Fuzzy Variable Structure Control of Photovoltaic MPPT System

In order to reduce chattering phenomenon of variable structure control, a fuzzy variable structure control method is adopted and applied in the photovoitaic maximum power point tracking （MPPT） control system. Firstly, the electric features of PV cells and a dynamic model of photovoitaic system with a DGDC buck converter are analysed. Then a hybrid fuzzy variable structure controller is designed. The controller is composed of a fuzzy variable structure control term and a supervisory control term. The former is the main part of the controller and the latter is used to ensure the stability of the system. Finally, the conventional variable structure control method and the fuzzy variable structure control method are applied respectively. The comparing of simulation results shows the superiority of the latter.     

Research on the Winding/Unwinding Control System Based on Fuzzy Control Theory

A fuzzy controller of the winding/unwinding control system used in jig-dyeing machine is introduced, which is superior to the one with conventional optimal PID controller in convergence speed and stability. Its mathematical model and transfer function are presented based on mechanism of the winding/unwinding control system. Simulation of the fuzzy controller carried out in the MATLAB （Simulink） environment proves that the control system based on fuzzy controller is superior in quality, precision and operation to a conventional optimal PID controller. The outlined experimental results also show the effectiveness and the robustness of the fuzzy PID controller in good dynamic performance, high robustness to parameter variation and disturbance.     

An Intelligent Adaptive Fuzzy PID Controller Based on Multimodel Control Approach

A novel intelligent adaptive fuzzy PHD controller based on multimodel control approach is presented in this paper.It can improve the system performance of the dynamic time- varying system at various operating conditions.The fuzzy PHD controller is implemented by combining a fuzzy PI with a fuzzy PD controller in a parallel structure. The parameters of the fuzzy PHD controller are linked, via analytical derivation, to the gains of the linear PID controller. The sum of error square is used as performance criterion to locate the model that best reresents the process among the multiple models, The desired control output to drive the process along the desired path is generated only by modifying the output scale factots GU_I and GU_D of the fuzzy PID controller, Among the prescribed models, the control signal of the nearestmmodel to the system is applied. The system can be driven to its original trajectory because of the robustness of the fuzzy PID controller, Computer simulation results show that the adaptiv     

Intelligent Integrated Control of Underactuated Mechanical Systems with Second-order Nonholonomic Constraints

This paper describes an intelligent integrated control of an acrobot, which is an underactuated mechanical system with second-order nonholonomic constraints. The control combines a model-free fuzzy control, a fuzzy sliding-mode control and a modelbased fuzzy control. The model-free fuzzy controller designed for the upswing ensures that the energy of the acrobot increases with each swing. Then the fuzzy sliding-mode controller is employed to control the movement that the acrobot enters the balance area from the swing-up area. The model-based fuzzy controller, which is based on a Takagi-Sugeno fuzzy model, is used to balance the acrobot. The stability of the fuzzy control system for balance control is guaranteed by a common symmetric positive matrix, which satisfies linear matrix inequalities.     

A LOCAL CONTROLLER BASED CONSTANT TENSION CONTROL SYSTEM

This paper is mainly about a local controller whose main function is to achieve the constant tension of the thin denier filament in the high speed winding process. A mathematic model of the induction motor while controlling its stator frequency and voltage is given. A new kind of variable parameter, real time constant tension control system is presented. The paper uses the microprocessor -INTEL 8097 as the CPU of the local controller. A standard serial communication interface-RS232 is used to communicate with the main computer. Computer simulation and experiment test show that this system has good control characteristics.     

The Redundant Arm Self-motion Control Based on Serf-tuning Fuzzy PID Controller

A fuzzy control algorithm based on self-tuning PID proportional factor is presented. To a certain de-gree, it overcomes robot motion control‘s nonlinearity and uncertainty caused by joints coupled and fric-tion, and decreases overshoot of end manipulator‘s tracking desired curves. The controller‘s structure is very simple but effective. With this control method, a 7-DOF redundant ann‘s self-motion developed by the authors is investigated. Research results show that the said controller restrains track overshoot and preferable merits.     

