Robust trajectories following control of a 2-link robot manipulator via coordinate transformation for manufacturing applications

A common idea concerning trajectory control of robot manipulators is to tackle the motion of the end-effector. According to traditional trajectory designs, a prescribed profile in a work space is first decomposed into independent joint positions such that the success in a contouring task lies with good tracking capability of individual joints. To advance trajectory control precision without relying on high tracking performance, a contour control strategy for a robot manipulator is presented in this paper. Different from the traditional concept of trajectory control, a contour following control strategy is developed via a coordinate transformation scheme. The main advantage of the proposed control architecture is that the final contouring accuracy will not be degraded in case the tracking performance of the robot manipulator is not good enough. Moreover, using a concept of variable structure control theory, a smooth robust control algorithm is realized in the form of proportional control plus an integration term. The robustness of the control algorithm is also demonstrated. A number of experiments are conducted to demonstrate the advantage of the trajectories following control framework and validate the feasibility of the proposed controller.     

Generalized Hamilton–Jacobi–Bellman Formulation -Based Neural Network Control of Affine Nonlinear Discrete-Time Systems

In this paper, we consider the use of nonlinear networks towards obtaining nearly optimal solutions to the control of nonlinear discrete-time (DT) systems. The method is based on least squares successive approximation solution of the generalized Hamilton-Jacobi-Bellman (GHJB) equation which appears in optimization problems. Successive approximation using the GHJB has not been applied for nonlinear DT systems. The proposed recursive method solves the GHJB equation in DT on a well-defined region of attraction. The definition of GHJB, pre-Hamiltonian function, HJB equation, and method of updating the control function for the affine nonlinear DT systems under small perturbation assumption are proposed. A neural network (NN) is used to approximate the GHJB solution. It is shown that the result is a closed-loop control based on an NN that has been tuned a priori in offline mode. Numerical examples show that, for the linear DT system, the updated control laws will converge to the optimal control, and for nonlinear DT systems, the updated control laws will converge to the suboptimal control.     

Generalized hamilton-jacobi-bellman formulation -based neural network control of affine nonlinear discrete-time systems

In this paper, we consider the use of nonlinear networks towards obtaining nearly optimal solutions to the control of nonlinear discrete-time (DT) systems. The method is based on least squares successive approximation solution of the generalized Hamilton-Jacobi-Bellman (GHJB) equation which appears in optimization problems. Successive approximation using the GHJB has not been applied for nonlinear DT systems. The proposed recursive method solves the GHJB equation in DT on a well-defined region of attraction. The definition of GHJB, pre-Hamiltonian function, HJB equation, and method of updating the control function for the affine nonlinear DT systems under small perturbation assumption are proposed. A neural network (NN) is used to approximate the GHJB solution. It is shown that the result is a closed-loop control based on an NN that has been tuned a priori in offline mode. Numerical examples show that, for the linear DT system, the updated control laws will converge to the optimal control, and for nonlinear DT systems, the updated control laws will converge to the suboptimal control.     

一种基于对策论的拥塞控制方法

大部分端到端拥塞控制机制假设端用户是"合作"的,并且它们的实现严重依赖于这个假设.但是当网络中有"不合作用户"出现时,将可能因为不公平的资源竞争(如带宽)而发生拥塞甚至导致拥塞崩溃.现有的拥塞控制方法不能很好地解决这个问题.提出了一种基于对策论的拥塞控制方法--有效违规用户惩罚算法,它把网络上非合作用户竞争资源看成N人非合作对策.算法具有"惩恶扬善"的功能,并使得对策存在着唯一的纳什均衡,从而解决了存在"非合作用户"而导致的拥塞问题.仿真结果证明了算法的有效性.     

Observer-based event-triggered containment control of multi-agent systems with time delay

This paper studies the containment control of general linear multi-agent systems with or without time delay. The observer-based event-triggered control schemes will be considered. For the conventional distributed containment control protocol, we will not update the relative state continuously, i.e. the relative state will be updated by some events which happen intermittently. A completely decentralised event trigger will be designed for leader–follower systems. Under the proposed protocol, if we design some appropriate feedback gain matrices, all followers will asymptotically converge to the convex hull spanned by the dynamic leaders. Numerical simulations are also provided and the results show highly consistent with the theoretical results.     

A new networked predictive control approach for systems with random network delay in the forward channel

This article is concerned with the design of a networked predictive control (NPC) scheme with random network delay in the forward channel. A new design method of NPC is proposed. Correspondingly, the necessary and sufficient conditions on the stability of the closed-loop networked control system are derived. The merit of the proposed design method lies in its decreased conservativeness, which is achieved by packing the current predictive control signal with history predictive signals. By this means, the future plant input is known. Therefore, the state predictor can be designed such that its performance and stability will not be affected by the future input of the plant, while the existing design methods of NPC cannot do so. The proposed design method is shown to be much less conservative than the existing result through several examples.     

