Self-adaptive PID controller of microwave drying rotary device tuning on-line by genetic algorithms

The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and with multivariable nonlinear interaction of microwave and materials. The conventional PID control strategy incorporated with optimization GA was put forward to maintain the optimum drying temperature in order to keep the moisture content below 1%, whose adaptation ability included the cost function of optimization GA according to the output change. Simulations on five different industrial process models and practical temperature process control system for selenium-enriched slag drying intensively by using IMDRDWM were carried out systematically, indicating the reliability and effectiveness of control design. The parameters of proposed control design are all on-line implemented without iterative predictive calculations, and the closed-loop system stability is guaranteed, which makes the developed scheme simpler in its synthesis and application, providing the practical guidelines for the control implementation and the parameter design.

A Design of a PID Self-Tuning Controller Using LabVIEW

In this paper a trial has been made to design a simple self-tuning LabVIEW-based PID controller. The controller uses an open-loop relay test, calculates the tuned parameters in an open loop mode of operation before it updates controller parameters and runs the process as a closed-loop system. The controller reacts on a persistent offset error value as a result of load disturbance or a set point change. Practical results show that such a controller may be recommended to control a variety of industrial processes. A GUI was developed to facilitate control-mode selection, the setting of controller parameters, and the display of control system variables. GUI makes it possible to put the controller in manual or self-tuning mode.

Design and simulation about a self-Tuning fuzzy-PID controller

Fuzzy logic has attracted the attention of structural control engineers during the last few years,because fuzzy logic can handle nonlinearities,uncertainties,and heuristic knowledge effectively and easily.In this paper,a self-Tuning fuzzy-PID control method which used the technology of the fuzzy control and PID control unified is presented.These techniques can visualize the results and processes for structure stress.These techniques will also provide convenience for engineers and users,and have high practical values.The MATLAB simulation result shows that the system precision and the efficiency are very high and the static error is small,and robustness was also validated.

Development of an Enhanced Self-Tuning RBF-PID Controller for Achieving Higher Energy-Efficient Process Control

Proportional, integral and derivative (PID) control strategy has been widely applied in heating systems in decades. To improve the accuracy and the robustness of PID control, self-tuning radial-basis-function neural network PID (RBF-PID) is developed and used. Even though being popular, during the control process both of PID and RBF-PID control strategy are inadequate in achieving simultaneous high energy-efficiency and good control accuracy. To address this problem, in this paper we develop and report an enhanced self-tuning radial-basis-function neural network PID (e-RBF-PID) controller. To identify the superiority of e-RBF-PID, following works are conducted and reported in this paper. Firstly, four controllers, i.e., on-off, PID, RBF-PID and e-RBF-PID are designed. Secondly, in order to test the performance of the e-RBF-PID controller, an experimental water heating system is constructed for being controlled. Finally, the energy consumption for the four controllers under the three control scenarios is investigated through experiments. The experimental results indicate that in the three scenarios, the developed e-RBF-PID controller outperforms on-off controller as having higher accuracy. Compared to the PID controller, the e-RBF-PID controller has higher speed in control, and the experimental results show that settling time savings is between 12.6% - 49.0%. Most importantly, less control energy consumption is obtained if using the e-RBF-PID controller. It is found that up to 28.5% energy consumption can be saved. Therefore, it is concluded that the proposed e-RBF-PID is capable of enhancing energy efficiency during control process.

Fuzzy self-tuning PID control of the operation temperatures in a two-staged membrane separation process

为从精炼厂气体的氢恢复的一个二阶段的膜分离过程被介绍。煤气的膜分离过程的原则和操作温度的影响被分析。因为常规 PID 控制器是困难的使操作温度稳定，一个模糊自我调节的 PID 控制算法被建议。申请证明算法是有效的，两个阶段的操作温度能稳定地被控制，并且氢恢复单位的操作灵活性和适应性安全地被提高。这研究打一个基础优化膜分离进程的控制并且因此保证膜性能。

AUTOMATIC TUNING OF PID CONTROLLERS IN THE THERMAL POWER UNIT LOAD CONTROL SYSTEM

A method of measuring the interactions in a multivariable control sys-tem(MVCS)in time domain is defined in this paper.An intelligent decoupling com-pensator is designed in terms of the concept of fuzzy control,so that the auto-tuningof controllers’ parameters in a 2×2 MVCS can be turned into that of two independentsingle-loop control systems(SLCS).The method presented in the paper has success-fully been used in a simulation experiment on the automatic tuning of a coordinatedcontrol system(CCS)in the drum-boiler turbogenerating unit(DBTU)and the simu-lation results axe satisfactory.

