The Distribution Population-based Genetic Algorithm for Parameter Optimization PID Controller

Enlightened by distribution of creatures in natural ecology environment, the distributionpopulation-based genetic algorithm (DPGA) is presented in this paper. The searching capability ofthe algorithm is improved by competition between distribution populations to reduce the search zone.This method is applied to design of optimal parameters of PID controllers with examples, and thesimulation results show that satisfactory performances are obtained.

Optimal fuzzy PID controller with adjustable factors based on flexible polyhedron search algorithm

A new kind of optimal fuzzy PID controller is proposed, which contains two parts. One is an on line fuzzy inference system, and the other is a conventional PID controller. In the fuzzy inference system, three adjustable factors x p, x i , and x d are introduced. Their functions are to further modify and optimize the result of the fuzzy inference so as to make the controller have the optimal control effect on a given object. The optimal values of these adjustable factors are determined based on the ITAE criterion and the Nelder and Mead′s flexible polyhedron search algorithm. This optimal fuzzy PID controller has been used to control the executive motor of the intelligent artificial leg designed by the authors. The result of computer simulation indicates that this controller is very effective and can be widely used to control different kinds of objects and processes.

CONTROLLING HYPERCHAOS IN PLANAR SYSTEMS BY ADJUSTING PARAMETERS

For the two_parameter family of planar mapping, a method to stabilize an unstable fixed point without stable manifold embedding in hyperchaos is introduced. It works by adjusting the two parameters in each iteration of the map. The explicit expressions for the parameter adjustments are derived, and strict proof of convergence for method is given.

Design of PID controller with incomplete derivation based on differential evolution algorithm

To determine the optimal or near optimal parameters of PID controller with incomplete derivation, a novel design method based on differential evolution （DE） algorithm is presented. The controller is called DE-PID controller. To overcome the disadvantages of the integral performance criteria in the frequency domain such as IAE, ISE, and ITSE, a new performance criterion in the time domain is proposed. The optimization procedures employing the DE algorithm to search the optimal or near optimal PID controller parameters of a control system are demonstrated in detail. Three typical control systems are chosen to test and evaluate the adaptation and robustness of the proposed DE-PID controller. The simulation results show that the proposed approach has superior features of easy implementation, stable convergence characteristic, and good computational efficiency. Compared with the ZN, GA, and ASA, the proposed design method is indeed more efficient and robust in improving the step response of a control system.

Design of PID controller with incomplete derivation based on ant system algorithm

A new and intelligent design method for PID controller with incomplete derivation is proposed based on the ant system algorithm ( ASA) . For a given control system with this kind of PID controller, a group of optimal PID controller parameters K p * , T i * , and T d * can be obtained by taking the overshoot, settling time, and steady-state error of the system's unit step response as the performance indexes and by use of our improved ant system algorithm. K p * , T i * , and T d * can be used in real-time control. This kind of controller is called the ASA-PID controller with incomplete derivation. To verify the performance of the ASA-PID controller, three different typical transfer functions were tested, and three existing typical tuning methods of PID controller parameters, including the Ziegler-Nichols method (ZN),the genetic algorithm (GA),and the simulated annealing (SA), were adopted for comparison. The simulation results showed that the ASA-PID controller can be used to control different objects and has better performance compared with the ZN-PID and GA-PID controllers, and comparable performance compared with the SA-PID controller.

A method of tuning PID parameters for P-GMAW based on physical experiments

To improve welding quality, a method of proportional-integral-differential （PlD） parameters tuning based on pulsed gas metal arc welding （P-GMAW） control was put forward. Aiming at the request of dynamic responsiveness of PGMA W constant current control, a self-developed welding waveform wavelet analyzer was employed. By tuning the proportional parameter, integration time and differential time in sequence, the optimal PID parameters could be achieved. The results showed that, due to the PID parameters tuned by this method, the welding process was stable and the weld bead appearance was nice. The requirement of dynamic responsiveness of P-GMAW constant current control was fully met.

Auto-Tuning Parameters of Fractional PID Controller Design for Air-Conditioning Fan Coil Unit

The traditional integer order PID controller manipulates the air-conditioning fan coil unit(FCU)that offers cooliug and heatins loads to each air-conditioning room in summer and winter,respectivelv.In order to maintain a steady indoor temperature in summer and winter,the control quality cannot meet the related requirements of air-conditioning automation,such as large overshoot,large steady state error.long regulating time,etc.In view of these factors,this paper develops a fractional order PID controller to deal with such problem associated with FCU.Then,by varving mutation factor and crossover rate of basic differential evolution algorithmadaptivelv,a modified differential evolution algorithm(MDEA)is designed to tune the satisfactory values of five parameters of indoor temperature fractional order PID controller.This fractional order PID coutrol system is configured and the corresponding mumerical simulation is conducted by means of MATLAB software.The results indicate that the proposed fractional order PID control svstem and MDEA are reliable and the related control performance indexes meet with the related requirements of comfortable air-conditioning design and control criteria.

