多模型自适应控制的分层递阶构造与覆盖性质分析

针对一类非最小相位系统,设计一种多模型自适应控制器.该控制器由固定控制器模型、常规自适应模型和可重新赋值自适应模型构成.固定控制器模型采用分层递阶结构用来减少模型集的数目,根据切换指标选出的上一层最优控制器,动态设计本层固定控制器模型实现对其参数变化范围的覆盖.该控制器采用直接自适应算法,通过加权多项式的选取,消除了稳态误差.文末对系统的覆盖性、模型数目等进行了分析.仿真结果表明当采用相同数目的模型时,其控制效果明显优于常规多模型控制器.     

一种新型非线性PID控制器及其参数设计

方法简单、参数效率高是非线性PID控制器所期望的特征. 本文提出一种新的非线性PID控制器设计方法,并就其非线性函数的函数特点以及控制器参数选择问题进行了分析. 首先, 利用电容极间场强的作用原理提出了一种非线性函数构造方法, 并用来对常规PID控制器进行修正, 形成一种非线性PID控制器; 其次, 对非线性函数进行了分析, 指出了不同参数对非线性函数的影响; 最后, 利用T–无源的有关结论对这种非线性PID控制器的稳定性进行分析, 得到了这一非线性PID控制器的参数设计依据. 仿真实例表明了文中所提控制     

新型道口控制器的研制

介绍了一种新型道口控制器的硬件设计和组成原理;本控制器设计方案经过测试.其在经济上和维护上,显然要优于原道口控制器,保证了列车运行的安全、正点.     

履带式移动机器人轨迹跟踪研究

详细分析了履带式移动机器人的受力特点,提出了一种适宜进行控制器设计的履带移动机器人模型.根据履带式移动机器人动力学模型和运动学模型,设计了机器人的轨迹跟踪控制器.利用Lyapunov稳定判据证明控制器的全局稳定性.在控制器的设计中考虑了履带一地面作用,引入参数对其描述.考虑到机器人动力学约束,引入机器人速度、加速度控制策略以保证机器人运动平滑.仿真实验验证了该方法的有效性和全局收敛.     

基于遗传算法和模糊PID的励磁控制器

随着电力系统的发展,常规PID励磁控制器已经不能满足系统运行的动态和静态性能要求,为了克服这一缺点,设计了一种新型模糊PID控制器,在常规模糊PID励磁控制器基础之上,提出了一种利用遗传算法优化的模糊控制器.介绍了同步发电机自动励磁系统及模糊PID励磁控制器的构成,模糊PID控制器的原理及作用.仿真研究结果表明利用该方法设计的励磁控制器具有更好的动静态特性.     

ETC系统中车道控制器的设计

车道控制器是ECT系统中的重要组成部分.车道控制器用于管理ETC系统中的交通信号灯、视频采集设备、栏杆机、车辆检测设备和费额显示器等设备.介绍了一种基于W77E58微处理器的车道控制器的详细设计方案,同时给出了车道控制器的硬件结构和软件组成.     

一种基于MVC的主辅控制器设计与实现

针对当前多层Web体系结构的设计中存在的一些问题,本文基于MVC设计模式,对MVC的控制器做进一步的研究和设计.首先分析比较了单一控制器和多控制器两种常用的控制器设计方法,接着基于多控制器设计方法提出了一种主辅控制器设计方案,并综合使用Servlet＋JavaBean技术加以具体实现.可以发现,这种控制器设计方案具有较好的可维护性、可扩充性和作为一个应用框架的可伸缩性.     

基于神经元的多变量自适应控制器的研究与设计

本文将单神经元控制器的基本思想引入到多变量控制系统,提出和设计了一种基于神经元的、具有在线学习功能的多变量控制器.该控制器具有结构简单、不依赖于对象模型和在线计算量少的特点.仿真实验结果表明,该控制器具有较好的控制效果.     