Multi-Sensor-Based Control Strategy for Initiating and Maintaining Interaction Between a Robot and a Human

This paper presents a multi-sensor-based control strategy allowing a mobile robot to safely navigate with respect to a given human being. Two sensors are embedded in our robot: a vision system that is able to detect and track the person of interest, and a RFID antennas belt that can locate the tag worn by the latter. Thus, our control strategy will be built using image features (when the user is visible) and RFID information (when not). In the first case, a robust visual servoing control will be designed, while in the second case a suitable RFID controller will be proposed. Experimental results demonstrate the efficiency of the proposed control strategy.     

A new state space control scheme for Host-Gate Way Rate Control Protocol within intranets using ATM ABR service

In this paper, a new control strategy based on Host-Gate Way Rate Control Protocol is proposed for intranet congestion management. A more sophisticated optimal control algorithm based on a state space approach will be proposed via using the Available Bit Rate (ABR) service of an Asynchronous Transfer Mode (ATM) backbone network. The stability of the proposed control algorithm will be analyzed and the benefits of the algorithm are investigated thoroughly. Simulations confirm that the proposed new algorithm will produce lower queue level variance at the gateway. This implies that smaller buffers can fulfill the requirement for a given loss probability. Moreover, the queue level variance is less sensitive to variations in the ABR bandwidth model. This is true even when a self-similar long-range dependent trace is used to represent the ABR bandwidth in simulations, which is encouraging in view of the known self-similar nature of both LAN traffic and compressed video streams that will be sharing the ATM network.     

Constrained Moving Path Following Control for UAV With Robust Control Barrier Function

This paper studies the moving path following(MPF)problem for fixed-wing unmanned aerial vehicle(UAV) under output constraints and wind disturbances. The vehicle is required to converge to a reference path moving with respect to the inertial frame, while the path following error is not expected to violate the predefined boundaries. Differently from existing moving path following guidance laws, the proposed method removes complex geometric transformation by formulating the moving path following pr...     

非仿射系统的自学习滑模抗扰控制

针对一类单输入单输出(single-input single-output,SISO)非仿射非线性系统的控制问题,提出了一种自学习滑模抗扰控制方法.该方法用非线性光滑函数设计扩张状态观测器,实现SISO非仿射非线性系统内部不确定性和外部扰动的扩张状态估计,并将扩张状态观测器(extended state observer,ESO)与自学习滑模控制技术融为一体,实现SISO非仿射非线性系统的自学习滑模抗扰控制.该方法不依赖受控对象的数学模型,可以快速跟踪任意给定的参考信号.数值仿真试验表明了该方法响应速度快、控制精度高,具有很强的抗扰动能力,因而是一种鲁棒稳定性很强的控制方法,在SISO非仿射非线性系统控制领域具有重要作用.     

Fast response and robust controller based on continuous eigenvalue configurations and time delay control

A soft variable structure point-to-point control scheme is proposed for a micro positioning system. The specific scheme is continuous eigenvalue configurations control combined with time delay control. By continuous tuning the state feedback control vector, the eigenvalues of the system will proceed continuously toward negative infinity, which will bring quick response. The simple tuning strategy is derived, which is a continuous function of displacement error. Furthermore, Time delay control is adopted to improve robustness to system uncertainties and disturbances. From the simulation and experimental results, the proposed control scheme provides good performances in settling time, positioning accuracy and disturbance rejection.     

多输入离散时滞系统的变结构控制设计

研究多输入时滞离散系统的变结构控制问题．首先将离散时滞系统简化为无时滞离散系统,在此基础上提出一种新的变结构控制设计算法．该算法能使从空间任意点出发的运动在有限时间内准确到达并保持在切换面上,不发生切换面的穿越,有效地消除了抖振．数值计算和仿真结果表明了该方法的有效性．     

网络时延的模糊逻辑补偿方法的研究

当网络应用到控制系统中时,网络将引起时延,从而对闭环网络控制系统产生一些不利的影响,比如系统性能下降,系统不稳定等。本文介绍了通过在已有的PI控制器的基础上,再增加一个模糊逻辑补偿器来补偿网络控制系统中网络所引起的时延,其优点是不需要再重新设计已有的PI控制器,而只是简单地将模糊逻辑控制器的输出作为一个参数来调节PI控制器所提供的控制信号。文中采用了MATLAB/SIMULINK仿真,仿真结果表明了该方法的有效性。     

基于分数阶滑模控制技术的永磁同步电机控制

针对传统整数阶滑模控制系统中存在的抖震问题,本文提出了分数阶滑模控制策略并应用到永磁同步电机的速度控制.传统滑模控制器中的开关函数由作用在切换流型或其整数阶导数面推广到其分数阶导数面,利用分数阶系统的特性,缓慢地传递系统的能量,有效地削减抖震.本文采用模糊逻辑推理算法,实现软开关切换增益的自整定.仿真和实验证明,本文提出的分数阶滑模控制系统不但能有效地削减抖震,而且能保持滑模控制器对系统参数变化和外部扰动的鲁棒性.     

