Immersion and invariance‐based impedance control for electrohydraulic systems

This work deals with the impedance control of electrohydraulic systems based on the concept of immersion and invariance. In the first step, the impedance control task for a basic electrohydraulic system comprising a hydraulic cylinder and a 4/3 proportional valve is analyzed. In order to mitigate the problem of energetic inefficiency and the high demands on the dynamics of the valve, an extended electrohdydraulic system is proposed. By means of a suitable choice of the parameters and an immersion and invariance‐based controller strategy, a significant reduction of both energy consumption and required dynamics of the valve can be obtained. The feasibility of the proposed impedance control strategies is demonstrated by extensive simulation studies. Copyright © 2009 John Wiley & Sons, Ltd.     

基于动态结构自适应神经网络的不确定时滞系统跟踪控制

针对一类不确定时滞非线性系统,提出一种自适应跟踪控制器.首先采用Lyapunov-Krasovskii函数设计时滞补偿器,并构造其中的参数调节规律.再针对建模误筹及小确定非线性,引入动态结构自适应神经网络,其隐层神经元个数可以随着跟踪误差的增大而在线增加,以提高逼近精度.最后,用仿真示例表明本文所提方法是有效的.     

基于单位分解的一类非线性不确定系统跟踪控制设计

利用单位分解在紧致域上能够以任意给定精度逼近连续函数的性质,针对一类不确定非线性系统设计了带有自适应律的鲁棒自适应跟踪控制器．结果表明这种控制器可以使输出跟踪误差渐近收敛到零点的一个小邻域内,并保证闭环系统的所有状态一致有界．最后的仿真实例说明了该方法的有效性．     

基于迭代学习控制的移动机器人轨迹跟踪控制

为提高移动机器人对特定轨迹的重复跟踪能力,提出了采用开闭环PD型迭代学习控制算法对移动机器人进行轨迹跟踪控制的方法。建立了包含外界干扰的非完整约束条件下的轮式移动机器人运动学模型,给出了系统的控制算法和控制结构。仿真结果表明,采用开闭环PD型迭代学习控制算法对轨迹跟踪是可行有效的,收敛速度优于其他迭代学习算法。     

基于自适应阻抗控制的轴孔装配方法

提出了一种基于自适应阻抗控制的轴孔装配方法,它能根据得到的力信息,按照自适应调整律对机器人末端的参考位置进行修正,使得轴始终朝着减小卡阻力的方向运动,最终完成插轴入孔的动作.其算法简单,计算量小,修正量的计算可以在线进行,故能满足实时控制的要求.仿真结果表明了这种方法的有效性.     

基于FNN的覆冰机器人越障机械臂轨迹跟踪控制

覆冰机器人除冰时要跨越各种障碍物。采用卡尔曼滤波学习算法,将自适应模糊神经网络控制器用于覆冰机器人越障时的机械臂轨迹跟踪控制,解决了BP算法实时性差的问题。经过仿真实验论证,该方法对覆冰机器人越障时的机械臂轨迹跟踪控制具有很好的效果,表明控制策略和理论分析的可行性。     

Tracking control of mechanical systems via sliding Lagrangian

According to a classical theorem in mathematical physics, a mechanical system is completely defined by its Lagrangian. This property is utilized to design the tracking control of manipulators via a new family of sliding surfaces referred to as sliding Lagrangian surfaces and which exhibit some interesting features. They are physically meaningful. They create forces of reaction of low magnitude. They are intimately related to the second variation of the mechanical Lagrangian, in such a manner that one can refine the design by using a neighbouring-optimal control involving linear dynamic and quadratic cost. One can also combine the approach with the variable structure technique to achieve a good robustness with a low chattering phenomenon.     

