基于模糊控制的电气电压自适应控制器设计

电气设备上的碰撞性负载会造成电气电压波动,以往用于防止电气电压波动的设备存在使用效果不理想的问题。因此,设计基于模糊控制的电气电压自适应控制器,建立模糊控制数学模型和电气设备中电容、电感的虚拟控制通路,将控制通路的工作频率和电气电压设为模型输入项,将工作频率因子设为输出项,使用多向传导晶体阀门连接控制通路,交换通路电气电压并进行补偿,改善电气电压波动情况。进一步介绍了控制器数据采集卡AD760x的高精度采集电路,并对模糊控制下电气电压控制延时的估计过程进行设计,提高控制效果。实验结果表明,所设计的控制器控制效果好,鲁棒性强。     

Balancing control of a unicycle robot with double gyroscopes using adaptive fuzzy controller

This paper presents a unicycle robot which utilizes the precession effect of a double-gyroscope for lateral balancing and designs an adaptive fuzzy controller to realize the balance control according to its dynamic model. The double gyroscope structure of the unicycle robot can eliminate the pitch angle interference caused by the precession effect and improve the robot's lateral anti-interference ability. An adaptive fuzzy controller is designed based on the dynamic equations of the unicycle robot to improve its robustness. The adaptive controller part improves the anti-interference ability of the unicycle robot, and the fuzzy controller part is used as decoupling controller to reduce the interference of coupling. Simulation and experimental results to verify the anti-interference ability and decoupling effect of the designed controller.     

An adaptive fuzzy sliding-mode controller for servomechanismdisturbance rejection

A two-level spring-lumped mass servomechanism system was constructed for disturbance rejection control investigation. This dynamic absorber is similar to a model of the serial-type vehicle suspension system. The lower level is actuated by two DC servo motors, to provide the specified internal and external disturbances to the vibration control system. The upper level has another DC servo motor to control the main body balancing position. In order to tackle the system's nonlinear and time-varying characteristics, an adaptive fuzzy sliding-mode controller is proposed to suppress the main mass position variation due to external disturbance. This intelligent control strategy combines an adaptive rule with fuzzy and sliding-mode control technologies. It has online learning ability for responding to the system's time-varying and nonlinear uncertainty behaviors, and for adjusting the control rules and parameters. Only seven rules are required for this control system, and its control rules can be established and modified continuously by online learning. The experimental results show that this intelligent control approach effectively suppresses the vibration amplitude of the body, with respect to the external disturbance     

Sliding-mode motion controller with adaptive fuzzy disturbance estimation

This paper proposes a motion control scheme which belongs to the class of the control schemes known as sliding-mode control with disturbance estimation. A novel adaptive fuzzy disturbance estimator works as an estimator of a major part of robot dynamics. The adaptation algorithm is derived by using the Lyapunov stability theory and provides global asymptotic stability of the state errors, resulting in the sliding-mode regime. The structure of the disturbance estimator is optimized by the introduction of three fuzzy logic subsystems, based on the physical properties of the robot mechanism. This also significantly lowers the computational burden and enables real-time implementation. Performance of the proposed controller scheme, as well as some practical design aspects, are demonstrated by the control of a direct-drive robot.     

自适应模糊滑模控制器设计

针对传统滑模控制的抖振问题,利用线性化反馈技术,将模糊自适应和滑模控制相结合,设计一种新型的模糊滑模控制器。通过模糊推理和基于Lyapunov函数的稳定性分析,获得模糊控制规则的自适应律,构成自适应模糊滑模控制器,有效解决了传统滑模控制中,需要确定参数摄动和外部干扰上确界不确定性问题,倒立摆上的运行结果表明该方法的有效性。     

模糊自适应PID算法的贴片机多路温控系统

为解决传统贴片机温控系统控制效率低、温控精度不理想等问题,提出一种适用于贴片机多通道温控系统的模糊自适应PID算法。算法既具有传统PID控制器结构简单、静态控制精度高等优点,又改进了PID控制器对于非线性、大时滞系统的控制效果。     

一种自适应模糊PID控制器应用仿真

研究了一种误差驱动型自适应模糊PID控制器在二阶时滞系统中的应用。选择系统的稳态误差和误差变化率为PID参数自适应模糊调整的前件变量,将前件变量模糊化为7个论域期间,建立了PID参数调整的模糊规则表,查表得PID参数的后件参数,采用极大值反模糊化规则得到具体PID控制参数。仿真结果表明采用该控制器后系统的调节时间大大缩短,控制效果令人满意。     

Complex fuzzy adaptive filter with LMS algorithm

A fuzzy adaptive filter is constructed from a set of fuzzy IF-THEN rules that change adaptively to minimize some criterion function as new information becomes available. This paper generalizes the fuzzy adaptive filter based on least mean squares (LMS) to include complex parameters and complex signals. The fuzzy filter as adaptive equalizer is applied to quadrature amplitude modulation (QAM) digital communication with linear complex channel characteristics     

