PID参数整定法的仿真

PID调节器的控制品质,主要取决于调节器的参数整定.计算量大是用理论计算方法整定PID调节器参数要解决的难题之一.针对PID调节器参数整定过程中计算复杂、计算量大的问题,提出了一种基于Matlab的调节器参数衰减频率特性整定法.该方法以Matlab为工具,将理论计算与仿真分析结合起来,根据控制要求计算并绘制出控制器整定参数关系曲线,对计算结果进行仿真,分析整定参数在解平面上变化时闭环系统的响应,从而确定出最佳的调节器整定参数.结果表明,对于不同的被控对象参数或不同的整定要求,该方法都能方便地求得最佳的调节器整定参数,使得采用理论计算法整定调节器参数具有了工程实用价值.     

基于幅值裕度和相位裕度的PID参数最优整定方法

给出一种基于幅值裕度和相位裕度的PID参数最优整定方法.首先,基于改进的D–分割法确定满足幅值裕度和相位裕度要求的控制参数稳定域,然后根据最大灵敏度函数、超调和调节时间定义控制器设计的目标函数,在所得到的控制参数稳定域中计算出一组最优的控制参数值.仿真结果表明,该整定方法能够保证闭环系统具有强鲁棒性、良好的跟踪性能和抗干扰性能.它不仅适用于稳定时滞对象,而且还适用不稳定时滞对象.     

Performance adaptive control General structure and a case study

This paper proposes a supervisory performance tuner for an adaptive controller. The objective of the performance tuner is to automatically adjust tuning parameters of an adaptive controller such that the actual setpoint-tracking and regulatory performance approaches user specifications and is maintained at this level at all times. Experimental evaluation of the prototype performance tuning loop with adaptive generalized predictive and pole placement controllers on a pilot-scale process demonstrates the practicality and utility of this idea.     

Development of a tunable method for PID controllers to achieve the desired phase margin

A new method for classical PID controller adjustment is broached. It allows to provide the required phase margin in a designed system. The mathematical formulation of the method and assumptions to implement it are given. The transfer functions of the plant are converted into real and imaginary parts at the frequency. Based on them, the analytical expressions for the controller settings are obtained. Thereby, the tuning parameters are the phase margin and crossover frequency. Some guidelines are provided for the selection of the crossover frequency on the basis of an integral performance index (ITAE). Several simulation examples are included to show the effectiveness of the proposed method.     

用改进的人工蜂群算法设计AVR系统最优分数阶PID控制器

分数阶PID控制器（FOPID）是标准PID控制器的一般形式.与PID控制器相比,FOPID有更多的参数,其参数整定也更复杂.本文提出一种基于环交换邻域和混沌的人工蜂群算法（CNC-ABC）,用于FOPID控制器的参数整定.CNC-ABC算法由于应用了环交换邻域,增加了解的搜索范围,从而能加快人工蜂群算法的收敛速度;同时利用混沌的遍历性使算法跳出局部最优解.用CNC-ABC算法优化AVR系统的FOPID控制器的参数.仿真结果表明,CNC-ABC算法整定的FOPID控制器比其它FOPID及PID控制器有较好的性能.     

Simultaneous automatic tuning of cascade control systems from closed-loop step response data

This study presents a novel automatic tuning method for cascade control systems in which both primary and secondary controllers are tuned simultaneously using a single closed-loop step test. The proposed technique identifies the required process information with the help of B-spline series representation for the step responses. The two proportional–integral–derivative (PID) controllers are then tuned using an internal model control (IMC) approach. Considering the rationale of cascade control, the secondary controller is designed for faster disturbance attenuation. Without requiring an additional experiment, the primary controller is designed based on an identified process model that accurately accounts for inner loop dynamics. Finally, this study includes robustness considerations in the controller tuning process, and develops explicit guidelines for the selection of the IMC tuning parameters, completing the automatic tuning procedure for cascade control systems. The proposed method is robust to measurement noise because of the filtering property of the B-splines, and can provide superior control performance for both set-point tracking and disturbance rejection. Simulation examples demonstrate the effectiveness of the proposed automatic tuning method.     

一种基于Matlab的参数自调整模糊控制器的设计方法

本文介绍了一种在MATLAB的模糊控制工具箱中,通过编写S函数实现对量化因子和比例因子的在线自动调整来设计模糊控制器,从而有效地实现参数自调整模糊控制器的设计方法。为了验证参数自调整模糊控制器的优越性,分别进行了空调温度控制系统的PID控制、常规模糊控制和参数自调整模糊控制的仿真研究。结果表明,参数自调整模糊控制器较之常规的模糊控制器,在被控对象特性变化或较大扰动的情况下,控制系统能保持较好的性能,是一种较理想的控制方法,具有广阔的发展前景。     

An automatic parking system using an optimized image-based fuzzy controller by genetic algorithms

An automatic parking system of a car-like mobile robot is an important issue in commercial applications. An image-based fuzzy controller for an automatic parking system of a car-like mobile robot was developed in previous work, where the membership functions were tuned by experimentally. The aim of this paper is to optimize the parameters of the membership functions, which were performed in previous work, using a genetic algorithm against the complicated tuning of the controller. The details of GA implementation, such as the design parameters and choice of fitness function, are described. Simulation results illustrate the effectiveness of the developed schemes.     