Neural Model-Based Self-Tuning PID Strategy Applied to PEMFC

This paper illustrates the benefits of a self-tuning PID strategy applied to a proton exchange membrane fuel cell system. Controller parameters are updated on-line, at each sampling time, based on an instantaneous linearization of an artificial neural network model of the process and a General Minimum Variance control law. The self-tuning PID scheme allows managing nonlinear behaviors of the system while avoiding heavy computations. The applicability, efficiency and robustness of the proposed control strategy are experimentally confirmed using varying control scenarios. In this aim, the original built-in controller is overridden and the self-tuning PID controller is implemented externally and executed on-line. Experimental results show good performance in setpoint tracking accuracy and robustness against plant/model mismatch. The proposed strategy appears to be a promising alternative to heavy computation nonlinear control strategies and not optimal linear control strategies.

模糊自整定PID的液压马达驱动机床主轴速度控制研究

液压马达驱动机床主轴系统具有参数时变和高度非线性,传统PID控制器控制精度不高。针对液压马达驱动机床主轴系统速度控制问题,采用模糊自整定PID控制器实现液压马达驱动机床主轴系统的有效控制,并对控制效果进行仿真验证。构造了液压马达驱动机床主轴系统模型简图,建立了液压马达驱动机床主轴系统数学模型。对传统PID控制器参数,用模糊控制器进行实时整定,开发了模糊自整定PID控制器。最后,采用MATLAB对液压马达驱动机床主轴系统进行仿真。同时,与传统PID控制器的计算结果进行对比和分析。仿真结果显示:采用模糊自整定PID控制器的液压马达驱动机床主轴转速超调量小,具有更快的响应时间,跟踪精度高,同时系统能耗减少20%左右;即使受到较大随机干扰,模糊自整定PID控制器也能快速消除干扰,使机床主轴转速处于受控状态。采用模糊自整定PID控制器可以有效提高液压马达驱动机床主轴系统的动态稳定性以及抗干扰能力。

基于STM32的密炼机自整定PID温控系统设计

针对密炼机温度控制系统中人工整定PID带来的系统响应不及时、误差大等问题,该文设计了一种基于STM32的自整定PID温度控制系统。对于电动阀只能单极性调节问题,通过设置适当的工艺点来控制继电输出。为提高震荡曲线的辨识,采用参数归一化方法计算震荡曲线的临界增益。考虑密炼机的工作环境和系统响应曲线的频率特性,加入带有临界滞环控制的继电控制方法,提高了特征参数的精确性,更好地整定了PID参数。应用结果表明,基于STM32的PID整定温度控制系统能够将温度误差控制在1℃左右,且控制时间相比于人工PID控制系统提高了30%,极大地满足了密炼机的温度控制要求,具有良好的实用价值。

基于参数自整定模糊PID的BLDC控制研究

为解决传统PID控制在无刷直流电机调速系统中的控制精度低、效果不佳等问题,设计了一种基于参数自整定模糊PID控制的调速系统。通过在Matlab/Simulink仿真软件中建立了无刷直流调速系统的模型,分别采用传统PID控制、模糊PID控制和参数自整定模糊PID控制来对转速环进行调控,而电流环则采用PID控制。通过对比研究结果发现,采用参数自整定模糊PID控制的调速系统具有许多优势。系统的超调量较小,控制效果较好,同时提高了系统的鲁棒性。通过搭建模型并进行仿真实验,证明了采用参数自整定模糊PID控制的调速系统在解决无刷直流电机调速系统控制精度低、效果不佳等问题方面具有优势。这一方法能够有效提升系统的控制性能,并增强系统的鲁棒性。该无刷直流电机的调速系统可以稳定、可靠运行,满足使用需求。

基于继电反馈PID自整定的加热系统

某工厂对某种液体进行加热控制,针对某液体复杂的反应过程,设计出带自整定功能的PID自动调节加热设备。该设计以意法半导体公司(ST)的STM32F103C8T6为控制器,以PT100为温度采集元件,控制可控硅进行过零功率调节,通过MCGS触摸屏来显示,设定有关波形和参数,在控制过程中,可以根据有关加热要求选择多种整定参数,以满足液体的不同动态响应类型。该文主要介绍系统硬件组成原理框图,给出系统主要硬件电路图和自整定算法的工作流程,并对PID程序编制的一些关键点进行说明。实验证明加热系统能满足工厂要求。

足式机器人腿部关节改进单神经网络PID控制算法研究

为了满足液压足式机器人在复杂环境中实现精确、快速的腿部关节控制需求,把单神经网络PID能够实时调节参数的优点运用到足式机器人液压机械腿关节的控制中,在单神经网络PID的基础上增加机械腿关节的位置和速度控制算法,形成改进单神经网络PID,实现了对神经元比例参数自调整、PID参数的自整定,能够较好地适应内、外参数的变化,增强了腿部关节的快速性、精确性。在Simulink中进行建模仿真以及在设计的以STM32为中央处理芯片的控制平台上进行实验测试,结果表明:改进单神经网络PID在足式液压机器人的腿部关节控制中具有响应速度快、超调量小、控制精度高、鲁棒性强等优点。