基于单片机的红外遥控开关控制器

介绍了一种可以由普通遥控器作为信号输入的开关控制器.该控制器可以通过学习、分析和记忆多种遥控器的编码,实现对多种电器的开关控制.简单介绍了由AT89C51单片机构成的红外遥控开关控制器的结构、功能及工作原理,阐述了解码程序的基本结构和程序框图.该控制器可用于一些其它的控制场合.     

仿射非线性系统的广义逐点最小范数控制

在Freeman的逐点最小范数控制器的基础上,提出了一种新的非线性控制器设计框架一广义逐点最小范数控制器,并证明了其连续性.通过一个引导函数,新的控制器可以和其他的控制器设计策略结合,从而大大提高了控制器设计的灵活性.另外,给出了新方法的两个应用:改善局部线性化控制器稳定域较小的缺陷;及和其它控制器设计方法结合,使之能够简单有效地处理具有输入约束的系统.     

具有H_∞跟踪性能的机器人自适应PID控制

针对非线性不确定机器人系统的轨迹跟踪控制问题,提出一种鲁棒自适应PID控制算法.该控制器由主控制器和监督控制器组成.主控制器以常规PID控制为基础,基于滑模控制思想设计PID参数的自适应律,根据误差实时修正PID参数.基于Lyapunov函数设计的监督控制器补偿自适应PID控制器与理想控制器之间的差异,使系统具有设定的H_∞的跟踪性能.最后,两关节机器人的仿真实验结果表明了算法的有效性.

Abstract：

A robust adaptive PID control algorithm is proposed for trajectory tracking of robot manipulators with nonlinear uncertainties.The controller is composed of a main controller and a supervisory controller.The main controller is designed based on the traditional PID controller.The parameters of the PID controller are updated online according to the system running errors with the adaptation law based on the sliding mode control.The supervisory controller is proposed to compensate the error between the adaptive PID controller and the ideal controller in the sense of the Lyapunov function with the specified H_∞ tracking performance.Finally, the simulation results based on a two-joint robot manipulator show the effectiveness of the presented controller.     

Study of Learning Fuzzy Controllers

This paper compares two types of learning fuzzy controllers, the self-organizing fuzzy (SOF) controller and the hybrid self-organizing fuzzy proportional–integral–derivative (SOF-PID) controller. The SOF is an extension of the rule-based fuzzy controller, with additional rule creation and rule modification mechanisms. The hybrid SOF-PID comprises the SOF as a learning supervisory controller readjusting the proportional gain of the PID controller at the actuator section, when the system is on line. The structures of the SOF controller and the hybrid SOF-PID controller are studied. The performances of the SOF controller and the hybrid SOF-PID controller are compared by applying them to a two-link non-linear revolute-joint robot arm. For the path tracking experiments, the hybrid SOF-PID controller followed the required path more closely and smoothly than the SOF controller. The results of the experiments for the SOF controller and the hybrid SOF-PID controller are also compared with those obtained with a conventional PID controller, using the same values supplied at the setpoint.     

基于反步法的移动机器人鲁棒跟踪控制

以四轮移动机器人为研究对象,建立了机器人完整的数学模型,包括运动学模型、动力学模型以及驱动电机模型。在机器人数学模型的基础上,采用反步法的思想设计具有全局收敛特性的鲁棒轨迹跟踪控制器,设计中考虑了驱动电机模型使控制器更符合实际控制要求,并将其分解为运动学控制器、动力学控制器以及电机控制器三部分,降低了控制器设计的难度。构造了系统的李雅普诺夫函数,证明了该类型移动机器人在所得控制器作用下,能实现对给定轨迹的全局渐近追踪。仿真实验结果表明基于反步法的控制器是有效的。     

Gain scheduling control of nonlinear systems based on approximate input-output linearization

The gain scheduling control mostly has been developed based on Jacobian linearization around the operating points related with scheduling variables. In this paper, We introduce a gain scheduling control method based on approximate input-output linearization. First, the nonlinear system is approximately input-output linearized via a diffeomorphism. Then, a gain scheduling controller with derivative information is developed. The proposed controller consists of two parts. The outer loop controller is like a feedback linearizing controller and the internal controller is a gain scheduling controller. It is shown that the overall resulting controller has a simple structure and at the same time achieves better tracking performance over the existing Jacobian-based gain scheduling controller.     