基于智能优化的移动机器人轨迹跟踪控制

建立了机器人运动学模型,设计了基于Lyaponov稳定理论的轨迹跟踪控制器,该控制器的性能取决于其参数的大小。粒子群优化算法具有收敛速度快,需要调节的参数少等优点,但优化过程中容易发生“早熟”收敛,使优化陷入局部极小值。通过引入模拟退火算法、“交叉算子”和“变异算子”,提出了一种改进粒子群优化算法,对控制器的参数进行优化设计。最后,通过仿真计算,证明了该方法的有效性。     

基于预测值控制的变采样网络控制系统

利用节点采用事件–时间驱动方式建立了变采样网络控制系统, 在固定时延稳定控制的基础上, 根据预测控制值和预测反馈值给出该系统在变时延下所对应的状态转移矩阵, 研究了满足变采样网络控制系统稳定的预测误差和预测时间的条件, 最后给出了一个例子说明分析的结果.     

非最小相位系统跟踪控制综述

非最小相位系统是指包含不稳定零动态的系统.经典的跟踪控制理论,特别是非线性系统跟踪控制理论,是以最小相位系统为基础建立的,不能直接用于非最小相位系统.研究非最小相位系统跟踪控制理论,是对经典控制理论的扩展和补充,具有重要的意义.本文对目前非最小相位系统跟踪控制领域取得的成果进行综述.首先梳理各种非最小相位系统跟踪控制方法的基本思想,并按照近似跟踪和精确跟踪进行归类,建立非最小相位系统跟踪控制的基本框架.然后围绕该框架对各种方法进行详细介绍.接着讨论非最小相位系统的跟踪性能限制.最后总结现有研究存在的一些问题及对今后的发展方向进行展望.本文的目的在于使控制工作者对非最小相位系统的跟踪控制有一个较为清晰的认识.     

多智能体系统的旋转目标跟踪控制

介绍对一个旋转目标实现跟踪控制的多智能体系统协调控制问题.提出一个包含领航者及多个跟随者的多智能体系统,该领航者是一个进行匀速圆周运动的智能体,为实现对领航者的跟踪,设计一种能实现旋转跟踪控制的协议,并通过李雅普诺夫方法证明协议能实现旋转目标的跟踪控制.最后,通过数值仿真实验验证了所设计的协议的有效性.     

Haptic force control based on impedance/admittance control aided by visual feedback

This paper demonstrates a haptic device for interaction with a virtual environment. The force control is added by visual feedback that makes the system more responsive and accurate. There are two popular control methods widely used in haptic controller design. First, is impedance control when user motion input is measured, and then, the reaction force is fed back to the operator. The alternative method is admittance control, when forces exerted by user are measured and motion is fed back to the user. Both, impedance and admittance control are also basic ways for interacting with a virtual environment. In this paper, several experiments were performed to evaluate the suitability of force-impedance control for haptic interface development. The difference between conventional application of impedance control in robot motion control and its application in haptic interface development is investigated. Open loop impedance control methodology is implemented for static case and a general-purpose robot under open loop impedance control was developed as a haptic device, while a closed loop model based impedance control was used for haptic controller design in both static and dynamic case. The factors that could affect to the performance of a haptic interface are also investigated experimentally using parametric studies. Experimental results for 1 DOF rotational motion and 2 DOF planar translational motion systems are presented. The results show that the impedance control aided by visual feedback broaden the applicability of the haptic device and makes the system more responsive and accurate.

An estimation method of end-point impedance based on bilateral control system

ABSTRACT

This paper aims at developing an estimation method of end-point impedance. Human operators are constantly changing their end-point impedance for adapting to the surrounded environment and executing some complicated tasks, and it is highly meaningful to investigate these variations for the further understanding of human motion. Most of the conventional researches, however, have considered non-contact-point impedance or tasks that is only holding the vibrated sticks due to the experimental constraints. This paper proposes the estimation method of end-point impedance by using bilateral control system. The extra signal is added to the force controller for the impedance estimation. In addition, the effect of the bilateral controller is estimated and removed from the impedance estimation process for securing the applicability of moving tasks. The proposed method was validated through simulations and an experiment. The experimental result showed that the end-point stiffness can be estimated properly even if the operator robot was moving and changed its end-point impedance.     

