is time-varying and bounded. For the first case,the authors solve the problem exactly in the sense that the tracking error approaches zero asymptotically. For the second case, the authors solve the problem practically in the sense that the steady-state tracking error can be made arbitrarily small. Finally, an example is given to illustrate the effectiveness of our approach.     

一类离散非线性系统反步递推黄金分割自适应控制

针对一类含参数不确定的离散时间严反馈非线性系统，提出了反步递推（Backstepping）算法与黄金分割原理相结合的新型控制策略。采用反步递推控制方法处理前n-2阶子系统，利用其结果重构余下的二阶非线性子过程，再通过黄金分割自适应算法对二阶子过程进行控制。该策略一方面解决了单纯反步递推算法在过渡阶段参数失配时，控制量剧烈波动的问题；另一方面减少了反步递推算法的计算量。给出了闭环系统有界稳定性的证明，并通过仿真实例验证了该反步递推黄金分割自适应控制方法的有效性和优越性。     

不确定非线性时滞系统的鲁棒可靠控制

研究一类不确定非线性时滞系统的状态反馈鲁棒可靠控制问题。系统包含状态时滞、控制输入时滞、参数不确定性和未知的非线性扰动。目的是设计线性无记忆状态反馈控制器 ,使得对于任意容许的不确定性以及在一个预先指定的执行器子集合中执行器的失效 ,相应的闭环系统渐近稳定。最后给出一个数值例子验证了所给结果的有效性     

一类非线性时滞系统的可靠控制设计

针对一类非线性时滞系统 ,首先不考虑故障情况 ,设计了一种控制器 ,使得系统在控制器的作用下 ,对于任意的初始状态都能控制到原点。然后针对可能发生的故障 ,利用神经网络的在线建模能力 ,以其输出作为原有控制律的附加控制信号来补偿故障对系统的影响 ,从而构成了一种可靠控制器 ,实现了该类系统的可靠控制。     

不确定非线性系统变结构模糊自适应鲁棒控制

考虑一类不确定非线性系统的鲁棒控制器设计问题,在假设系统不确定性函数结构未知的情况下,利用模糊系统对不确定性函数进行逼近,将获得的模糊系统函数作为系统不确定性界函数。在此基础上,提出了一种变结构模糊自适应鲁棒控制算法,该算法在确保系统的滑动模态超平面为渐近可达的前提下,在线对系统模型的控制增益参数和不确定性函数的界参数进行估计。最后以船舶减摇鳍非线性控制系统为例,进行了变结构鲁棒自适应模糊控制器的设计。仿真研究表明,所提出的算法是有效的。     

Adaptive Stabilization for a Class of Feedforward Systems with Zero-Dynamics

This paper investigates adaptive state feedback stabilization for a class of feedforward nonlinear systems with zero-dynamics,unknown linear growth rate and control coefficient.For design convenience,the state transformation is first introduced and the new system is obtained.Then,the estimation law is constructed for the unknown control coefficient,and the state feedback controller is proposed with a gain updated on-hne.By appropriate choice of the estimation law for the control coefficient and the dynamic gain,the states of the closed-loop system are globally bounded,and the state of the original system converges to zero.Finally,a simulation example is given to illustrate the correctness of the theoretical results.     

基于状态观测器的非线性系统神经网络自适应控制

结合高增益观测器,针对相对阶为n的非线性系统,设计了神经网络自适应控制器。利用Lyapnov定理获得了神经网络权值的更新律和控制器的控制律,从而确保了整个闭环系统的稳定性和有界性。由于神经网络不需任何的离线训练,因而该控制器能够广泛应用于一大类非线性性系统的控制中。仿真结果验证了控制方案的有效性。     

Formation Tracking for Nonlinear Multi-agent Systems with Input and Output Quantization via Adaptive Output Feedback Control

Signal quantization can reduce communication burden in multi-agent systems, whereas it brings control challenge to multi-agent formation tracking. This paper studies the output feedback control problem for formation tracking of multi-agent systems with both quantized input and output.The agents are described by a nonlinear dynamic model with unknown parameters and immeasurable states. To estimate immeasurable states and solve the uncertainties, state observers are developed by using dynamic high-gain tools. Through proper parameter designs, an output feedback quantized controller is established based on quantized output signals, and the quantization effect on the control system is eliminated. Stability analysis proves that, with the proposed control scheme, multi-agent systems can track the reference trajectory while forming and maintaining the desired formation shape.In addition, all the signals in the closed-loop systems are bounded. Finally, the numerical simulation and practical experiment are provided to verify the theoretical analysis.     

