基于输入输出线性化的自适应模糊滑模航迹控制

针对船舶直线航迹控制的非线性特性,设计一种基于输入输出线性化的自适应模糊滑模控制器,并利用Lyapunov理论,证明该系统在所设计控制器作用下全局渐近稳定,Simulink仿真结果表明,所设计控制器能够有效抑制常规滑模所固有的稳态抖振现象,且在参数摄动及风浪干扰下具有强鲁棒性,较好的实现了对设定航迹的跟踪。     

Connections between finite-gain and asymptotic stability

The relationship between input-output and Lyapunov stability properties for nonlinear systems is studied. Well-known definitions for the input-output properties of finite-gain and passivity, even with quite reasonable minimality assumptions on a state-space representation, do not necessarily imply any form of stability for the state. Attention is given to the precise versions of input-output and observability properties which guarantee asymptotic stability. Particular emphasis is given to the possibility of multiple equilibria for the dynamical system.     

A link between input-output stability and Lyapunov stability

It is shown that incremental boundedness of an input-output operator ensures global asymptotic stability of any motion. A reciprocal statement is set.     

Analysis of stability and stabilization of cascade systems with time delay in terms of linear matrix inequalities

The stability of nonlinear cascade systems with a time delay is studied. Conditions of the global asymptotic stability in terms of linear matrix inequalities for a finite set of matrices are obtained. The problem of stabilization of the controlled delay system is considered, which is solved based on the stability conditions. The proposed approach to the analysis of qualitative properties and to the solution of stabilization problems is based on the results concerning the asymptotic stability of the delay linear systems, the decomposition of the original system, and the representation of the delay nonlinear system by a Takagi–Sugeno system. Examples illustrating the simplification of the system analysis by reducing its size and decreasing the number of linear matrix inequalities are discussed.     

A condition for the stability of switched nonlinear systems

In this paper, we present a sufficient condition for the global asymptotic stability of a switched nonlinear system composed of a finite family of subsystems. We show that the global asymptotic stability of each subsystem and the pairwise commutation of the vector fields that define the subsystems (i.e., the Lie bracket of any pair of them is zero) are sufficient for the global asymptotic stability of the switched system. We also show that these conditions are sufficient for the existence of a common Lyapunov function.     

一类非线性系统的全局渐近稳定和有限时间镇定

针对一类全矩阵形式的非线性系统, 研究其全局稳定性及有限时间镇定问题. 首先, 全矩阵形式非线性系统被分成上三角形式和下三角形式非线性系统的加和, 并针对下三角形式非线性系统, 利用加幂积分方法, 自上而下地设计系统的全局稳定控制器; 其次, 在上面控制器作用下, 证明全矩阵形式系统在一个给定领域内是局部渐近稳定的; 最后, 运用自下而上的顺序, 一种嵌套饱和方法被用到上述控制器中, 通过调节饱和度, 使得闭环系统全局渐近稳定. 此外, 在适当的条件下, 可以得到全矩阵形式非线性系统的全局有限时间稳定性.     

基于输入输出线性化的船舶全局直线航迹控制

针对水面船舶直线航迹控制系统的非线性数学模型,基于输入输出线性化技术,给出了一类重定义输出变量和采用该输出变量的状态反馈控制律,并得到了保证系统全局渐近稳定的充分条件．数值仿真和模拟试验结果表明,所提出的充分条件能够保证船舶航迹控制全局渐近稳定,设计的控制律具有比较理想的控制效果．     

受多随机噪声和多随机脉冲干扰的非线性系统稳定性分析

针对一类受多有色噪声和多随机脉冲干扰的非线性系统(其中系统连续动态中的多随机噪声包含乘性和加性有色噪声且离散动态中多随机脉冲幅值的类型由一个齐次不可约非周期Markov链决定),分别提出概率意义和矩意义下的噪声-状态稳定性、概率意义下的全局渐近稳定性、矩意义下的指数稳定性判据.在脉冲数量受模态依赖平均脉冲区间约束下,首先基于乘性随机噪声的估计和Lyapunov函数方法,分别研究系统在矩意义下的噪声到状态稳定性和指数稳定性判据;然后基于乘性随机噪声满足大数定律的假设和Lyapunov函数方法,分别给出系统在概率意义下的噪声-状态稳定和全局渐近稳定的充分条件;最后通过仿真结果验证所提出稳定性判别准则的有效性.     

On delay-dependent stability for vector nonlinear stochastic delay-difference equations with Volterra diffusion term

Global asymptotic stability conditions for discrete vector nonlinear stochastic systems with state delay and Volterra diffusion term are obtained based on the convergence theorem for semimartingale inequalities, without assuming the Lipschitz conditions for nonlinear drift functions. The derived stability conditions are directly expressed in terms of the system coefficients. A number of nontrivial examples of nonlinear systems satisfying the obtained stability conditions are given. The obtained results are compared to some previously known asymptotic stability conditions for discrete nonlinear stochastic systems.     

Robust control design of a class of nonlinear input- and state-constrained systems

This work focuses on control design for input-output feedback linearizable nonlinear systems with bounded inputs and state constraints in the presence of uncertainty. Controllers based on Lyapunov’s direct method have been synthesized before for this class of nonlinear systems to enforce asymptotic stability in the presence of bounded inputs. However, none of these controllers accounts explicitly for state constraints. In order to address this task, we propose an optimization-based design method for which two properties will be guaranteed simultaneously despite parametric uncertainty, namely, closed-loop stability with bounded inputs and feasibility of the transient in the presence of state constraints.     

