scholarly journals Speed control of an SPMSM using a tracking differentiator-PID controller scheme with a genetic algorithm

2021 ◽  
Vol 11 (2) ◽  
pp. 1728
Author(s):  
Noor Hameed Hadi ◽  
Ibraheem Kasim Ibraheem
Keyword(s):  
Genetic Algorithm ◽  
Pid Controller ◽  
Permanent Magnet Synchronous Motor ◽  
Absolute Error ◽  
Pi Controller ◽  
Tracking Differentiator ◽  
Control Scheme ◽  
Objective Performance ◽  
The Absolute ◽  
Energy Signal

In this paper, a tracking differentiator-proportional integral and derivative (TD-PID) control scheme is proposed to control the speed of a surface mount permanent magnet synchronous motor (SPMSM). The TD is used to generate the necessary transient profile for both the reference and the output speed, which are compared with each other to produce the error signals that feed into the PID controller. In addition to the TD unit parameters, the PID controller’s parameters are tuned to achieve the optimum new multi-objective performance index, comprised of the integral of the time absolute error (ITAE), the absolute square of the control energy signal (USQR), and the absolute value of the control energy signal (UABS) and utilizing a genetic algorithm (GA). A nonlinear model of the SPMSM is considered in the design and the performance of the proposed TD-PID scheme was validated by comparing its performance with that of a traditional PI controller in a MATLAB environment. Different case studies were tested to show the effectiveness of the proposed scheme, results including peak overshoot, energy consumption, control signal chatter, and 30% improvement in the OPI, with variable reference speeds, load torque, and parameters uncertainties. Illustrate the proposed scheme's success compared with PI controller.

scholarly journals Application of the genetic algorithm for cascade control of a HVAC system

2019 ◽  
Vol 292 ◽  
pp. 01064 ◽  
Author(s):  
Donka Ivanova ◽  
Nikolay Valov ◽  
Martin Deyanov
Keyword(s):  
Genetic Algorithm ◽  
Control Systems ◽  
Pid Controller ◽  
Classical Method ◽  
Pi Controller ◽  
Cascade Control ◽  
Hvac System ◽  
Cascade System ◽  
Outer Loop ◽  
Cascade Control System

In this article the application of genetic algorithm for tuning of HVAC cascade system is proposed. The tuning procedure for a cascade system is very time-consuming and practice shows that additional controller tuning is needed when classical method is used. The main problem in classical method is the interconnection between the parameters of the two controllers. The proposed optimal tuning procedure overcomes the disadvantages. It is based on the following criteria: minimum integral square error, minimum settling time and minimum overshoot. The best process quality is achieved with PI controller in the inner loop and a PID controller in the outer loop of the cascade HVAC system. The proposed method for simultaneous tuning of controller parameters in a cascade control system can be applied in different control systems.

scholarly journals Genetic Algorithm Based PID Controller Tuning Approach for Continuous Stirred Tank Reactor

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
A. Jayachitra ◽  
R. Vinodha
Keyword(s):  
Genetic Algorithm ◽  
Pid Controller ◽  
Absolute Error ◽  
Stirred Tank ◽  
Continuous Stirred Tank Reactor ◽  
Stirred Tank Reactor ◽  
Tank Reactor ◽  
Operating Range ◽  
Continuous Stirred Tank ◽  
Dynamic Nonlinearity

Genetic algorithm (GA) based PID (proportional integral derivative) controller has been proposed for tuning optimized PID parameters in a continuous stirred tank reactor (CSTR) process using a weighted combination of objective functions, namely, integral square error (ISE), integral absolute error (IAE), and integrated time absolute error (ITAE). Optimization of PID controller parameters is the key goal in chemical and biochemical industries. PID controllers have narrowed down the operating range of processes with dynamic nonlinearity. In our proposed work, globally optimized PID parameters tend to operate the CSTR process in its entire operating range to overcome the limitations of the linear PID controller. The simulation study reveals that the GA based PID controller tuned with fixed PID parameters provides satisfactory performance in terms of set point tracking and disturbance rejection.

