非完整链式系统的时变光滑指数镇定

针对非完整链式系统,导出了一种时变光滑反馈控制律,该控制律可以保证系统状态全局指数收敛到原点,克服了以往控制律非光滑或虽光滑但却只能渐近镇定系统的缺陷.所得控制律应用于移动机器人系统的镇定.     

非完整向量幂式系统的光滑时变指数镇定

研究非完整向量幂式系统的镇定问题,通过引入一个辅助状态变量,此类系统可将转换成一个线性时变系统,由此可得至具有指数收敛率的光滑反馈控制律。该方法优点是控制律光滑并且设计过程简单,系统每个状态的收敛率可被事先确定。仿真结果表明,仿真结果表明了该方法的有效性。     

非完整系统的离散时间反馈镇定

讨论非完整系统的镇定问题。针对一类具有两个控制、三个状态的非完整系统，提出一种利用分段常值控制序列反馈镇定此类系统的策略，并以两杆平面空间机器人系统为例，验证了控制策略的有效性。     

具有时变时滞的不确定非完整系统的输出反馈镇定

针对一类含有状态时变时滞的不确定非完整系统, 提出一种输出反馈镇定控制算法. 通过应用不连续的输入-状态变换和缩放变换, 将原始研究系统转换为更利于反馈控制器设计的新系统. 基于此系统设计状态反馈控制律, 通过构造状态观测器、利用必然等价原理给出理想的输出反馈镇定控制器. 分析表明, 所设计的控制器能够使得闭环系统的状态渐近趋于零. 最后通过仿真实例表明了所提出控制策略的有效性.

     

一类非完整约束系统的镇定与能控性

考虑非完整约束系统的镇定与能控性问题. 文中首先证明了虽然一般地说这类系统不能由光滑反馈镇定, 但它的存在性依赖于初值. 当初值在一个零测集外时, 这种反馈镇定确实存在. 然后我们证明了这类系统在分段光滑控制下全局可控. 由于证明是构造性的, 它给出了相应的控制.     

控制受限的一类确定非完整动力学系统的镇定

利用滑动模态的方法,采用多步控制策略,对一类控制受限的不确定非完整动力学系统设计了镇定控制器,使得闭环系统的状态在有限时间内可收敛到原点的事先给定的任意小的ε领域中,最后,将该方法用于一类移动机器人的控制器设计,仿真结果验证了该方法的有效性。     

双体多驱动小车非完整约束点镇定问题的研究

推导了双体多驱动小车的运动学方程 ,并且给出了标准链式表达式 ,证明了双体车的镇定控制问题 .     

不确定非完整动力学系统的指数镇定

研究具有未知惯性参数非完整动力学系统的镇定问题,基于非连续变换和动力学方程的性质,设计出两类非线地指数镇定律－鲁棒控制和自适应控制律。将其用于一类移动机器人的位姿镇定,仿真结果验证了所提出控制方法的有效性。     

一类不确定非完整机器人的时变自适应镇定

通过对质心和几何中心不重合情况下两轮驱动移动机器人镇定问题的研究，提出了一种光滑时变控制律，并针对质心和几何中心距离参数未知的情况，利用自适应技术对其进行了修正. 证明了所提出的控制律可使该类型移动机器人的位姿从任意的初始状态指数收敛到原点．仿真试验验证了本文所提出控制律的有效性．     

Prescribed-time stabilization of p-normal nonlinear systems by bounded time-varying feedback

This article studies the prescribed-time stabilization problem of p-normal nonlinear systems by bounded time-varying high-gain feedback. A time-varying bounded controller, which can achieve prescribed-time stabilization, is designed via backstepping. Because of the usage of time-varying high-gain functions which grow unbounded as the time tends to the prescribed time, the usual separation technique is invalid. To solve this problem, a novel design scheme is proposed. It is shown that all of the closed-loop trajectories convergence to the origin in prescribed time. Finally, a numerical example verifies the effectiveness of the proposed method.     

Guaranteed cost output control for uncertain neutral systems with time-varying delays via LMI

In this paper, the robust guaranteed cost output control for a class of uncertain neutral system with time-varying delays is considered. Based on Lyapunov–Krasovskii functional theory, some stabilization criteria are derived and guaranteed costs are given. Delay-dependent and delay-independent criteria are proposed for the stabilization of the system. Static output linear feedback control is considered to stabilize the uncertain neutral system. Linear matrix inequality (LMI) approach and parametrizing transformation approach are used to solve the stabilization problems. A procedure for the controller design is provided. Optimal guaranteed cost output control will be achieved when the optimization problem under LMI conditions can be solved. Finally, two numerical examples are illustrated to show the use of the results.     

