机器人操作器力控制稳定性分析

当机械手同刚性环境接触时，机械手力控制难于保持系统的稳定性，这就是机械手力控制动态不稳定性，本文分析了机械手力控制未建模特性：１）机械手驱动电机动态特性；２）力传感器动态特性；３）接触环境的动态特性；４）机械手力控制采样控制延迟等对机械手力控制稳定性的影响，最后给出了仿真及实验研究结果。     

一种非线性动力系统的开环控制方法及其应用研究

本文研究采用振荡控制方法，来改善非线性动力系统的特性，具体对用Ｄｕｆｆｉｎｇ、Ｒａｙｌｅｉｇｈ及Ｖａｎ ｄｅｒ Ｐｏｌ方程描述的动力系统特性进行了分析，并进行了该系统振荡稳定性、振荡可控性分析，最后引入振荡控制，使原系统特性得到很大改善。     

人工关节试验机电液力伺服控制系统迭代学习控制策略仿真

本文首先介绍了人工关节试验机电液力伺服控制系统的构成，并分析了其静特性。针对力系统的特性，本文提出了一种闭环比例型一阶给定超前迭代学习控制算法，并对其控制效果进行了仿真研究。研究结果表明，采用迭代学习控制算法可以有效地提高力系统的跟随精度。     

免疫机理在模糊PID控制中的应用

本文探讨了模糊控制在PID控制中的应用，并且着重介绍了生物系统的免疫机理的特点，根据其控制特性，提出了在模糊控制中加入生物免疫机理的思想，改进控制的效果。     

火电厂沸腾燃烧锅炉微机控制系统

本文在对沸腾燃烧锅炉动态特性作出分析的基础上，通过现场调研提出了符合实际的微机控制方案，现场运行收到满意效果。该控制系统由一台ＴＰ－８０５微型计算机及输入、输出接口、信号转换器等组成。本文主要介绍微机控制系统的研究及投运的基本情况，着重于动态特性分析和控制方案的确定。     

舵鳍联合控制系统研究

本文研究了船舶运动的控制问题，利用船舶运用本身固有的耦合特性，对舵鳍操作采用联合控制的方案，取得了较好的效果。     

中小型通用变频器控制待性的分析

在变频器应用中，经常遇到这佯的问题．在知道了要控制的电机负载特性后，如何选择性能价格比较高的变频调速器?要解决这个问题，首先要掌握各种变频器的控制特性，才能保证圆满地完成整个调速系统的设计。本文以有一定代表性的西门子和富士两大品牌为例，对工业控制中应用较为广泛的中小型通用变频器的控制特性进行分析。     

非线性离散系统的迭代学习控制方法及其应用*

本文根据误差收敛准则，提出了非线性离散系统的迭代学习算法，给出了ＰＩＤ型学习控制的收敛条件，并证明了ＰＩＤ型学习控制对预定轨线的逼近特性，在交流变频电机起动过程控制中应用表明，使用本文方法可以得到实用的结果。     

控制高阶串联系统的一种新方法

本文应用ＩＭＣ系统特性及模型参考自适应控制原理，提出了一种控制高阶串联系统的新方法。     

基于控制量补偿的过热汽温混合型模糊自调整PID控制研究

本文针对惰性区具有多个参数及迟延摄动的电厂锅炉过热汽温控制问题及其对汽温响应和抗扰动特性的特殊要求，提出一种基于控制量补偿的混合型模糊自调整PD控制策略。仿真结果表明，这种混合模糊控制方法和利用自适应遗传算法优化获得的固定参数PID控制方式相比，显著的改善了汽温响应特性，同时较好的解决了采用常规PID控制器的过热汽温系统中，控制器的参数整定无法同时兼顾设定值跟踪响应特性和干扰抑制特性的问题。     

Control of a Robotic Manipulator Using Artificial Neural Networks with On-line Adaptation

An adaptive neural system for positioning control of a PUMA 560 manipulator is presented". The computed torque method was implemented with a Multi-Layer Perceptron with on-line learning. The control scheme is implemented into two phases. The first one is the off-line phase in which the neural network is trained with previously known control actions. The second one is the on-line phase in which the neural network parameters are adapted while controlling the manipulator. The control system is able to respond to changes in the manipulator model and to load disturbances. As will be shown, control system performance is improved with the on-line learning strategy presented in this paper.     

Dynamic Modeling and Tracking Control of a Nonholonomic Wheeled Mobile Manipulator with Dual Arms

This paper presents methodologies for dynamic modeling and trajectory tracking of a nonholonomic wheeled mobile manipulator (WMM) with dual arms. The complete dynamic model of such a manipulator is easily established using the Lagrange’s equation and MATHEMATICA. The structural properties of the overall system along with its subsystems are also well investigated and then exploited in further controller synthesis. The derived model is shown valid by reducing it to agree well with the mobile platform model. In order to solve the path tracking control problem of the wheeled mobile manipulator, a novel kinematic control scheme is proposed to deal with the nonholonomic constraints. With the backstepping technique and the filtered-error method, the nonlinear tracking control laws for the mobile manipulator system are constructed based on the Lyapunov stability theory. The proposed control scheme not only achieves simultaneous trajectory and velocity tracking, but also compensates for the dynamic interactions caused by the motions of the mobile platform and the two onboard manipulators. Simulation results are performed to illustrate the efficacy of the proposed control strategy.     