动态神经网络的输入2状态稳定性分析

针对非自治的动态神经网络系统，建立了动态神经网络的数学模型．并将其等效成一个非线性仿射控制系统．深入分析了该系统平衡点的存在性、唯一性和全局渐近稳定性，给出了系统输入-状态稳定的充分条件，构建了ISS-Lyapunov函数，并应用该函数确保了系统的全局渐近稳定性．     

时滞标准神经网络模型及其应用

提出一种新的神经网络模型---时滞标准神经网络模型(DSNNM),它由线性动力学系统和有界静态时滞非线性算子连接而成.利用不同的Lyapunov泛函和S方法推导出DSNNM全局渐近稳定性和全局指数稳定性的充分条件,这些条件可表示为线性不等式(LMI)形式.大多数时滞(或非时滞)动态神经网络(DANN)稳定性分析或神经网络控制系统都可以转化为DSNNM,以便用统一的方法进行稳定性分析或镇定控制.从DSNNM应用于时滞联想记忆(BAM)神经网络的稳定性分析以及PH中和过程神经控制器的综合实例,可以看出,得到的稳定性判据扩展并改进了以往文献中的稳定性定理,而且可将稳定性分析推广到非线性控制系统的综合.     

Global PID Control of Robot Manipulators Equipped with PMSMs

This paper is concerned with PID position regulation of robot manipulators actuated by permanent magnet synchronous motors (PMSMs). We present a global asymptotic stability proof when the electric dynamics of these actuators is taken into account. Our controller is so simple that it differs from standard field oriented control (SFOC) of PMSMs in only three simple nonlinear terms that have to be added and a nonlinear PID controller which is used instead of a classical PID controller. Thus, our proposal represents the closest result to SFOC of PMSMs provided with a formal global asymptotic stability proof. We present an advancement, if modest, towards presenting a global stability proof for SFOC when used in robotics.     

Asymptotic stabilization of dynamically quantized nonlinear systems in feedforward form

This paper studies the stabilizability of an n-dimensional quantized feedforward nonlinear system. The state of that system is first quantized into a finite number of bits, and then sent through a digital network to the controller. We want to minimize the number of transmitted bits subject to maintaining asymptotic stability. In the prior literature, n bits are used to stabilize the n-dimensional system by assigning one bit to each state variable (dimension). Under the stronger assumption of global Lipschitz continuity, this paper extends that result by stabilizing the system with a single bit. Its key contribution is a dynamic quantization policy which dynamically assigns the single bit to the most “important” state variable. Under this policy, the quantization error exponentially converges to 0 and the stability of the system can, therefore, be guaranteed. Because 1 is the minimum number of quantization bits (per sampling step), the proposed dynamic quantization policy achieves the minimum stabilizable bit number for that n-dimensional feedforward nonlinear system.     

Asymptotic stability equals exponential stability, and ISS equals finite energy gain — if you twist your eyes

In this paper we show that uniformly global asymptotic stability for a family of ordinary differential equations is equivalent to uniformly global exponential stability under a suitable nonlinear change of variables. The same is shown for input-to-state stability and input-to-state exponential stability, and for input-to-state exponential stability and a nonlinear H_∞ estimate.     

Global stability analysis scheme for a class of nonlinear time delay systems

We consider a class of nonlinear time delay systems created by generalizing the model for FAST TCP, an Internet congestion control algorithm. We achieve a time delay independent sufficient condition for the global asymptotic stability of the class of systems. The sufficient condition is verified by constructing two sequences that represent the lower and upper bound variations of the system trajectory in time, and showing that the two sequences converge to the equilibrium point of the system. The simulation results exemplify that the sufficient condition is valid for global asymptotic stability, and that the sufficient condition is a close approximation to the unknown necessary and sufficient condition for global asymptotic stability.     

Connections between Razumikhin-type theorems and the ISS nonlinearsmall gain theorem

A Razumikhin-type theorem that guarantees input-to-state stability for functional differential equations with disturbances is established using the nonlinear small-gain theorem. The result is used to show that input-to-state stabilizability for nonlinear finite-dimensional control systems is robust, in an appropriate sense, to small time delays at the input. Also, relaxed Razumikhin-type conditions guaranteeing global asymptotic stability for differential difference equations are given     

Delayed standard neural network models for control systems.

In order to conveniently analyze the stability of recurrent neural networks (RNNs) and successfully synthesize the controllers for nonlinear systems, similar to the nominal model in linear robust control theory, the novel neural network model, named delayed standard neural network model (DSNNM) is presented, which is the interconnection of a linear dynamic system and a bounded static delayed (or nondelayed) nonlinear operator. By combining a number of different Lyapunov functionals with S-procedure, some useful criteria of global asymptotic stability and global exponential stability for the continuous-time DSNNMs (CDSNNMs) and discrete-time DSNNMs (DDSNNMs) are derived, whose conditions are formulated as linear matrix inequalities (LMIs). Based on the stability analysis, some state-feedback control laws for the DSNNM with input and output are designed to stabilize the closed-loop systems. Most RNNs and neurocontrol nonlinear systems with (or without) time delays can be transformed into the DSNNMs to be stability-analyzed or stabilization-synthesized in a unified way. In this paper, the DSNNMs are applied to analyzing the stability of the continuous-time and discrete-time RNNs with or without time delays, and synthesizing the state-feedback controllers for the chaotic neural-network-system and discrete-time nonlinear system. It turns out that the DSNNM makes the stability conditions of the RNNs easily verified, and provides a new idea for the synthesis of the controllers for the nonlinear systems.     

Global stabilization of nonlinear cascade systems

We present sufficient conditions for the global stabilizability of two cascade connected nonlinear systems. These are based on general results concerning global asymptotic stability of triangular systems which are proved in the last section. For polynomial systems, in particular, the stabilizing feedback is given explicitly.