This paper presents an application of an Ant Colony Optimization （ACO） algorithm to optimize the parameters in the design of a type of nonlinear PID controller. The ACO algorithm is a novel heuristic bionic algorith...This paper presents an application of an Ant Colony Optimization （ACO） algorithm to optimize the parameters in the design of a type of nonlinear PID controller. The ACO algorithm is a novel heuristic bionic algorithm, which is based on the behaviour of real ants in nature searching for food. In order to optimize the parameters of the nonlinear PID controller using ACO algorithm, an objective function based on position tracing error was constructed, and elitist strategy was adopted in the improved ACO algorithm. Detailed simulation steps are presented. This nonlinear PID controller using the ACO algorithm has high precision of control and quick response.展开更多
An improved particle swarm algorithm based on the D-Tent chaotic model is put forward aiming at the standard particle swarm algorithm. The convergence rate of the late of proposed algorithm is improved by revising the...An improved particle swarm algorithm based on the D-Tent chaotic model is put forward aiming at the standard particle swarm algorithm. The convergence rate of the late of proposed algorithm is improved by revising the inertia weight of global optimal particles and the introduction of D-Tent chaotic sequence. Through the test of typical function and the autotuning test of proportionalintegral-derivative （PID） parameter, finally a simulation is made to the servo control system of a permanent magnet synchronous motor （PMSM） under double-loop control of rotating speed and current by utilizing the chaotic particle swarm algorithm. Studies show that the proposed algorithm can reduce the iterative times and improve the convergence rate under the condition that the global optimal solution can be got.展开更多
a new strategy combining an expert system and improved genetic algorithms is presented for tuning proportional-integral-derivative （PID） parameters for petrochemical processes. This retains the advantages of genetic...a new strategy combining an expert system and improved genetic algorithms is presented for tuning proportional-integral-derivative （PID） parameters for petrochemical processes. This retains the advantages of genetic algorithms, namely rapid convergence and attainment of the global optimum. Utilization of an orthogonal experiment method solves the determination of the genetic factors. Combination with an expert system can make best use of the actual experience of the plant operators. Simulation results of typical process systems examples show a good control performance and robustness.展开更多
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 co...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.展开更多
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 responsiv...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.展开更多
This paper presents a fuzzy tuning system for real-time industrial PID （proportional-integral-derivative） controllers. The algorithm set the proportional gain, integral time and derivative time of a classical PID st...This paper presents a fuzzy tuning system for real-time industrial PID （proportional-integral-derivative） controllers. The algorithm set the proportional gain, integral time and derivative time of a classical PID structure according to the set point, error and error derivative of the process, respectively. The tuning of the PID controller is based on a fuzzy inference machine. The set of rules of the fuzzy inference machine was obtained by experts engineering. The system is tested in an austempering process but can be applied in any industrial plant. Besides, an analysis between the response of the process with a PID controller and the system of fuzzy auto-tuning for P1D proposed was made.展开更多
利用SIEMENS公司S7-200系列PLC作为控制器,凭借其强大的PID指令和较强的浮点数计算能力,实现复杂过程控制实验的设计与研究,并使用SIEMENS公司软件系统Win CC(Windows Control Center)进行上位机监控和过程控制数据的保存。本文对S7-20...利用SIEMENS公司S7-200系列PLC作为控制器,凭借其强大的PID指令和较强的浮点数计算能力,实现复杂过程控制实验的设计与研究,并使用SIEMENS公司软件系统Win CC(Windows Control Center)进行上位机监控和过程控制数据的保存。本文对S7-200系列PLC的PID应用进行了分析,根据过程控制系统提出的总体要求和技术指标,对液位、压力、流量、温度等过程控制实验曲线进行分析,阐述PID算法各个环节的作用,总结PID的实验整定方法,以及PID整定方法选用的原则。展开更多
针对开关磁阻电机PID(Proportional Integral Derivative)控制中存在的稳定性差、参数调节困难等问题,文中基于传统开关磁阻电机PID调速系统引入鲸鱼优化算法,将改进时间绝对误差函数作为适应度函数对K_(p)、K_(i)、K_(d)这3个控制参数...针对开关磁阻电机PID(Proportional Integral Derivative)控制中存在的稳定性差、参数调节困难等问题,文中基于传统开关磁阻电机PID调速系统引入鲸鱼优化算法,将改进时间绝对误差函数作为适应度函数对K_(p)、K_(i)、K_(d)这3个控制参数进行整定。在MATLAB/Simulink仿真平台搭建了三相6/4极开关磁阻电机的PID参数整定系统,分析了传统经验PID调参和算法整定参数的效果对比,并将鲸鱼算法的优化效果与粒子群算法、遗传算法和灰狼优化算法结果进行对比。仿真结果表明,所提方法获得的PID参数较精确,其效果优于3种对比算法。相比于经验法整定参数,鲸鱼算法整定参数响应速度提升了51.10%,误差减小了0.67%,使调速系统具有更快、更稳定的响应特性。展开更多
文摘This paper presents an application of an Ant Colony Optimization （ACO） algorithm to optimize the parameters in the design of a type of nonlinear PID controller. The ACO algorithm is a novel heuristic bionic algorithm, which is based on the behaviour of real ants in nature searching for food. In order to optimize the parameters of the nonlinear PID controller using ACO algorithm, an objective function based on position tracing error was constructed, and elitist strategy was adopted in the improved ACO algorithm. Detailed simulation steps are presented. This nonlinear PID controller using the ACO algorithm has high precision of control and quick response.