Design and analysis of direct-action CMAC PID controller

This paper is to propose a direct-action (DA) cerebellar model articulation controller (CMAC) proportional-integral-derivative (PID) controller. The proposed controller, termed the DAC-PID controller, can generate four simple types of the nonlinear functions and then determine a control effort from those functions to control the process. In addition, the real-coded genetic algorithm is used to tune the parameters of the DAC-PID controller such that we can optimize those parameters. The performance of the proposed controller is also discussed in the sense of quantitative analysis. Simulation results demonstrate that the DAC-PID controller is superior to the conventional PID controller tuned by Ziegler–Nichols method and, moreover, as better as the optimal PID controller and the optimal fuzzy-PID controller.     

一种稳定的机器人神经网络控制器研究

研究一种稳定的机器人神经网络（ＮＮ）控制器，提出了由神经网络控制器和监督控制器构成的控制方案，给出了控制器的设计方法及ＮＮ学习自适应律，并基于Ｌｙａｐｕｎｏｖ方法证明了控制系统的稳定性和ＮＮ参数收敛性，仿真结果表明该控制方案具有良好的鲁棒性和参数收敛性，从而证明控制器的有效性。     

New type of controller: the proportional integral minus delay controller

In the design of a control system, the derivative controller is often required to obtain a quick response. However, when the control system is subject to noise inputs, the functioning of the derivative controller may be jeopardized owing to its sensitivity to high-frequency noise. In order to overcome this problem, a new type of controller, called the proportional-integral-minus-delay (PIMD) controller is proposed in this paper. It is shown that in addition to exhibiting almost the same characteristics as the conventional proportional-plus-integral-plus-derivative (PID) controller, the PIMD controller is less sensitive to high-frequency noise. It seems that an appropriate PIMD controller would be a good replacement for a PID controller. The output time responses of the closed-loop system with a PIMD controller and the frequency-response characteristics of a PIMD controller are obtained by computer simulation.     

Adaptive controller for tracking power profile in a fuel cell powered automobile

In this paper, a model reference adaptive controller is designed using the Lyapunov method, for tracking a time varying power profile in an automobile powered by a fuel cell. The adaptability of the controller is tested by implementing the controller on different power profiles which simulate actual power requirement of different road conditions. The performance of the adaptive controller is compared with a conventional PID controller and it is observed that the adaptive controller has superior performance.     

Adaptive cruise control of a HEV using sliding mode control

This paper presents adaptive cruise control of a hybrid electric vehicle. First, the mathematical model of the vehicle is formulated. Next, a classical controller is applied to the vehicle model. Swarm optimisation is implemented for self parameter tuning of the controller. The model is simulated and the result of the response to a variable speed is analysed. The results reveal that the controller is not a powerful means to manage the rapid transformation of the desire set point. Accordingly, a sliding mode controller is developed next. The performance of this controller is compared with the classical controller.     

新型模糊PID控制及在HVAC系统的应用

为了推广模糊控制器在非线性系统中的应用,提出一种利用PID控制器的参数优化和调节模糊控制器的新型设计方法.通过模糊控制器的结构分析建立与PID控制之间的精确解析关系之后提出基于PID控制增益因子的模糊控制器设计算法,然后利用改进的变论域思想进一步优化模糊控制器设计参数.将其应用于暖通空调(HVAC)系统的节能控制中并与常规PID控制器相比较,仿真和实验结果表明这种模糊控制器具有超调量小、跟踪迅速、鲁棒性强等优越的控制性能.