Exponential stabilization of nonholonomic dynamic systems by smooth time-varying control

A general dynamic model is proposed for describing a large class of nonholonomic systems including extended chained systems, extended power systems, underactuated surface vessel systems etc. By introducing an assistant state variable and a time-varying state transformation based on the concept of minimal dilation degree, this class of nonholonomic systems is transformed into linear time-varying control systems, and the asymptotic exponential stability is thus achieved by using a smooth time-varying feedback control law. The existence and uniqueness of the minimal dilation degree for the discussed systems are also proved under certain conditions.     

Adaptive output feedback control for nonholonomic systems with uncertain chained form

The output feedback adaptive control problem is investigated for nonholonomic systems with strongly nonlinear uncertainties and unknown virtual control directions. A nonlinear output feedback switching controller based on the output measurement of the first subsystem is employed in order to make the state scaling effective and ensure the convergence of the system states. The novel observer/estimator is introduced for state and unknown parameter estimates. The integrator backstepping technique by the use of a constructive recursive is applied to the design of the adaptive controller and to overcome the unknown virtual control directions. The simulation result validates the effectiveness of the proposed scheme.     

Tracking control design for nonholonomic mechanical systems with affine constraints

The trajectory tracking control is considered for nonholonomic mechanical systems with affine constraints and dynamic friction. A new state transformation is proposed to deal with affine constraints, and then an integral feedback compensation strategy is used to identify the dynamic friction. The proposed controller ensures that the output tracking errors converge to zero as t →∞.As an application, a detailed example is presented to illustrate the effectiveness of the control scheme.     

Stabilization of uncertain chained nonholonomic systems using adaptive output feedback

In this paper, adaptive output feedback control is presented to solve the stabilization problem of nonholonomic systems in chained form with strong nonlinear drifts and uncertain parameters using output signals only. The objective is to design adaptive nonlinear output feedback laws which can steer the closed‐loop systems to globally converge to the origin, while the estimated parameters remain bounded. The proposed systematic strategy combines input‐state scaling with backstepping technique. Motivated from a special case, adaptive output feedback controllers are proposed for a class of uncertain chained systems. The simulation results demonstrate the effectiveness of the proposed controllers. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Finite‐time tracking control of uncertain nonholonomic systems by state and output feedback

This paper studies the finite‐time tracking control of nonholonomic systems in chained form with parameter uncertainties, unknown output gains, and mismatched uncertainties. To achieve the finite‐time tracking control of uncertain nonholonomic systems, we propose 2 types of controllers by state and output feedback, respectively. Both of the proposed 2 types of controllers can achieve the finite‐time output tracking control of the nonholonomic systems even in the presence of mismatched uncertainties and/or unknown gains. The effectiveness of our proposed controllers are illustrated with simulation examples.     

Observer-based output feedback control of networked control systems with non-uniform sampling and time-varying delay

This paper investigates the problem of observer-based output feedback control for networked control systems with non-uniform sampling and time-varying transmission delay. The sampling intervals are assumed to vary within a given interval. The transmission delay belongs to a known interval. A discrete-time model is first established, which contains time-varying delay and norm-bounded uncertainties coming from non-uniform sampling intervals. It is then converted to an interconnection of two subsystems in which the forward channel is delay-free. The scaled small gain theorem is used to derive the stability condition for the closed-loop system. Moreover, the observer-based output feedback controller design method is proposed by utilising a modified cone complementary linearisation algorithm. Finally, numerical examples illustrate the validity and superiority of the proposed method.     

Adaptive neural optimal control via command filter for nonlinear multi-agent systems including time-varying output constraints

In this article, an optimal command-filtered backstepping control approach is proposed for uncertain strict-feedback nonlinear multi-agent systems (MASs) including output constraints and unmodeled dynamics. One-to-one nonlinear mapping (NM) is utilized to recast constrained systems as corresponding unrestricted systems. A dynamical signal is applied to cope with unmodeled dynamics. Based on dynamic surface control (DSC), the feedforward controller is designed by introducing error compensating signals. The optimal feedback controller is produced applying adaptive dynamic programming (ADP) and integral reinforcement learning (IRL) techniques in which neural networks are utilized to approximate the relevant cost functions online with established weight updating laws. Therefore, the entire controller, including feedforward and feedback controllers, not only ensures that all signals in the closed-loop systems are cooperative semi-globally uniformly ultimately bounded (SGUUB) and the outputs maintain in the provided time-varying constraints, but also makes sure that the cost functions achieve minimization. A simulation example is presented to illustrate the feasibility of the proposed control algorithm.