An adaptive fuzzy logic controller: its VLSI architecture andapplications

Most previous work about the hardware design of a fuzzy logic controller (FLC) intended to either improve its inference performance for real-time applications or to reduce its hardware cost. To our knowledge, there has been no attempt to design a hardware FLC that can perform an adaptive fuzzy inference for the applications of on-line adaptation. The purpose of this paper is to present such an adaptive memory-efficient FLC and its applications. Taking advantage of the adaptability provided by a symbolic fuzzy rule format and the dynamic membership function generator, as well as the high-speed integration capability afforded by VLSI, the proposed adaptive fuzzy logic controller (AFLC) can perform an adaptive fuzzy inference process using various inference parameters, such as the shape and location of a membership function, dynamically and quickly. Three examples are used to illustrate its applications, and the experimental results show the excellent adaptability provided by AFLC     

Fault-tolerant switched reluctance motor drive using adaptive fuzzy logic controller

An adaptive fuzzy controller has been designed to develop a high-performance fault-tolerant switched reluctance motor (SRM) drive. The fuzzy controller continuously adapts its properties to regulate the machine torque as desired by the drive system even under fault conditions. The adaptation of the fuzzy membership functions results in extended conduction period and increased peak current of the healthy phases to deliver the commanded torque, as much as possible. The adaptive fuzzy controller provides smooth torque output with minimum ripple, even under fault conditions, yielding a high-performance SRM drive with fault-tolerant capability.     

基于FPGA的温度模糊自适应PID控制器的设计

针对桌恒温箱控制系统中存在的非线性、时变等特点,结合传统PID与现代模糊控制理论,以EPIC12型FP-GA为核心控制器,采用模块化思想,设计并实现温度模糊自适应PID控制.实际运行结果表明,采用该方法可明显改善控制效果,在简化设计的同时,也可提高系统的运算速度和可靠性.     

基于模糊免疫自适应PID的汽车烘房温度控制系统

烘房温度控制是汽车涂装系统的重要环节,对汽车生产的质量、成品率等有重要影响。针对烘房温度控制系统的难点和性能要求,提出了利用模糊免疫自适应PID控制器调节烘房温度。该控制方法兼具模糊控制、免疫控制和传统PID的优点,通过实时调整PID控制器的参数来保持系统的稳定性。仿真结果表明基于自适应模糊免疫PID控制器在响应速度、抗干扰能力上都优于模糊PID控制器和传统PID控制器。该控制方法为汽车烘房温度控制提供了一种新的控制策略。     

一种基于遗传算法的解析模糊控制器

提出了一种解析规则模糊控制器的改进结构，并引入了能够动态调整模糊控制规则的修正函数；同时，通过遗传算法，实现了模糊控制器控制参数的组合优化设计。仿真结果表明这种设计方法是有效的。     

基于模糊控制的PEMFC控制器设计

针对PEMFC严重的非线性、高耦合、多变量等特点,提出一种基于模糊控制的PEMFC控制器设计方案。采用AT89S52单片机为核心,使用总线式数字测温器件DS18B20作为温度传感器,运用风扇和双向晶闸管通过模糊控制技术控制。PEMFC的反应温度通过LCD实时监控,配备声光警报系统。并通过Proteus 7 Professional的仿真以及样机测试证明了模糊算法的优越性和电路的有效性。     

自适应模糊PID控制的太阳光跟踪伺服系统

针对太阳光跟踪伺服系统中应用的传统PID控制过程中的一些问题,本文通过对自适应模糊PID控制系统的分析,设计了双轴跟踪伺服系统自适应模糊PID控制器,并在Simulink环境中建立方位角跟踪传动机构仿真模型且完成仿真。仿真结果表明,太阳光跟踪伺服系统自适应模糊PID控制器较传统PID控制器具有较强的稳定性、适应性与鲁棒性,这在太阳光跟踪伺服系统控制领域具有重要的实用价值与应用空间。     

GA and Lyapunov theory-based hybrid adaptive fuzzy controller for non-linear systems

In this present article, a new hybrid methodology for designing stable adaptive fuzzy logic controllers (AFLCs) for a class of non-linear system is proposed. The proposed design strategy exploits the features of genetic algorithm (GA)-based stochastic evolutionary global search technique and Lyapunov theory-based local adaptation scheme. The objective is to develop a methodology for designing AFLCs with optimised free parameters and guaranteed closed-loop stability. Simultaneously, the proposed method introduces automation in the design process. The stand-alone Lyapunov theory-based design, GA-based design and proposed hybrid GA–Lyapunov design methodologies are implemented for two benchmark non-linear plants in simulation case studies with different reference signals and one experimental case study. The results demonstrate that the hybrid design methodology outperforms the other control strategies on the whole.     

一种基于L-M算法的组合神经网络模糊控制器

提出了一种基于L-M算法的神经网络模糊控制器。用两个相同的三层前向神经网络①和②来生成E和EC的隶属度,用三层前向神经网络③来实现模糊控制规则并生成控制输出,经过研究和对比选择了对于这3个网络来说最好的训练算法Levenberg-Marquardt算法。仿真结果表明了该控制器极好的控制性能。