一类不确定混沌系统的自适应模糊同步控制

针对一类带有未知非线性函数、参数和外界干扰的混沌系统,通过将一个时变参数引入到带有非线性后件的T-S模糊逻辑系统中,结合自适应方法对未知参数进行在线估计,完成了自适应模糊同步控制器的设计,并实现了驱动-响应混沌系统的渐近同步。一般而言,带有非线性后件的T-S模糊逻辑系统具有更高的逼近能力,可用更少的规则去逼近主从系统中的未知非线性函数,且在同步控制器的设计过程中,参数自适应律的个数与模糊规则的个数无关。因此,该同步方法不仅减少了在线运算量,而且通过直觉推理生成规则少、解释性强的模糊逻辑系统具有更广泛的应用。最后所给数值仿真算例说明了该方法的有效性。     

一类非线性系统的鲁棒自适应控制

针对一类含有不确定参数和未知扰动的非线性系统，提出一种鲁棒自适应控制方法以确保系统输出稳定地精确跟踪给定的参考信号。控制器的设计分两步进行：首先，在不考虑扰动的情况下，采用一种基于参数映射的Lyapunov设计方法设计系统参数自适应控制器；然后，在该自适应控制器的基础上，采用衰减控制策略设计鲁棒补偿器，实现对扰动的抑制。最后通过数字仿真验证了设计方案的有效性。     

A Robust Output—Feedback Controller for a Class of Uncertain Nonlinear Systems

1　IntroductionRecently,the nonlinear output- feedback control problems are solved successfully by usingbackstepping for a class of nonlinear systems. The partialstate feedback control problemsolved in Jiang and Praly,1996 is more general than the output- feedback control problem.However,the assumptions made in the paper are too restrictive which does not only re-quire the existence of c,γ andψ1 to be ascertained a priori,but also require them to beknown for an unknown system. If c,γ can n…     

一类带非线性扰动不确定系统的脉冲控制

在实际系统中,总存在各种干扰。针对一类带非线性扰动的线性不确定系统,采用脉冲控制的方法来实现鲁棒镇定,提出了脉冲控制下新的鲁棒可镇定判据,并通过实例仿真验证了所得结果的有效性。     

非线性多智能体系统分布式鲁棒输出调节

为解决具有一般非线性形式和不确定参数的多智能体系统的协调控制问题,设计了非线性分布式反馈控制器,使得多智能体系统鲁棒渐近跟踪参考信号或者鲁棒渐近抑制干扰。在所考虑的多智能体系统中,将动态领导者或者环境干扰看作是产生参考信号或者干扰信号的外部系统。最后,给出一个仿真算例,验证所得结果的有效性。     

OUTPUT FEEDBACK CONTROL FOR MIMO NONLINEAR SYSTEMS WITH EXOGENOUS SIGNALS

The paper addresses the global output tracking of a class of multi-input multi-output （MIMO） nonlinear systems affected by disturbances, which are generated by a known exosystem. An adaptive controller is designed based on the proposed observer and the backstepping approach to asymptotically track arbitrary reference signal and to guarantee the boundedness of all the signals in the closed loop system. Finally, the numerical simulation results illustrate the effectiveness of the ProPosed scheme.     

基于神经网络的非线性系统的间接自适应控制

针对一类不确定非线性动态系统 ,利用多层神经网络系统MNNs的逼近能力 ,提出了一种间接鲁棒自适应神经网络控制器的设计方案。该方案不仅能够保证闭环系统的所有信号有界 ,而且理论分析证明了闭环系统的跟踪误差渐近收敛到零。仿真试验表明本控制算法是有效的。