一类参数未知混沌系统的鲁棒自适应控制

研究一类含有动态不确定性及未知参数的混沌系统控制问题。基于递推控制方法，通过自适应机制来在线辩识系统未知参数，同时在设计控制器的过程中逐步引入镇定因子，以消除系统不确定性的影响，最终得到一个鲁棒控制器，使得闭环系统渐近稳定。仿真结果表明了该控制策略的有效性。     

输入具有齿隙非线性特性的周期系统的自适应控制

针对一类输入含齿隙非线性动态特性的周期时变系统, 在周期不确定性可时变参数化的条件下设计自适应控制器. 对周期时变参数进行傅里叶级数展开, 并采用微分自适应律估计未知傅里叶系数和齿隙动态特性参数, 通过鲁棒方法消除截断误差和齿隙模型的有界误差项对系统性能的影响. 采用双曲函数替代符号函数确保控制器可微, 同时能有效抑制颤振. 引入Δ函数, 避免参数估计发散, 并保证系统输出渐近跟踪理想轨迹. 理论分析与仿真结果表明, 闭环系统所有信号有界.     

一类带死区输入的非线性不确定系统滑模自适应控制

研究一类参数不确定和带有未知死区的非线性系统滑模自适应控制问题。将死区分解为两部分,被控系统中有两类不确定性的系统参数,一类是常值的未知系统参数;另一类是时变的未知系统参数和部分未知的死区。采用滑模控制和自适应控制相结合的方式,第一类不确定性可以由自适应控制来处理,而第二类不确定性可以由滑模控制来处理,即滑模自适应控制器。为了消除滑模控制所带来的抖振,引入边界层。采用’Lyapunov函数证明了系统的稳定性。仿真实验表明方法的可行性。     

控制方向未知的二阶时变非线性系统自适应迭代学习控制

对一类二阶严格反馈时变非线性系统的自适应迭代学习控制问题进行了研究.系统中含有非周期时变参数化不确定性且控制方向未知.首先,提出了一种神经网络估计器,实现了对未知非周期时变非线性函数的逼近.随后,用Nussbaum函数对未知控制方向进行了自适应估计,并综合应用baCkstcpping技术和自适应迭代学习控制技术设计了控制器.所设计的控制器能保证系统所有状态量在Lpe-范数意义下有界,且系统的输出量在LT2-范数意义下收敛到期望轨迹.最后的仿真研究证明了控制器设计方法的有效性.     

一类非线性系统的自适应无源化控制

讨论了一类含未知参数的非线性系统的自适应无源化问题.通过引入切换拓宽可反馈无源化对象的范围,在控制项前面的系数是未知参数线性函数的条件下构造出自适应无源反馈规律.在该条件不满足时,基于无源性分析给出了鲁棒自适应控制器,可以保证闭环系统是全局渐近稳定的.仿真结果表明了所提出算法的有效性.     

鲁棒自适应模糊控制器在复杂系统中的应用

在利用T-S模糊模型对未知函数逼近的基础上,针对一类含未知非线性函数和外界干扰的复杂系统,设计一种直接鲁棒自适应模糊控制器。此控制器学习参数只有一个,工程技术上容易实现。通过对达芬强迫振荡系统仿真,验证了该方案的有效性。     

非对称饱和扇形输入非线性系统的自适应模糊控制

针对一类具有未知不确定性,且状态不可测的非线性系统,考虑了输入端的饱和非对称扇区非线性特性影响,提出了系统模型未知情形下基于自适应模糊观测器的跟踪控制方案,采用Lyapunov-Krasovskii函数给出了滑模控制器参数和模糊逻辑的自适应调整律.所提方法不仅可保证闭环跟踪系统的稳定性,还削弱了传统方法对模型结构的依赖...     

