测试转台的输出改进自抗扰控制器设计

当电机存在低频大力矩扰动时,使用经典方法控制测试转台很难达到期望的测量精度,为了有效抑制扰动达到期望精度,提出一种输出改进的自抗扰控制器设计方法。在控制的起始阶段采用普通自抗扰控制器,系统进入稳态后引入非线性饱和环节限定自抗扰控制器的输出幅值。仿真结果表明,系统既具有良好的动态特性,又有很好的抗扰性,达到了较好的输出精度。最后与经典控制方法相比较进一步验证了其良好的控制效果。     

基于自抗扰控制的两轮自平衡车控制系统仿真研究

为解决两轮自平衡车因不同用户身高体重的差异造成系统模型不准确而带来控制器对系统控制稳定性能差的问题,将自抗扰控制技术运用到两轮自平衡车运动平衡控制中。首先采用拉格朗日方法建立两轮自平衡车动力学模型,然后针对系统的特性推导出实现两轮平衡车自平衡控制的自抗扰控制器控制律。最后,搭建两轮自平衡车控制系统的Simulink仿真平台,分别采用线性自抗扰控制和经典自抗扰控制方法进行了试验比较。试验结果表明:与经典自抗扰控制器相比,新的自抗扰控制器能够较好地适应身高体重变化的环境,较好地自主达到稳定运行状态。     

自适应模糊自抗扰控制器的研究与设计

针对普通PID在实际工程控制中参数整定难,抗干扰能力差的问题,设计了一种基于模糊控制原理的改进型自抗扰控制器.该控制器充分结合了模糊控制器和自抗扰控制器的各自优势,并对其进行了随动系统的仿真.仿真结果表明,该控制器可设计成为一个响应速度快、静差小的控制系统,与经典PID控制器在同样的系统中比较,自适应模糊自抗扰控制有较好的控制性能.     

自抗扰控制器在液位控制中的研究

经典PID控制器由于其简单实用,在液位控制中广泛的应用。但对于涉及到工业过程控制中的一阶时滞系统来说:PID控制存在着诸多不理想因素,如环境变化等容易导致工业模型参数随之变化造成的控制不理想。为了改善其液位的控制效果并保留经典PID控制的简单实用性。提出了一种比较新型的控制方案:即自抗扰控制器(ADRC)水箱液位控制。自抗扰控制器具有模型简单,收敛速度快,精度高,参数易于调节等特点,通过建立控制系统的仿真模型,将用Z-N整定方法的PID控制与自抗扰控制进行比较,并进行了仿真对比研究。结论表明:自抗扰算法在液位控制等控制工程中是一种优秀的控制方案。     

二阶自抗扰控制器的参数简化

为了克服PID控制器自身具有的缺陷，在PID的基础上提出了自抗扰控制器（ADRC）。该控制器由跟踪微分器、扩张状态观测器和非线性状态误差反馈三部分组成，其控制效果优于经典PID控制器，但是参数众多、调节复杂。通过线性简化和参数整合建立简化的线性自抗扰控制器。MATLAB仿真表明，简化的线性自抗扰控制器参数调节过程大大简化，而控制性能并未受到明显影响。     

自抗扰控制器在卷绕头速度控制中的应用

卷绕头要求恒张力恒线速度控制,采用可以代替经典PID控制器的自抗扰控制器,它不依赖于对象的精确模型就可以实现干扰补偿,仿真和实验结果表明,自抗扰控制器在整个卷绕过程中,具有良好的动态性能,且对负载及各种扰动都有非常好的鲁棒性。     

无刷直流电机的新型控制器

自抗扰控制(ADRC)是在继承经典PID不依赖于对象模型的基础上,通过改进经典PID固有缺陷而形成的新型控制技术.为满足无刷直流电机控制系统性能要求,在分析永磁无刷直流电机特点及使用现状的基础上,建立了基于自抗扰控制器的无刷直流电机控制系统.仿真结果表明,自抗扰控制器对无刷直流电机模型的不确定性和外部扰动变化具有较强的适应性和鲁棒性,算法简单、工程适用性较强,系统具有良好的动态响应性能.     

自抗扰控制器在卷绕头速度控制中的应用

卷绕头要求恒张力恒线速度控制,采用可以代替经典PID控制器的自抗扰控制器,它不依赖于对象的精确模型就可以实现干扰补偿,仿真和实验结果表明,自抗扰控制器在整个卷绕过程中,具有良好的动态性能,且对负载及各种扰动都有非常好的鲁棒性.     

基于变结构控制的二阶自抗扰控制

结合变结构控制器抗扰性能强，调节速度快和结构简单的特点，提出一种基于变结构控制器的二阶自抗扰控制器。首先，设计了系统的相轨迹和一种变结构控制律，使得系统具有更强抗扰能力和更快的调节速度。在带宽近似不变的情况下，可以通过调节参数改变系统的抗扰性和调节时间。证明了系统的稳定性，研究了变结构控制器的参数选取问题，考虑扩张状态观测器的观测误差，分析了参数选取对系统抗扰性的影响。最后，采用仿真实验测试了控制器的性能，实验结果表明，相比基于PD控制的标准自抗扰控制控制器，该控制器在调节时间、抗扰性及参数整定上均更优。     

基于增量式方法的自抗扰控制无扰切换技术

针对自抗扰控制在分散控制系统中的应用问题,研究了自抗扰控制的无扰切换方法。通过分析调节系统无扰切换原理,提出利用增量型线性自抗扰控制器实现无扰切换的方法。在电厂仿真机平台上编写了二阶线性自抗扰控制器模块,通过组态、运行验证了该方法可以实现自抗扰控制器的手/自动无扰切换、两种不同控制器之间的无扰切换。通过该方法可以将自抗扰控制应用到分散控制系统中,提高控制性能。     

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.     

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.     

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.     

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.     

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.     

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。     

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。     

拟合迭代学习数据的工业过程控制器

为进一步提高工业过程控制系统的跟踪能力, 实现稳、准、快等性能, 本文利用迭代学习算法产生的各类信息, 在控制器函数拟合的基础上, 设计了一种高精度跟踪的鲁棒控制器. 首先在频域对闭环迭代学习算法进行分析, 得出迭代学习控制器等同于级联控制器的结论, 进而采用一个低阶结构的控制器去拟合误差序列与控制序列,避免了难以物理实现的高阶控制器, 最后通过对一般的工业过程对象进行实验设计, 结果表明这种控制器在快速性、无超调及控制精度上具有很好的优势, 并且具有良好的抑制干扰能力.     

Design of a hybrid fuzzy logic proportional plus conventionalintegral-derivative controller

Presents approaches to the design of a hybrid fuzzy logic proportional plus conventional integral-derivative (fuzzy P+ID) controller in an incremental form. This controller is constructed by using an incremental fuzzy logic controller in place of the proportional term in a conventional PID controller, By using the bounded-input/bounded-output “small gain theorem”, the sufficient condition for stability of this controller is derived. Based on the condition, we modify the Ziegler and Nichols' approach to design the fuzzy P+ID controller. In this case, the stability of a system remains unchanged after the PID controller is replaced by the fuzzy P+ID controller without modifying the original controller parameters. When a plant can be described by any modeling method, the fuzzy P+ID controller can be determined by an optimization technique. Finally, this controller is used to control a nonlinear system. Numerical simulation results demonstrate the effectiveness of the fuzzy P+ID controller in comparison with the conventional PID controller, especially when the controlled object operates under uncertainty or in the presence of a disturbance     

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.