Optimum design of fractional order PID controller for AVR system using chaotic ant swarm

Fractional-order PID (FOPID) controller is a generalization of standard PID controller using fractional calculus. Compared to PID controller, the tuning of FOPID is more complex and remains a challenge problem. This paper focuses on the design of FOPID controller using chaotic ant swarm (CAS) optimization method. The tuning of FOPID controller is formulated as a nonlinear optimization problem, in which the objective function is composed of overshoot, steady-state error, raising time and settling time. CAS algorithm, a newly developed evolutionary algorithm inspired by the chaotic behavior of individual ant and the self-organization of ant swarm, is used as the optimizer to search the best parameters of FOPID controller. The designed CAS-FOPID controller is applied to an automatic regulator voltage (AVR) system. Numerous numerical simulations and comparisons with other FOPID/PID controllers show that the CAS-FOPID controller can not only ensure good control performance with respect to reference input but also improve the system robustness with respect to model uncertainties.     

An algorithm for computerized automatic tuning of power system stabilizers

The main objective of this paper is to relieve the power system engineers from the burden of the complex and time-consuming process of power system stabilizer (PSS) tuning. To achieve this goal, the paper proposes an automatic process for computerized tuning of PSSs, which is based on an iterative process that uses a linear matrix inequality (LMI) solver to find the PSS parameters. It is shown in the paper that PSS tuning can be written as a search problem over a non-convex feasible set. The proposed algorithm solves this feasibility problem using an iterative LMI approach and a suitable initial condition, corresponding to a PSS designed for nominal operating conditions only (which is a quite simple task, since the required phase compensation is uniquely defined). Some knowledge about the PSS tuning is also incorporated in the algorithm through the specification of bounds defining the allowable PSS parameters. The application of the proposed algorithm to a benchmark test system and the nonlinear simulation of the resulting closed-loop models demonstrate the efficiency of this algorithm.     

基于衰减频率特性的PID参数优化整定研究

用衰减频率特性法整定PID控制器可使闭环系统获得要求的衰减比,但是求得的整定参数的解是不确定的,因而难以确定最佳整定参数。就此,将基于衰减频率特性的PID控制器整定问题转换成带衰减比约束的控制器参数优化问题,首先用Matlab计算出整定参数的解曲线或解曲面,然后利用Simulink在仿真环境下寻优,获得期望性能下的最佳整定参数。仿真结果表明所提出的整定方法有效,且控制器具有良好的抗干扰能力。     

Differential evolutionary algorithm for TCSC-based controller design

In this paper, a systematic procedure for modelling, simulation and optimal tuning the parameters of a thyristor controlled series compensator (TCSC) controller, for the power system stability enhancement is presented. The design problem of the proposed controller is formulated as an optimization problem and differential evolution (DE) is employed to search for optimal controller parameters. A detailed analysis on the selection of objective function and controller structure on the effectiveness of the TCSC controller is carried out and simulation results are presented. The dynamic performance TCSC controller under various loading and disturbance conditions are analyzed and compared. Finally, the proposed design approach is extended to a multi-machine power system for simultaneous design of multiple and multi-type controllers.     

基于Bode''''s integrals的PID控制器的设计及其仿真

该文为一类稳定的最小相位控制对象提出一种新的PID控制器的参数整定方法。它是基于Bode’s integrals可以给出最小相位稳定系统的幅值与相位的关系，从而运用bode’s integrals近似表示控制对象G（jw）的幅值和相位的微分，然后将该简化结果用于PID控制器的设计中，从而得到新的控制器参数整定方法。该文中PID控制器的设计要求是，调整控制对象的Nyquist曲线在给定频率处的斜率，以提高闭环系统性能。最后，通过在matlab中对一类稳定的最小相位系统的计算机仿真例子比较，可以显示出该方法的优越性。     

Adaptive fuzzy PI controller with shifted control singletons

It is well known the fact that the design of a fuzzy control system is based on the human expert experience and control engineer knowledge regarding the controlled plant behavior. As a direct consequence, a fuzzy control system can be considered as belonging to the class of intelligent expert systems. The tuning procedure of a fuzzy controller represents a quite difficult and meticulous task, being based on prior data regarding good knowledge of the controlled plant. The complexity of the tuning procedure increases with the number of the fuzzy linguistic variables and, consequently, of the fuzzy inference rules and thus, the tuning process becomes more difficult. The paper presents a new design strategy for such expert fuzzy system, which improves their performance without increasing the number of fuzzy linguistic variables. The novelty consists in extending the classic structure of the fuzzy inference core with an intelligent module, which tunes one of the control singletons, providing a significant simplification of the design and implementation procedure. The proposed strategy implements a logical, not physical, supplementation of the linguistic terms associated to the controller output. Therefore, a fuzzy rules set with a reduced number of linguistic terms is used to implement the expert control system. This logical supplementation is based on an intelligent algorithm which performs a shifting of only one of the control singletons (the singleton associated to the SMALL_ linguistic variable), its value becoming variable, a fact that allows an accurate control and a better performance for the expert control system. The logic of this intelligent algorithm is to initially provide a high controller output, followed by a slowdown of the control signal near to the operating set point. The main advantage of the proposed expert control strategy is its simplicity: a reduced number of linguistic terms, combined with an intelligent tuning of a single parameter, can provide results as accurate as other more complex available solutions involving tuning of several parameters (well described by the technical literature). Also, a simplification of the preliminary off-line tuning procedure is performed by using a reduced set of fuzzy rules. The generality of the proposed expert control strategy allows its use for any other controlled process.     