一类时变系统鲁棒自适应状态反馈控制的稳定性分析

针对一类离散线性时变参数系统,给出了一种自适应状态反馈控制器,系统的时变参数是已知有界实函数和未知常数的线性组合,该控制器由带有死区的最小二乘辨识算法,状态反馈控制算法和状态观测器构成,文中详细地分析了闭环系统在有界外部干扰和小未建模不确定性影响下的全局稳定性和鲁棒性。     

基于自适应模糊逻辑系统的一类混沌系统同步控制

针对一类带有未知函数和干扰的混沌系统,进行了基于自适应模糊逻辑系统的自适应同步控制器的设计。首先基于模糊逼近原理,通过对该混沌系统中未知函数的输入输出进行采样,根据采样数据信息设计出具有参数自适应功能的Mamdani型模糊逻辑系统;然后利用该模糊逻辑系统给出一种带有参数自适应的驱动响应同步控制器设计方法;最后通过数值仿真算例表明了该方法的有效性。     

一类非齐次高阶非线性系统的自适应控制设计

本文讨论了一类具有未知参数的非齐次高阶非线性系统的全局强稳定自适应控制器的设计问题,定义了一个时变未知参数和一列非齐次辅助函数,通过增加辅助函数的积分项的方法并结合自适应控制技术,放宽了目前已有结论中对非线性项的限制,给出了使系统全局强稳定的连续自适应控制器存在的一个充分条件,给出了它的自适应状态反馈控制器的递推设计方法,并通过一个例子验证了文章的理论结果.     

Adaptive backstepping sliding mode control with tuning functions for nonlinear uncertain systems

An adaptive backstepping tuning functions sliding mode controller is proposed for a class of strict-feedback nonlinear uncertain systems. In this control design, adaptive backstepping is used to deal with unknown or uncertain parameters and the matching condition restricting the Lyapunov based design. The main drawback of the Lyapunov based adaptive backstepping which is the overparametrisation is eliminated by the tuning functions. The adaptive backstepping tuning functions design is combined with the sliding mode control in order to overcome quickly varying parametric and unstructured uncertainties, and to obtain chattering free control. The proposed controller not only provides robustness property against uncertainty but also copes with the overparametrisation problem. Experimental results of the proposed controller are compared with those of the standard sliding mode controller. The proposed controller exhibits satisfactory transient performance, good estimates of the uncertain parameters, and less chattering.     

Finite-time tracking control for strict-feedback nonlinear systems with full state constraints

In this paper, an adaptive finite-time controller is considered for a class of strict-feedback nonlinear systems with parametric uncertainties and full state constraints. Novel tan-type barrier Lyapunov functions are proposed to ensure the boundedness of the fictitious state tracking errors. A new tuning function is constructed to eliminate the effect of uncertainties by using the extended finite-time stability condition. It is shown that under the proposed backstepping control scheme the finite-time convergence of system output tracking error to a small set around zero is realised and the full state constraints are not violated. A numerical example is provided to demonstrate the effectiveness of the proposed finite-time control scheme.     

Adaptive fuzzy H/sub /spl infin// stabilization for strict-feedback canonical nonlinear systems via backstepping and small-gain approach

A novel adaptive fuzzy controller with H/sub /spl infin// performance is proposed for a wide class of strict-feedback canonical nonlinear systems. The systems may possess a class of uncertainties referred to as unstructured uncertain functions, which are not linearly parameterized and have no prior knowledge of the bound. The Takagi-Sugeno-type fuzzy logic systems are used to approximate the uncertainties and a systematic design procedure is developed for synthesis of adaptive fuzzy control with H/sub /spl infin// performance, which combines the backstepping technique and generalized small gain approach. The method preserves the three advantages, those are, the semiglobal uniform ultimate bound of adaptive control in the presence of unstructured uncertainties can be guaranteed, the adaptive mechanism with only one learning parameter is obtained and the possible controller singularity problem in some of the existing adaptive control schemes with feedback linearization techniques can be removed. Performance and limitations of proposed method are discussed and illustrated with simulation results.     