PID Controller Design Based on the Time Domain Information of Robust IMC Controller Using Maximum Sensitivity

The IMC(Internal Model Control) controller based on robust tuning can improve the robustness and dynamic performance of the system.In this paper,the robustness degree of the control system is investigated based on Maximum Sensitivity(Ms) in depth.And the analytical relationship is obtained between the robustness specification and controller parameters,which gives a clear design criterion to robust IMC controller.Moreover,a novel and simple IMC-PID(Proportional-Integral-Derivative) tuning method is proposed by converting the IMC controller to PID form in terms of the time domain rather than the frequency domain adopted in some conventional IMC-based methods.Hence,the presented IMC-PID gives a good performance with a specific robustness degree.The new IMC-PID method is compared with other classical IMC-PID rules,showing the flexibility and feasibility for a wide range of plants.

Design of an Intelligent Usage Parameter Control in ATM Networks

This paper presents the principle of the fuzzy associate memory controlled leaky bucket (FAMLB) and several concepts for Usage Parameter Control (UPC) in ATM networks. The multiplex weight and random fuzzy rules adjustment method in the system architecture are introdued. The conclusions show that the FAMLB is a better dynamic method of UPC than the traditional ones.

基于BPNN-PID控制策略的果蔬保鲜环境参数调控优化

【目的】开发新的控制策略,用于解决传统控制方法果蔬保鲜环境参数因时变性、非线性、滞后性强和惯性大等特点导致的控制精度低、鲁棒性弱等问题。【方法】将传统比例−积分−微分(Proportional-integral-derivative,PID)和BP神经网络(Back-propagation neural network,BPNN)算法相结合,开发一种基于BPNN-PID的控制策略,通过自主搭建的果蔬保鲜环境调控试验平台和自主设计的控制系统,研究不同控制策略对保鲜环境参数调控效果的影响。【结果】基于BPNN-PID控制策略的果蔬保鲜环境控制系统,环境温度超调量为1.7℃、稳定时间为80 min、稳态误差为±0.2℃,环境相对湿度超调量为2.8%、稳定时间为55 min,相对湿度稳定维持在80%~90%范围内。与传统PID控制策略相比,BPNN-PID控制策略环境温度超调量减小了2.1℃、稳态误差减小了0.3℃、稳定时间缩短了25 min,环境相对湿度超调量减小了2.2%、稳定时间缩短了25 min,环境参数波动幅度均有所降低。【结论】本文开发的果蔬保鲜环境控制系统呈现出良好的动态调整能力,具有较强的鲁棒性,控制性能明显提升,实现了保鲜环境参数的精准控制,满足果蔬保鲜贮藏要求。研究结果为果蔬保鲜环境参数调控提供了参考。

基于模糊-遗传算法的粗纱机出料传动系统PID参数优化方法

目前常规的粗纱机出料传动系统PID参数优化方法主要通过结合被控对象的稳态增益情况构建出优化函数,实现PID参数优化整合,忽略了实际运行工况下的干扰成分,导致参数优化效果不佳。对此,提出基于模糊-遗传算法的粗纱机出料传动系统PID参数优化方法。首先结合PID的系统阶跃响应曲线,以被控量的偏差变化率作为主要参数选取性能指标;然后通过引入负荷扰动模块以及频率干扰模块,对PID调节模块进行建模分析;最后结合模糊-遗传算法对最优适应度值进行求解,从而实现PID参数的有效优化,并对提出的方法进行优化效果检验。最终测试结果表明,采用提出的方法对PID参数进行优化整合时,控制输出曲线与理论输出曲线的拟合程度更高,具备较为理想的优化效果。

基于改进粒子群算法的PID控制参数优化

针对传统粒子群算法存在收敛速度慢,收敛精度低以及易陷入局部最优的问题,提出了一种融合中垂线策略的中垂线粒子群算法(MAPSO),同时引入惯性权重余弦调整策略,避免算法陷入局部最优。基于中垂线策略的游离粒子位置更新方法,能够加快粒子的收敛速度,从而增强算法的寻优速度和寻优精度。将改进的粒子群算法用于PID控制器参数优化,与Ziegler-Nichols(Z-N)公式法、线性递减惯性权重粒子群优化算法(MeanPSO)进行对比实验,结果表明中垂线粒子群算法精度更高,能够快速地整定PID参数,使控制系统响应函数性能指标更好。

