Despite the popularity, the tuning aspect of proportional–integral-derivative (PID) controllers is a challenge for researchers and plant operators. Various controllers tuning methodologies have been proposed in the literature such as auto-tuning, self-tuning, pattern recognition, artificial intelligence, and optimization methods. Chaotic optimization algorithms as an emergent method of global optimization have attracted much attention in engineering applications. Chaotic optimization algorithms, which have the features of easy implementation, short execution time and robust mechanisms of escaping from local optimum, is a promising tool for engineering applications. In this paper, a tuning method for determining the parameters of PID control for an automatic regulator voltage (AVR) system using a chaotic optimization approach based on Lozi map is proposed. Since chaotic mapping enjoys certainty, ergodicity and the stochastic property, the proposed chaotic optimization introduces chaos mapping using Lozi map chaotic sequences which increases its convergence rate and resulting precision. Simulation results are promising and show the effectiveness of the proposed approach. Numerical simulations based on proposed PID control of an AVR system for nominal system parameters and step reference voltage input demonstrate the good performance of chaotic optimization.

Tuning of PID controller for an automatic regulator voltage system using chaotic optimization approach

The ability of PI and PID controllers to compensate many practical processes has led to their wide acceptance in industrial applications. The requirement to choose two or three controller parameters is most easily done using tuning rules. Starting with a general discussion of industrial practice, the paper provides a survey of additional tuning rules for continuous-time PI and PID control of time-delayed single-input, single-output (SISO) processes, to those explored in a recent book by the author

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PI and PID controller tuning rules: an overview and personal perspective

Optimization algorithms inspired by the ants' foraging behavior have been initially used for solving combinatorial optimization problems Since the emergence of ant algorithms as an optimization tool, some attempts were also made to use them for tackling continuous optimization problems In recent years, the investigation of synchronization and control problem for discrete chaotic systems has attracted much attention, and many possible applications The optimization of a proportional-integral-derivative (PID) controller based on a modified continuous approach of ant colony optimization combined with a differential evolution method (MACO) for synchronization of two identical discrete chaotic systems subject the different initial conditions is presented in this paper Numerical simulations based on optimized PID control of a nonlinear chaotic model demonstrate the effectiveness and efficiency of MACO approach Simulation results of the MACO to determine the PID parameters are compared with other metaheuristics including a classical ant colony optimization approach, genetic algorithm and evolution strategy The proposed approach of PID tuning based on MACO can be generalized to other chaotic systems

A modified ant colony optimization algorithm based on differential evolution for chaotic synchronization

A neutral system approach to H∞ PD/PI controller design of processes with uncertain input delay

Stability is very necessary in control system and it becomes more difficult to achieve for a nonlinear system which inverted pendulum is an example. Most of the controllers available suffer from problems such as difficult in tuning process, sluggishness in response time, quick and global convergence etc. This paper considered Proportional-Integra-Derivative optimized with Genetic Algorithm (GA-PID) Controller on Inverted pendulum for the control of the angle position. Conventional PID controller was used to validate the proposed controller. A MATLAB script for genetic algorithm was written with the aim of obtaining optimum PID parameters that would keep the pendulum angle at equilibrium (i.e. returns the pendulum to a desire point as quick as possible) by minimizing an objective function (Integral time absolute error ITAE). On the other hand, a convention PID controller was designed using MATLAB/Simulink environment; the PID's gains were manually tuned until an optimum response is achieved. The results obtained in both schemes shows that GA-PID showed superiority in all the performance indices used in evaluating the two controller schemes and therefore can serves as a valuable controller for the system.

GA-PID controller for position control of inverted pendulum

RaPID (Robust Advanced PID Control) is a new and original engineering tool for the design and implementation of optimal PID controllers. It integrates data acquisition, system identification and optimal PID control design. Special care has been taken in emphasizing engineering intuition and requirements as opposed to the mathematical details. The result is an extremely user-friendly design tool which allows for an easy model-based optimization of any PID controller.

Peter Van Overshee

Papers

RaPID: The end of Heuristic PID Tuning

RaPID : The end of heuristic pid tuning