Robust adaptive fuzzy tracking control for a class of perturbed strict-feedback nonlinear systems via small-gain approach

This paper presents a novel robust adaptive fuzzy tracking controller (RAFTC) for a wide class of perturbed strict-feedback nonlinear systems with both unknown system and virtual control gain nonlinearities. For unknown system nonlinearities, two types for them are included: one naturally satisfies the “triangularity condition” and may possess a class of unstructured uncertain functions which are not linearly parameterized, while the other is partially known and consists of parametric uncertainties and known “bounding functions”. The Takagi–Sugeno type fuzzy logic systems are used to approximate unknown system nonlinearities and a systematic design procedure is developed for synthesis of RAFTC by combining the backstepping technique and generalized small-gain approach. The algorithm proposed is highlighted by three advantages: (i) the semi-global uniform ultimate bound of RAFTC in the presence of perturbed uncertainties and unknown virtual control gain nonlinearities can be guaranteed, (ii) the adaptive mechanism with minimal learning parameterizations is obtained and (iii) the possible controller singularity problem in some of the existing adaptive control schemes with feedback linearization techniques can be removed. Performance and limitations of proposed method are discussed and illustrated with simulation results.     

Robust adaptive control of a class of nonlinear strict-feedback discrete-time systems with exact output tracking

In this paper, adaptive control is studied for a class of single-input–single-output (SISO) nonlinear discrete-time systems in strict-feedback form with nonparametric nonlinear uncertainties of the Lipschitz type. To eliminate the effect of the nonparametric uncertainties in an unmatched manner, a novel future states prediction is designed using states information at previous steps to compensate for the effect of uncertainties at the current step. Utilizing the predicted future states, constructive adaptive control is developed to compensate for the effects of both parametric and nonparametric uncertainties such that global stability and asymptotical output tracking is achieved. The effectiveness of the proposed control law is demonstrated in the simulation.     

Adaptive dynamic surface control for disturbance attenuation of nonlinear systems

This paper proposes an adaptive dynamic surface control (DSC) approach for disturbance attenuation of uncertain nonlinear systems in the parametric strict-feedback form. In the proposed control system, a smooth projection algorithm is employed to train uncertain parameters. The proposed DSC system can overcome the complexity of an actual controller caused by the recursive differentiation of virtual controllers and parameter adaptation laws in the backstepping design procedure. From Lyapunov stability analysis, it is shown that the proposed controller has H_∞ tracking performance to attenuate external disturbances     

Robust adaptive asymptotic tracking of nonlinear systems with additive disturbance

This note deals with the tracking control of multiple-input-multiple-output (MIMO) nonlinear parametric strict-feedback systems in the presence of additive disturbances and parametric uncertainties. For such systems, C/sup 0/ robust adaptive controllers usually cannot ensure asymptotic tracking or even regulation. In this work, under the assumption the disturbances are C/sup 2/ with bounded time derivatives, we present a C/sup 0/ robust adaptive control construction that guarantees the tracking error is asymptotically driven to zero.     

Adaptive Dynamic Surface Control for Stabilization of Parametric Strict-Feedback Nonlinear Systems With Unknown Time Delays

The robust stabilization method via the dynamic surface control (DSC) is proposed for uncertain nonlinear systems with unknown time delays in parametric strict-feedback form. That is, the DSC technique is extended to state time delay nonlinear systems with linear parametric uncertainties. The proposed control system can overcome not only the problem of ldquoexplosion of complexityrdquo inherent in the backstepping design method but also the uncertainties of the unknown time delays by choosing appropriate Lyapunov-Krasovskii functionals. In addition, we prove that all the signals in the closed-loop system are semiglobally uniformly bounded. Finally, an example is provided to illustrate the effectiveness of the proposed control system.     

基于S类函数的严格反馈非线性周期系统的自适应控制

针对一类严格反馈非线性周期系统, 在周期非线性可时变参数化的条件下设计自适应控制器. 通过将周期时变参数展开成傅里叶级数, 并采用微分自适应律估计未知系数, 进行控制器反推设计. 引入S类函数, 并在控制器设计中应用S类函数处理截断误差项对系统跟踪性能的影响, 同时, S类函数能确保虚拟控制的可微. 给出几种不同的S类函数设计, 分析比较将其应用于控制器设计时产生的不同效果. 理论分析与仿真结果表明, 提出的控制方法能够实现系统输出跟踪期望轨迹, 且闭环系统所有信号有界.