基于α阶逆的大时滞非线性动态矩阵控制

针对一类大时滞非线性系统,提出了基于α阶逆的动态矩阵控制新方法.该方法采用BP神经网络辨识逼近原非线性系统的α阶逆系统,并与原系统串联复合组成伪线性系统;采用基于线性系统的动态矩阵预测控制方法设计系统附加控制器.在系统存在建模误差、存在扰动和模型参数发生较大变化等情况下,采用该控制方法依然具有很好的动、静态性能和很强的鲁棒性.给出了详细的设计原理和步骤,并通过大量的仿真分析与已有的大时滞非线性系统内模控制研究结果进行了比较:内模控制依赖于系统模型,当模型出现严重失配的情况下,系统性能变坏,而采用提出的方法则不依赖系统精确的数学模型,计算量小,简化了非线性系统的设计;研究与仿真结果证明了所提控制方法的有效性.     

两种连接形式的拖挂式移动机器人路径跟踪控制

拖挂式移动机器人是一种具有不同连接形式的多车体系统.本文对标准连接和非标准连接的拖挂式机器人,研究了前向和倒车路径的跟踪控制.首先,建立系统的运动学模型并进行运动特性分析;其次,基于Lyapunov方法提出一种与期望路径具有一致运动方向的单体机器人全局路径跟踪控制器;然后将其引入到两种拖挂式机器人的前向跟踪控制中,并分别通过运动学变换和反演控制实现了两种连接形式下的倒车跟踪控制,从而使多节车体始终保持一致的运动方向,避免了不合理位形的出现.仿真结果表明该方法的有效性.     

An EMG-based variable impedance control for elbow exercise: preliminary study

As the medical field continues to evolve, the average life expectancy of the people increases. However, due to natural deterioration, the average muscle force of the arm decreases in respect to age. So, there are some needs for the people to exercise his/her body as he/she is getting older. There are many researches about the robotic rehabilitation of the upper limb for patients. However, only a few focus on the system of the upper limb muscle exercise for normal people. So, in this study, an electromyography (EMG)-based variable impedance control method is developed for elbow exercise in normal people. Four EMG sensors were attached to the designated right arm and their average EMG level was controlled by the proposed algorithm during an elbow flexion-extension exercise. A total of twenty nine experiments with 15 subjects were performed to verify the proposed control algorithm with NCCEES, an elbow exercise system developed by the authors for the elbow exercise. The experimental results showed that the proposed control algorithm could control the EMG level in approximately 24.1% percent error during the elbow exercise. However, the proposed control algorithm could not control the EMG level fluctuation which depended on the muscular characteristics of the subject. The effect of training with the proposed algorithm will be future work.     

Output feedback stabilization of nonlinear dual-rate sampled-data systems via an approximate discrete-time model

The problem of output feedback stabilization of nonlinear sampled-data control systems is considered under the low measurement rate constraint. A dual-rate control scheme is proposed that utilizes a numerical integration scheme to approximately predict the missing output values between measured output samples. It is shown that if an observer-based output feedback controller that semiglobally practically asymptotically (SPA) stabilizes the single-rate sampled-data plant model is given, then the SPA stability property will be preserved for the closed-loop dual-rate sampled-data system, on the basis of the proposed dual-rate control scheme under standard assumptions. A numerical example is given to illustrate the design method.     

A framework for brain learning-based control of smart structures

A novel framework for intelligent structural control is proposed using reinforcement learning. In this approach, a deep neural network learns how to improve structural responses using feedback control. The effectiveness of the framework is demonstrated in a case study for a moment frame subjected to earthquake excitations. The performance of the learning method was improved by proposing a state-selector function that prevented the neural network from forgetting key states. Results show that the controller significantly improves structural responses not only to earthquake records on which it was trained but also to earthquake records new to the controller. The controller also has stable performance under environmental uncertainties. This capability distinguishes the proposed approach and makes it more appropriate for the situations in which it is likely that the controller will be exposed to unpredictable external excitations and high degrees of uncertainties.     

一种改进的同伦算法与H∞鲁棒控制器设计

提出了一种具有阶次限制的鲁棒控制器设计方法, 该算法将控制系统的性能指标转化为灵敏度函数问题, 并利用Nevanlinna-Pick插值算法进行求解. 提出了一种改进的同伦算法, 将其用于求解由灵敏度函数产生的非线性方程. 基于改进同伦算法设计的鲁棒控制器 不仅避免了传统H∞控制中加权函数的选择问题, 而且克服了鲁棒控制器阶次较高的缺陷. 最后,文章以4阶系统为例, 设计了具有阶次限制的H∞鲁棒控制器, 通过与传统鲁棒控制器的比较可以看出, 基于本文方法设计的控制器不仅具有较低的阶次, 而且其控制性能也具有明显的优越性.