scholarly journals PSO-Based PID Controller Design for a Class of Stable and Unstable Systems

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
K. Latha ◽  
V. Rajinikanth ◽  
P. M. Surekha
Keyword(s):  
Comparative Study ◽  
Real Time ◽  
Pid Controller ◽  
Controller Design ◽  
Pso Algorithm ◽  
Search Space ◽  
Process Models ◽  
Stabilizing Controller ◽  
Fixed Weight ◽  
Unstable Process

Nonlinear processes are very common in process industries, and designing a stabilizing controller is always preferred to maximize the production rate. In this paper, tuning of PID controller for a class of time delayed stable and unstable process models using Particle Swarm Optimization (PSO) algorithm is discussed. The dimension of the search space is only three (, , and ); hence, a fixed weight is assigned for the inertia parameter. A comparative study is presented between various inertia weights such as 0.5, 0.75, and 1. From the result, it is evident that the proposed method helps to attain better controller settings with reduced iteration number. The efficacy of the proposed scheme has been validated through a comparative study with classical controller tuning methods and heuristic methods such as Genetic Algorithm (GA) and Ant Colony Optimization (ACO). Finally, a real-time implementation of the proposed method is carried on a nonlinear spherical tank system. From the simulation and real-time results, it is evident that the PSO algorithm performs well on the stable and unstable process models considered in this work. The PSO tuned controller offers enhanced process characteristics such as better time domain specifications, smooth reference tracking, supply disturbance rejection, and error minimization.

scholarly journals Controller Parameter Optimization for Nonlinear Systems Using Enhanced Bacteria Foraging Algorithm

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
V. Rajinikanth ◽  
K. Latha
Keyword(s):  
Real Time ◽  
Pid Controller ◽  
Nonlinear Process ◽  
Process Models ◽  
Proportional Integral Derivative ◽  
Controller Tuning ◽  
Spherical Tank ◽  
Pid Controller Tuning ◽  
Tank System ◽  
Tuning Methods

An enhanced bacteria foraging optimization (EBFO) algorithm-based Proportional + integral + derivative (PID) controller tuning is proposed for a class of nonlinear process models. The EBFO algorithm is a modified form of standard BFO algorithm. A multiobjective performance index is considered to guide the EBFO algorithm for discovering the best possible value of controller parameters. The efficiency of the proposed scheme has been validated through a comparative study with classical BFO, adaptive BFO, PSO, and GA based controller tuning methods proposed in the literature. The proposed algorithm is tested in real time on a nonlinear spherical tank system. The real-time results show that, EBFO tuned PID controller gives a smooth response for setpoint tracking performance.

Fuzzy Controller Design for Multi-Legged Robot

2011 ◽  
Vol 383-390 ◽  
pp. 7345-7350
Author(s):  
Zhi Yong Tang ◽  
Hai Xiao Zhong ◽  
Zhong Cai Pei ◽  
Yan Hao Bu
Keyword(s):  
Control System ◽  
Real Time ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Controller Design ◽  
High Accuracy ◽  
Dynamics Analysis ◽  
Legged Robot ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller

In this paper, we propose a mechanical structure for multi-legged robot. Referring the request of control system, we also made a proper choice on driving means. After dynamics analysis on a single leg of the robot, we make a simulation using ADAMS and get how the torque of each joint is changing when the robot is walking. The model of DC motor is established for the control system. Fuzzy PID controller was used to get real-time response and high accuracy of control system.

scholarly journals Modelling and Controller Design for Non- Linear Two Tank Interacting System

2020 ◽  
Vol 9 (6) ◽  
pp. 82-85
Keyword(s):  
Fuzzy Logic ◽  
Comparative Study ◽  
Mathematical Modelling ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Controller Design ◽  
Linear Process ◽  
Matlab Simulink ◽  
Non Linear ◽  
And Control

This paper explains the mathematical modelling and controller design of Two Tank Interacting System (TTIS) for a non-linear process. To design the non-linear process using Matlab Simulink and control the process using conventional PID controller and Fuzzy Logic Controller (FLC). A comparative study was conducted extensively made to examine which controller suits well for the non-linear process through the response observed.

scholarly journals Optimized designing of PID controller for variable speed wind turbine systems using PSO algorithm

2015 ◽  
Vol 37 ◽  
pp. 397
Author(s):  
Somayeh Abdolzadeh ◽  
Seyed Mohammad Ali Mohammadi
Keyword(s):  
Wind Turbine ◽  
Pid Controller ◽  
High Performance ◽  
Controller Design ◽  
Pso Algorithm ◽  
Variable Speed ◽  
Stable Convergence ◽  
Wind Turbine System ◽  
Variable Speed Wind Turbine ◽  
Wide Range

The PID controller design is a very popular method for controlling industrial processes and due to its simple structure and effective operation; it is used in a wide range of industries. In this paper, a method is provided for setting up the PID controller and Particle swarm optimization (PSO) algorithm is used to design a variable speed wind turbine system. The provided method has advantages such as easy implementation, stable convergence characteristics and high performance in computing. Finally the results are displayed.

scholarly journals PID Controller Design for Cruise Control System using Particle Swarm Optimization

2017 ◽  
Vol 43 (2) ◽  
pp. 30-35
Author(s):  
Ahmed Abdulnabi
Keyword(s):  
Particle Swarm Optimization ◽  
Pid Controller ◽  
Controller Design ◽  
Robustness Analysis ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Peak Time ◽  
Cruise Control ◽  
Swarm Optimization ◽  
Best Response

This paper presents a design of a Proportional-Integral-Derivative (PID) controller for automobile cruise controlsystem. The parameters of the PID controller, which are the proportional ( ), derivative ( ) , and integrator ( ), have beenselected using Particle Swarm Optimization (PSO) algorithm. In this study, the overall system performance has beencompared with other predesigned controllers (conventional PID, Fuzzy logic PID, state space, and Genetic algorithm basedPID controller). The simulation result illustrates that PSO based PID controller gives the best response in terms of settlingtime, rise time, peak time, and maximum overshot. The robustness analysis shows that the system is robust despite thedeviations in some of the system parameters.

Designing of IMC-PID Controller for Higher-order Process Based on Model Reduction Method and Fractional Coefficient Filter with Real-time Verification

2019 ◽  
Vol 15 (3) ◽  
Author(s):  
Ujjwal Manikya Nath ◽  
Chanchal Dey ◽  
Rajani K. Mudi
Keyword(s):  
Model Reduction ◽  
Real Time ◽  
Pid Controller ◽  
Performance Enhancement ◽  
Higher Order ◽  
Process Models ◽  
Reduction Scheme ◽  
Level Control ◽  
First Order ◽  
Improved Model

AbstractAn improved model reduction scheme is proposed here for higher-order processes and subsequently an enhanced IMC-PID controller is designed based on the obtained reduced model. In the proposed scheme, higher-order processes are estimated as first-order-plus-dead-time (FOPDT) model. Designed IMC controller includes a filter having two separate time constants with fractional order coefficients. Efficacy of the proposed model reduction scheme is verified in terms of closed loop performance evaluation for higher-order minimum and non-minimum phase process models in comparison with improved SIMC (iSIMC) controller (Grimholt. Optimal PI and PID control of first-order plus delay processes and evaluation of the original and improved SIMC rules. J Process Control. 2018;70:36–46). Overall performance enhancement for the proposed method is demonstrated through simulation study as well as real-time experimentation on a level control loop.

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