High Performance Position Control System Based on SR-PM Motor

A position control system was developed using a synchronous reluctance permanent magnetic (SR-PM) motor with the field oriented control (FOC). To get satisfactory control performance, a fuzzy adaptive proportion integration (PI) controller was used rather than a conventional PI controller for the position control. The controller tunes the PI parameters online with fuzzy logic, based on the error and the change of the error between the feedback and reference position. The superiority of the fuzzy PI controller compared to conventional controller is illustrated by simulations and experiments which confirm that the fuzzy PI controller effectively restrains overshoot of the position response. As a result, the servo system gives satisfac- tory steady state and dynamic performance.     

Traffic Signals Control with Adaptive Fuzzy Controller in Urban Road Network

An adaptive fuzzy logic controller （AFC） is presented for the signal control of the urban traffic network. The AFC is composed of the signal control system-oriented control level and the signal controller-oriented fuzzy rules regulation level. The control level decides the signal timings in an intersection with a fuzzy logic controller. The regulation level optimizes the fuzzy rules by the Adaptive Rule Module in AFC according to both the system performance index in current control period and the traffic flows in the last one. Consequently the system performances are improved. A weight coefficient controller （WCC） is also developed to describe the interactions of traffic flow among the adjacent intersections. So the AFC combined with the WCC can be applied in a road network for signal timings. Simulations of the AFC on a real traffic scenario have been conducted. Simulation results indicate that the adaptive controller for traffic control shows better performance than the actuated one.     

Hardware implementation of the quadruple inverted pendulum with single motor

Inverted pendulums are always used to verify some qualities and effect of certain control theory or method. Single or double inverted pendulum control system has been extensively studied for education and research purposes. However how to control a triple inverted pendulum is a difficult problem, which just a couple of control experts can solve including us. Undoubtedly, to implement controlling of a quadruple inverted pendulum is a very difficult problem, but we first successfully accomplished it using variable universe adaptive fuzzy control method in August, 2002. In this paper, a controller for a quadruple inverted pendulum is demonstrated using the variable universe adaptive fuzzy control theory.     

Optimal Fuzzy PID Controller with Adjustable Factors and Its Application to Intelligent Artificial Legs

A new kind of optimal fuzzy PID controller is proposed, which contains two parts. One is an on-line fuzzy inference mechanism and another is a conventional PID controller. In the fuzzy inference mecha-nism, three adjustable factors χp, χi, and χd are introduced. Their function is to further modify and op-timize the result of the fuzzy inference to make the controller have the optimal control effect on a given ob-ject. The optimal values of these factors are determined based on the ITAE criterion and the flexible poly-hedron search algorithm of Nelder and Mead. This PID controller has been used to control a D.C. motor of the intelligent artificial leg designed by the authors. The result of computer simulation indicates that the design of this controller is very effective and can be widely used to control different kinds of objects and processes.     

应用自适应模糊控制实施船舶动力定位

在船舶动力定位中引入自适应模糊控制方法,即采用近似的线性模型通过Ｋａｌｍａｎ滤波得到船舶低频运动的状态估计值,模糊化后作为模糊控制器的输入实现定位控制。模糊控制器的核心为逢适应模糊逻辑系统,由于它具有任意的非线性映射能力,从而使控制器的参数能够在定位过程中不断调整,以适应外部环境变化。仿真结果表明,该方法在不同海况下均能达到很好的控制效果。     

一类不确定切换模糊系统的鲁棒控制

针对不确定的模糊系统,提出一类不确定切换模糊系统的鲁棒控制问题.使用切换技术及Lyapunov函数方法构造出连续状态反馈控制器,使得对于所有允许的不确定性,相应的闭环系统渐近稳定,同时设计可以实现系统全局渐近稳定的切换律.模型中的每个切换系统的子系统是不确定模糊系统,取常用的平行分布补偿PDC控制器,主要条件以凸组合的形式给出,具有较强的可解性.这类混杂控制系统对参数变化具有很强的鲁棒性.计算机仿真结果表明设计方法的可行性与有效性.     

基于模糊控制的直线感应电动机转差频率矢量控制系统

建立了直线感应电动机的矢量控制数学模型,提出了速度闭环、磁链开环的转差频率矢量控制设计方法.设计了速度模糊控制器,对电机在起动和负载情况下进行了仿真实验.结果表明,采用模糊控制实现的直线感应电动机转差频率型矢量控制系统比PI控制系统具有更强的鲁棒性,系统的稳态性能和动态性能大大提高.     