基金supported by the National Natural Science Foundation of China(61301011)the Fundamental Research Funds for the Central Universities(HIT.NSRIF.2012010)+1 种基金the China Postdoctoral Science Foundation(2013M540279)the Heilongjiang Postdoctoral Financial Assistance(LBH-Z11157)
文摘An improved particle swarm algorithm based on the D-Tent chaotic model is put forward aiming at the standard particle swarm algorithm. The convergence rate of the late of proposed algorithm is improved by revising the inertia weight of global optimal particles and the introduction of D-Tent chaotic sequence. Through the test of typical function and the autotuning test of proportionalintegral-derivative （PID） parameter, finally a simulation is made to the servo control system of a permanent magnet synchronous motor （PMSM） under double-loop control of rotating speed and current by utilizing the chaotic particle swarm algorithm. Studies show that the proposed algorithm can reduce the iterative times and improve the convergence rate under the condition that the global optimal solution can be got.
文摘a new strategy combining an expert system and improved genetic algorithms is presented for tuning proportional-integral-derivative （PID） parameters for petrochemical processes. This retains the advantages of genetic algorithms, namely rapid convergence and attainment of the global optimum. Utilization of an orthogonal experiment method solves the determination of the genetic factors. Combination with an expert system can make best use of the actual experience of the plant operators. Simulation results of typical process systems examples show a good control performance and robustness.
文摘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.
文摘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.
文摘This paper presents a fuzzy tuning system for real-time industrial PID （proportional-integral-derivative） controllers. The algorithm set the proportional gain, integral time and derivative time of a classical PID structure according to the set point, error and error derivative of the process, respectively. The tuning of the PID controller is based on a fuzzy inference machine. The set of rules of the fuzzy inference machine was obtained by experts engineering. The system is tested in an austempering process but can be applied in any industrial plant. Besides, an analysis between the response of the process with a PID controller and the system of fuzzy auto-tuning for P1D proposed was made.
文摘利用SIEMENS公司S7-200系列PLC作为控制器,凭借其强大的PID指令和较强的浮点数计算能力,实现复杂过程控制实验的设计与研究,并使用SIEMENS公司软件系统Win CC(Windows Control Center)进行上位机监控和过程控制数据的保存。本文对S7-200系列PLC的PID应用进行了分析,根据过程控制系统提出的总体要求和技术指标,对液位、压力、流量、温度等过程控制实验曲线进行分析,阐述PID算法各个环节的作用,总结PID的实验整定方法,以及PID整定方法选用的原则。
文摘针对开关磁阻电机PID(Proportional Integral Derivative)控制中存在的稳定性差、参数调节困难等问题,文中基于传统开关磁阻电机PID调速系统引入鲸鱼优化算法,将改进时间绝对误差函数作为适应度函数对K_(p)、K_(i)、K_(d)这3个控制参数进行整定。在MATLAB/Simulink仿真平台搭建了三相6/4极开关磁阻电机的PID参数整定系统,分析了传统经验PID调参和算法整定参数的效果对比,并将鲸鱼算法的优化效果与粒子群算法、遗传算法和灰狼优化算法结果进行对比。仿真结果表明,所提方法获得的PID参数较精确,其效果优于3种对比算法。相比于经验法整定参数,鲸鱼算法整定参数响应速度提升了51.10%,误差减小了0.67%,使调速系统具有更快、更稳定的响应特性。