Tracking in nonlinear differential-algebraic control systems with applications to constrained robot systems

We consider the design of a feedback control law for control systems described by a class of nonlinear differential-algebraic equations so that certain desired outputs track given reference inputs. The nonlinear differential-algebraic control system being considered is not in state variable form. Assumptions are introduced and a procedure is developed such that an equivalent state realization of the control system described by nonlinear differential-algebraic equations is expressed in a familiar normal form. A nonlinear feedback control law is then proposed which ensures, under appropriate assumptions, that the tracking error in the closed loop differential-algebraic system approaches zero exponentially. Applications to simultaneous contact force and position tracking in constrained robot systems with rigid joints, constrained robot systems with joint flexibility, and constrained robot systems with significant actuator dynamics are discussed.     

基于RBF神经网络的轮式移动机器人轨迹跟踪控制

针对一类非完整移动机器人的轨迹跟踪控制系统,提出一种基于RBF神经网络的滑模控制与转矩控制相结合的智能控制方法。该方法同时考虑机器人运动学和动力学模型,通过RBF神经网络进行移动机器人运动过程学习,与速度误差结合构成力矩控制器,可保证闭环误差系统一致最终渐进稳定。采用基于李亚普诺夫(Lyapunov)稳定性理论的判稳方法,证明整个闭环控制系统的稳定性。仿真结果表明,该控制方案具有较强的鲁棒性。     

基于BP神经网络的腱驱动灵巧手的自适应阻抗控制

考虑到机器人手指与物体接触以及外部扰动的情况,提出一个基于BP神经网络的自适应阻抗控制器。这种修正策略通过BP神经网络和阻抗控制结合完成,保证了系统的稳定性,并且提高系统对灵巧手指与外界工作环境接触时,接触力的自适应能力。实验结果表明,在存在外部扰动的情况下,所设计的基于BP神经网络的自适应阻抗控制器具有较好的控制效果。     

Linearizing control of induction motor based on networked control systems

A new approach to speed control of induction motors is developed by introducing networked control systems （NCSs） into the induction motor driving system. The control strategy is to stabilize and track the rotor speed of the induction motor when the network time delay occurs in the transport medium of network data. First, a feedback linearization method is used to achieve input-output linearization and decoupling control of the induction motor driving system based on rotor flux model, and then the characteristic of network data is analyzed in terms of the inherent network time delay. A networked control model of an induction motor is established. The sufficient condition of asymptotic stability for the networked induction motor driving system is given, and the state feedback controller is obtained by solving the linear matrix inequalities （LMIs）. Simulation results verify the efficiency of the proposed scheme.     

Geometric properties of linearizable control systems

In this paper the distributions associated with a non-linear system of the form $$\frac{{dx}}{{dt}} = f(x) + \sum\limits_{\alpha = 1}^m {u_\alpha (t)g_\alpha (x)} ,f(0) = 0andx \in U_0 \subset R^n$$ are studied in relation to nonlinear state feedback $$u(x,v) = \hat a(x) + \hat S(x)v$$ withâ, u, v ∈ R ^m and ? a nonsingularm×m matrix withâ, ? functions ofx. Bothf andg are vector fields onU ₀, generally assumed to be real analytic. Two nested families of distributions {G ^j } and {M ^j } associated with the system are examined with emphasis on generic points ofU ₀, where it is shown that the usual conditions for feedback linearizability contain some redundancy. A characterization of state linearizability in terms of invariant factors of the equivalent linear form are given, and a criterion in terms of the distributions for a type of partial linearization is found.     

基于多智能体的可重构网络化控制系统

提出了一种基于多智能体（Multi-Agent System,MAS）的可重构网络化控制系统体系结构,该系统中的各控制节点可根据实际工况重新配置并相互配合完成控制任务,从而有效提高系统的灵活性和可扩展性。利用面向对象Petri网给出了该可重构网络化控制系统系统的通信模型,并提出了一种带宽调度策略以确保其中数据传输的实时性。     

Fundamental properties of reset control systems

Reset controllers are linear controllers that reset some of their states to zero when their input is zero. We are interested in their feedback connection with linear plants, and in this paper we establish fundamental closed-loop properties including stability and asymptotic tracking. This paper considers more general reset structures than previously considered, allowing for higher-order controllers and partial-state resetting. It gives a testable necessary and sufficient condition for quadratic stability and links it to both uniform bounded-input bounded-state stability and steady-state performance. Unlike previous related research, which includes the study of impulsive differential equations, our stability results require no assumptions on the evolution of reset times.