基于模糊自整定PID的双容水箱串级液位控制系统研究

双容水箱串级液位控制具有抗干扰能力强、超调量小、过渡过程较短等特点。传统的PID算法和参数整定方法难以达到期望的控制效果。因此,针对双容水箱串级液位控制,利用模糊推理的方法实现在线自整定PID参数,设计相应的模糊PID控制器,基于Simulink仿真建模,对比传统的PID与模糊自整定PID输出响应曲线发现,该模糊自整定PID系统具有更好的鲁棒性,抑制系统超调以及对控制参数变化的自适应能力更强。

Parameter Self - Learning of Generalized Predictive Control Using BP Neural Network

This paper describes the self—adjustment of some tuning-knobs of the generalized predictive controller(GPC).A three feedforward neural network was utilized to on line learn two key tuning-knobs of GPC,and BP algorithm was used for the training of the linking-weights of the neural network.Hence it gets rid of the difficulty of choosing these tuning-knobs manually and provides easier condition for the wide applications of GPC on industrial plants.Simulation results illustrated the effectiveness of the method.

PID 性能评估与整定系统在大型烯烃厂的应用

对PID性能评估与整定系统在某烯烃公司的运用情况进行了介绍。通过对各控制回路的性能评估,一张表就知晓几千个回路的运行情况,对平稳率不好的回路进行自整定,实现了自控率、平稳率、仪表和阀门运行情况的实时统计和分析,显著提高了装置的自控水平和管理效率。

基于模糊自整定PID的水箱液位控制

水箱液位控制系统具有时滞性、大惯性、不确定性等特点,采用传统的比例积分微分控制器(Proportional-Integral-Derivative,PID)调节难以实现液位的快速、准确调节。因此引入模糊控制理论,利用其自适应学习能力,根据实际情况调节PID控制参数,以更好地适应水箱液位控制系统的参数变化。对水箱液位控制系统进行仿真实验,实验结果表明,模糊自整定PID控制有效减少了系统响应时间和系统超调量,加强了系统的快速响应性和鲁棒性。此外,还通过随机扰动仿真实验验证了模糊自整定PID控制在抵抗干扰方面的有效性。

基于HS-PSO算法的PID控制器参数自整定

针对粒子群算法(PSO)算法局部搜索能力差的问题,提出一种对PID控制器参数进行自整定的基于和声搜索(HS)的改进粒子群优化算法(HS-PSO)。通过引入种群进程因子对惯性权重进行自适应调节以提高PSO算法的收敛速度。另外在PSO进化过程中每代产生的最优个体以新陈代谢方式进入和声记忆库中并进行和声搜索,以克服粒子群优化算法局部搜索能力差的缺陷。针对典型对象进行PID控制器参数自整定,仿真和工程应用结果表明所提HS-PSO算法较他它智能优化算法具有更好的全局优化能力。

基于数据挖掘的IMC-PID在线自整定算法的实现

提出了利用过程历史数据自动进行数据挖掘的PID参数在线自整定算法。算法以PID回路的动态响应特性为依据,通过给定ε-不敏感损失函数、辨识信任度函数,从可行数据集中选取有效数据集,以此作为回路参数自整定的有效数据。为确保PID控制尽可能达到最佳性能和鲁棒性,提出了基于对象组进行IMC-PID参数整定的方法。算法已应用于多个生产装置上,实际的投运结果表明,这种算法具有简便易用,推广能力强等特点,是PID参数整定算法中一种切实可行的算法。

基于参数自整定模糊PID控制器的TSMC-PMSM矢量控制

针对由双级矩阵变换器驱动的永磁同步电机(TSMC-PMSM)矢量控制系统存在的响应速度较慢、稳态性能差的缺陷,提出了在线自整定模糊PID控制算法以实现优化TSMC-PMSM矢量系统的调速性能。介绍了双级矩阵变换器与永磁同步电机的矢量控制技术相结合,并在此基础上搭建了采用模糊PID控制器的TSMC-PMSM矢量控制系统,并建立Matlab/Simulink仿真模型。仿真结果表明:模糊PID控制器减少了系统的超调,提高了矢量控制系统的鲁棒性,并且改善了变换器网侧的电能质量。

基于Matlab的2种Fuzzy-PID控制器的设计与仿真

针对电温控制,提出2种Fuzzy-PID控制方式Fuzzy-PID阈值控制和Fuzzy-PID参数自整定控制,运用仿真软件Matlab实现这2种Fuzzy-PID温度控制器的设计与仿真.Fuzzy-PID阈值控制器选用给定温度偏差值作为阈值,阈值以上的大偏差范围内采用模糊控制,温差小于阈值时采用PID控制;Fuzzy-PID参数自整定控制器先由模糊控制策略得到自适应的PID参数KP,KI,KD,再采用这个改进的PID控制器来控制全局系统.仿真结果表明2种Fuzzy-PID控制器都具有良好的动态和稳态性能.