机器人模糊学习控制

针对机器人轨迹跟踪控制问题,提出一种模糊学习算法,并设计出结构合理的模糊学习控制器,该控制器通过自身从过去趋向的学习能力可自动调整其模糊控制规则。将这种方法用于一个两自由度机械手的控制,仿真结果显示控制效果良好,所提出的控制器比惯用的模糊控制器展示出更良好的应用前景。     

基于改进粒子群优化PID参数的风力除尘控制系统的研究

对卷接机组集中工艺风力除尘系统控制需求及工艺特点进行了研究,针对风力系统中压力和流量之间存在非线性与强耦合性的特点,以及控制系统中传统自动化科学技术(proportional plus integral plus derivative controller,PID)控制和现有的模糊PID控制自适应和鲁棒性较差、系统稳定性能不理想的问题,文中提出对角矩阵解耦方法将压力和流量进行解耦,利用改进粒子群算法(particle swarm optimization,PSO)优化参数的PID控制器对两者进行独立控制。通过仿真软件和可编程序逻辑控制器(programmable logic controller,PLC)程序对算法进行实现。位置阶跃响应实验粒子寻优实验结果表明:该方法在阶跃响应上升时间、最大超调量和响应速度上均有很好的优化效果,即时控制调整变频器频率以及阀门开度,使主风管压力波动在0. 5%～1%内,流量波动控制在0. 4%～0. 8%内。     

负荷频率系统的LFC模糊监督控制器设计

提出了一种基于模糊MAMDANI推理算法的模糊监督控制器,采用各个区域的频率偏差作为控制器的输入。监督控制器作为一种前馈补偿,设计输出为一个ACE的倍数,加快调节过程,到达稳态。经过实验仿真数据对比,说明提出的监督控制器能有效提高系统的稳定性。     

模糊控制与PID控制方法的比较

研究了常规模糊控制器与ＰＩＤ控制器的关系．基于Ｔ－Ｓ模型,在一定的附加条件下,对这些模糊控制器进行了分析,理论上给出了这类模糊控制器与ＰＩＤ控制器参数间的定量关系式,并指出两者间的本质联系．仿真结果表明了模糊控制器与ＰＩＤ控制器的相似性,多个规则的模糊控制器要优于ＰＩＤ控制器,同时给出了一类模糊ＰＩＤ复合控制器（ＴＳ－ＰＩＤ）的设计方法．该类复合控制器兼有模糊控制器与ＰＩＤ控制器优点,具有较深远的应用前景．     

区间Ⅱ型变论域自适应模糊逻辑控制器

在变论域自适应模糊控制方法的基础上,结合Ⅱ型模糊集较强的鲁棒性和处理不确定性问题的能力,设计了一种区间Ⅱ型变论域自适应模糊逻辑控制器.为了使控制器保持在最优状态,采用粒子群优化算法来优化隶属度函数;然后由Lyapunov方法证明了区间Ⅱ型变论域自适应模糊逻辑控制器的稳定性.对Duffing系统和1维6卷混沌系统的仿真表明,区间Ⅱ型变论域自适应模糊逻辑控制器可以很好地跟踪参考信号,较之变论域模糊逻辑控制器,其可以有效地防止抖震且控制量较小.     

基于模糊PID控制的变频空调电气控制系统的设计

本文设计了一种冷热两用的热泵型分体式房间变频空调的电气控制系统,分为室内机和室外机两部分。变频电路采用智能功率模块,利用专用单片机对其进行控制。然后在硬件电路设计的基础上,编制了室内、外机的系统控制软件。选定模糊控制方案,设计了二维模糊温度控制器,提出了一种适于实时控制的温度控制器,并通过仿真验证了该方法的合理性。     

基于uCOS-II的模糊自适应温度控制系统设计

针对车间温度控制系统具有非线性、滞后性和时变性等特点,提出了一种改进型的模糊自适应PID控制器。该控制器通过在线调整学习速率因子和PID参数增量,并结合积分分离思路,实现PID参数的自适应调节。仿真结果表明该控制器优于传统PID控制和传统模糊自适应PID控制。控制系统采用PIC24F作为主控芯片,结合操作系统uCOS-II的实时性、可靠性以及模糊自适应控制的非线性、时变性等特点,通过实验成功的实现对温度准确控制。