红外干燥箱变论域模糊PID复合温控设计

烘干失重法粮食水分测定过程中,干燥箱温度的精准控制是检测结果准确性的重要保障。针对干燥箱温度变化过程非线性、时滞性和温控精度高的特点,提出一种基于粒子群模型参数辨识的变论域模糊PID复合温度控制策略。基于红外辐射干燥机理及能量守恒方程建立温控系统非线性模型,并利用粒子群优化算法完成参数辨识,通过设定二级偏差阈值,将变论域模糊PID算法结合Bang-Bang控制方法构成自适应分级复合控制策略。系统仿真实验表明:相较于常规PID控制和传统模糊PID控制方法,改进后的复合控制策略在超调量、调节时间和控制进度方面明显改善,在不同工作点温度下,控制误差均小于0.4℃,且具有较好的抗干扰能力。

基于改进麻雀搜索算法的PID参数整定系统设计

PID参数整定是PID控制中的一个关键步骤,常规的PID控制在一定程度上已被淘汰。为改善PID控制的效果和精度,文中将黄金正弦策略与精英反向学习策略相结合,提出一种改进的麻雀搜索算法。用23个标准函数对所提出的新方法进行了验证,实验结果证明了新方法的有效性。利用改进的麻雀搜索算法对PID控制参数进行了优化,并对该方法进行了仿真分析。结果表明,采用该方法进行PID参数整定时,其具有更好的稳定性、更高的精度和更好的性能。

DCS中串级PID调节器的用户功能块设计及应用

为了研究串级PID调节器在DCS中的应用,选用一种基于ABB-800F软件自定义的用户功能块作为研究对象,对该软件自带PID通用连续调节控制块(C_CU)展开PID调节器面板及程序设计,增强其功能,通过密码解锁,实现一种能够直观进行图形化界面参数整定及调试的通用PID软调节器,既可以单回路PID控制,又可以串级PID控制,且能在编程组态中像功能块FBD指令一样使用。该用户功能块串级PID软调节器在某化工甲醛生产中应用,已经取得良好的效果。

基于模糊控制的闪蒸罐PID控制器设计与仿真

PID控制器依照经验进行整定的方式需要花费大量时间和精力,而工业被控对象大都存在随时间变化、非线性等特性,PID控制的效果并不理想。以闪蒸罐压力控制为研究对象设计FUZZY-PID控制器。仿真结果表明:在PID调节后有超调情况下,FUZZY-PID控制器调节时间缩短约341.80 s,超调量减小约4.62%;在PID调节后无超调情况下,FUZZY-PID控制器调节时间缩短约395.60 s。抗干扰实验结果表明:在加入白噪声后,FUZZY-PID控制器与PID控制器控制效果差距不甚明显,都比较稳定,在同一时刻加入脉冲扰动后,FUZZY-PID控制器所需调节时间较PID控制器缩短约70.70 s,调节时间更短,更加稳定。说明相较于传统PID控制器,FUZZY-PID控制器调节时间更短、超调量更小、更加稳定。

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。

改进麻雀搜索算法的四旋翼PID参数优化设计

针对四旋翼无人机PID控制器参数人工整定复杂、费时且难以确保最优的问题,提出一种基于改进麻雀搜索算法的PID参数优化方法,用于四旋翼无人机控制系统。首先引入Piecewise混沌映射,增强初始种群分布的均匀性;其次在探索者位置更新公式中加入动态惯性权重,提升算法全局优化性能;最后结合自适应混合变异策略和历史最优值,增强变异的多样性、提高算法的搜索效率及精度。仿真结果表明,相比于标准麻雀搜索算法、粒子群算法和遗传算法,用改进麻雀搜索算法优化串级PID控制器参数,能够使控制系统具有更快的响应速度、更高的稳态精度。

基于改进WOA参数优化的反应釜PID控制器

为了解决工业中传统PID控制算法对于大时滞、非线性系统较难取得良好的控制效果的问题,提出一种基于改进鲸鱼优化算法(IWOA)的PID控制器整定算法。该算法考虑均衡算法的探查以及开发能力,引入非线性收敛因子;为了提高算法的勘察能力,避免陷入局部最优的情况,引入正余弦扰动因子改进位置更新策略;最后以化工反应中反应釜温度为被控对象,对其PID控制器进行参数自整定实验,并将结果与WOA算法、Z-N整定算法、PSO算法进行对比,验证了IWOA算法在优化PID控制器工程上的优越性。

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。