IMC based Robust PID design: Tuning guidelines and automatic tuning

This communication addresses the problem of tuning a PID controller for step response. The tuning is based upon a First Order Plus Time Delay (FOPTD) model and aims to achieve a step response specification while taking into account robustness considerations. The industrial ISA-PID formulation is chosen. A tuning rule is derived first where the four parameters of the ISA-PID are determined by means of two new parameters: one parameter is related to the desired closed-loop time constant and the other one to the robustness level. On a second step, these two parameters are set to a fixed value in order to get a simple and automatic rule that directly gives the controller parameters in terms of the process model parameters. The proposed automatic tuning rule is compared with other known tunings.     

A numerical optimization approach for tuning fuzzy logiccontrollers

This paper develops a method to tune fuzzy controllers using numerical optimization. The main attribute of this approach is that it allows fuzzy logic controllers to be tuned to achieve global performance requirements. Furthermore, this approach allows design constraints to be implemented during the tuning process. The method tunes the controller by parameterizing the membership functions for error, change-in-error, and control output. The resulting parameters form a design vector which is iteratively changed to minimize an objective function. The minimal objective function results in an optimal performance of the system. A spacecraft mounted science payload line-of-sight pointing control is used to demonstrate results.     

On the automatic tuning and adaptation of PID controllers

A simple approach to the automatic tuning of PID process controllers is proposed. Like the relay-based autotuner, its objective is to attain a design-point on the Nyquist diagram. By injecting sinewaves and employing a phase/frequency estimator, closed-loop adaptive tuning is possible and there is exact convergence to the design-point without the approximations of describing-function theory. The variant discussed here achieves a required phase margin and imposes a carefully chosen constraint on the controller parameters, leading to consistent behaviour for a wide variety of generic test-cases. A real-life demonstration on a non-linear flow rig is provided.     

Adaptive hierarchical tuning of fuzzy controllers

Fuzzy controller design includes both linear and non-linear dynamic analysis. The knowledge base parameters associated within the fuzzy rule base influence the non-linear control dynamics while the linear parameters associated within the fuzzy output signal influence the overall control dynamics. For distinct identification of tuning levels, an equivalent linear controller output and a normalized non-linear controller output are defined. A linear proportional-integral-derivative (PID) controller analogy is used for determining the linear tuning parameters. Non-linear tuning is derived from the locally defined control properties in the non-linear fuzzy output. The non-linearity in the fuzzy output is then represented in a graphical form for achieving the necessary non-linear tuning. Three different tuning strategies are evaluated. The first strategy uses a genetic algorithm to simultaneously tune both linear and non-linear parameters. In the second strategy the non-linear parameters are initially selected on the basis of some desired non-linear control characteristics and the linear tuning is then performed using a trial and error approach. In the third method the linear tuning is initially performed off-line using an existing linear PID law and an adaptive non-linear tuning is then performed online in a hierarchical fashion. The control performance of each design is compared against its corresponding linear PID system. The controllers based on the first two design methods show superior performance when they are implemented on the estimated process system. However, in the presence of process uncertainties and external disturbances these controllers fail to perform any better than linear controllers. In the hierarchical control architecture, the non-linear fuzzy control method adapts to process uncertainties and disturbances to produce superior performance.     

粒子群算法在PID控制器参数整定中的研究与应用

针对自动化控制系统中PID控制器参数整定困难的问题,提出了基于粒子群算法的PID控制器的设计方法,给出了具体的实验架构。采用系统参数鉴定的方式得到直流伺服发电机的传递函数,并利用粒子群算法搜寻PID参数。实验采用MATLAB仿真证明了该方法的可行性和优越性。所得到模拟结果跟遗传算法搜索PID参数的结果做比较,结果显示用粒子群算法调整PID参数所得到的运算时间比用遗传算法的运算时间要短。     

一种IAE指标触发的继电反馈PID参数自校正方法

针对实际工业过程中固定PID参数不能适应系统特征变化的问题,提出了一种在线控制器参数自动校正方法。首先,以内模控制为基础,由系统工作数据估计得到设定值阶跃变化下系统可获得的最优累积绝对误差值(IAE),并以此建立评价当前控制器优劣的性能指标。若性能不满足要求,则触发PID参数校正算法工作,通过引入继电反馈环节使控制回路振荡,获得控制系统临界信息,再根据改进的Z-N规则计算新的PID控制器参数。最后,分别用仿真和实际液位控制系统验证所提方法的有效性。