Speed control strategy of dual flexible servo system considering time-varying parameters for flexible manipulator with an axially translating arm

Many factors lead to fluctuations of output speed in the motor side during the movement processes in a flexible manipulator with an axially translating arm. These factors include the time-varying characteristics of manipulator parameters, external disturbance, and flexibility in the manipulator. The vibration of flexible manipulators is strengthened by fluctuations of output speed, which seriously affects the motion accuracy. Therefore, a variable parameters proportional–integral (PI) control strategy based on disturbance observer is adopted to reduce fluctuations of output speed in a dual flexible servo system. First, the dynamic model of the dual flexible servo system is established by the assumed mode method. Then, the variable parameters PI control strategy is applied to the servo system, and the controller parameters in different conditions are selected by pole placement strategies. Finally, numerical simulations and control experiments of the servo system are carried out. The results show that the control strategy using the variable parameters and disturbance observer could reduce fluctuations of output speed and improve the motion accuracy of flexible manipulators.     

基于自适应动态规划的移动装弹机械臂轨迹控制

针对移动装弹机械臂系统非线性、强耦合、受多种不确定因素影响的问题,本文基于自适应动态规划方法,提出了仅包含评价网络结构的轨迹跟踪控制方法,有效减小了系统跟踪误差.首先,考虑到系统非线性特性、变量间强耦合作用及重力因素的影响,通过拉格朗日方程建立了移动装弹机械臂的动力学模型.其次,针对系统存在不确定性上界未知的问题,建立单网络评价结构,通过策略迭代算法,求解哈密顿–雅可比–贝尔曼方程,基于李雅普诺夫稳定性理论,设计了自适应动态规划轨迹跟踪控制方法.最后,通过仿真实验将该控制方法与自适应滑模控制方法进行了对比,进一步检验了所设计控制方法的有效性.     

A multi-microprocessor-based decentralized adaptive controller for a robotic manipulator

In this paper, a simple and efficient decentralized adaptive controller for robotic manipulators is presented; the explicit recursive Newton-Euler dynamic model, which takes full advantage of the specific structure of a manipulator, is developed; and a multi-microprocessor-based implemental scheme for the decentralized adaptive controller is proposed. Some typical computer simulation results on a PUMA-like manipulator with three degrees of freedom are given to demonstrate the control effectiveness. An analysis of the computational complexity of the algorithm, using PUMA 560, is presented to show the high efficiency of the explicit model and the implementational scheme.     

基于RBF神经网络逆系统的机械手解耦控制策略

针对机械手系统具有非线性时变、多变量、强耦合的特点,提出一种基于RBF神经网络逆系统的机械手解耦控制策略。首先证明了系统的可逆性,进一步通过神经网络在线逆辨识建立机械手的神经网络逆系统模型,并将辨识得到的逆模型作为控制器模型与机械手系统串联,构成伪线性复合系统,实现了将具有强耦合特性的多变量输入/输出机械手系统解耦成单个独立的伪线性对象。最后以两关节机械手为仿真对象进行了仿真,仿真结果验证了本方案的有效性和可行性。     

机器人最佳轨迹规划和图形仿真的研究

本文介绍了基于 IBM-PC 微机的机器人轨迹规划的图形仿真系统.该系统可用于机器人运动学分析和最佳轨迹规划,并能产生机械手和广义物体组成的环境物的三维几何模型.系统以交互方式工作.在微机的 CRT 上,机械手连杆的运动具存动态效果.基于 MINIMAX 准则,我们提出了一种动力学性能指标用于轨迹规划.根据该指标所进行的轨迹规划可以获得最小的关节驱动力矩.最后,文中给出了 PUMA 560 机械手的仿真结果.     

机器人控制器中应用加速度反馈的几个问题讨论

加速度正反馈与近似积分负反馈相结合的综合加速度反馈在机械手位置控制中的 应用有明显的增阻尼效果,而在力控制中的应用却受到了很多条件的限制.利用PUMA560 机械手力控制的辨识模型,通过仿真手段分析了影响加速度反馈效果的原因,得出了机械手 驱动电机的动态、连杆的柔性和采样延迟是制约加速度反馈作用的主要因素的结论.最后在 此结论指导下的实验结果验证了这个结论的正确性,同时指出了应用加速度反馈的希望所 在.     

Adaptive learning with large variability of teaching signals for neural networks and its application to motion control of an industrial robot

Recently, various control methods represented by proportional-integral-derivative (PID) control are used for robotic control. To cope with the requirements for high response and precision, advanced feedforward controllers such as gravity compensator, Coriolis/centrifugal force compensator and friction compensators have been built in the controller. Generally, it causes heavy computational load when calculating the compensating value within a short sampling period. In this paper, integrated recurrent neural networks are applied as a feedforward controller for PUMA560 manipulator. The feedforward controller works instead of gravity and Coriolis/centrifugal force compensators. In the learning process of the neural network by using back propagation algorithm, the learning coefficient and gain of sigmoid function are tuned intuitively and empirically according to teaching signals. The tuning is complicated because it is being conducted by trial and error. Especially, when the scale of teaching signal is large, the problem becomes crucial. To cope with the problem which concerns the learning performance, a simple and adaptive learning technique for large scale teaching signals is proposed. The learning techniques and control effectiveness are evaluated through simulations using the dynamic model of PUMA560 manipulator.