Design of Gain Scheduled Multivariable Controllers for a Nonlinear Process

2011 ◽  
Vol 403-408 ◽  
pp. 4821-4827 ◽  
Author(s):  
N. Kamala ◽  
T. Thyagarajan ◽  
S. Renganathan
Keyword(s):  
Pid Controller ◽  
Absolute Error ◽  
Nonlinear Process ◽  
Simulation Studies ◽  
Continuous Stirred Tank Reactor ◽  
Control Scheme ◽  
Continuous Stirred Tank ◽  
Dynamic Nonlinearity ◽  
Gain Scheduled ◽  
Operating Points

In this paper, Genetic Algorithm is utilized to optimize the coefficients of a decentralized PID controller for a nonlinear Multi-Input Multi-output process by minimizing the Integral Absolute Error (IAE).The controller is tuned at chosen operating points, which are selected to cover the nonlinear range of the process. The optimal PID controller parameters are gain scheduled using a Fuzzy Gain scheduler. The effectiveness of the proposed control scheme has been demonstrated by conducting simulation studies on a Continuous Stirred Tank Reactor (CSTR) process which exhibits dynamic nonlinearity

Design of an Optimal Integral Backstepping Controller for a Quadcopter

2018 ◽  
Vol 24 (5) ◽  
pp. 46
Author(s):  
Laith Jasim Saud ◽  
Alaq Falah Hasan
Keyword(s):  
Pid Controller ◽  
Tracking Error ◽  
Absolute Error ◽  
Swarm Optimization ◽  
Full Control ◽  
Integral Action ◽  
Control Scheme ◽  
Optimal Values ◽  
Backstepping Controller ◽  
Yaw Angle

In this paper, an Integral Backstepping Controller (IBC) is designed and optimized for full control, of rotational and translational dynamics, of an unmanned Quadcopter (QC). Before designing the controller, a mathematical model for the QC is developed in a form appropriate for the IBC design. Due to the underactuated property of the QC, it is possible to control the QC Cartesian positions (X, Y, and Z) and the yaw angle through ordering the desired values for them. As for the pitch and roll angles, they are generated by the position controllers. Backstepping Controller (BC) is a practical nonlinear control scheme based on Lyapunov design approach, which can, therefore, guarantee the convergence of the position tracking error to zero. To improve controller capability in the steady state against disturbances, an integral action is used with the BC. To determine the optimal values of the IBC parameters, the Particle Swarm Optimization (PSO) is used. In the algorithm, the controller parameters are computed by minimizing a cost function that depends on the Integral Time Absolute Error (ITAE) performance index. Finally, different numerical simulations are provided in order to illustrate the performances of the designed controller. And for comparison purposes, a PID controller is designed and optimized using the PSO to control the quadcopter. The obtainediresults indicated a superiority in performance for the IBC over the PID controller based on some points among which are: a 13.3% and 30.5% lesser settling times for X and Y consequently, the ability to perform critical maneuvers that the quadcopter failed to do using the PID controller, and the capability of fast following up and conforming the changes of pitch (

scholarly journals Design of an Intelligent NPID Controller Based on Genetic Algorithm for Disturbance Rejection in Single Integrating Process with Time Delay

2020 ◽  
Vol 9 (1) ◽  
pp. 25
Author(s):  
GunBaek So
Keyword(s):  
Genetic Algorithm ◽  
Time Delay ◽  
Pid Controller ◽  
Nonlinear Function ◽  
Absolute Error ◽  
Open Loop ◽  
Real Coded Genetic Algorithm ◽  
On Line ◽  
Response Performance ◽  
Integrating Process

The integrating process with time delay (IPTD) is a fundamentally unstable open-loop system due to poles at the origin of the transfer function, and designing controllers with satisfactory control performance is very difficult because of the associated time delay, which is a nonlinear element. Therefore, this study focuses on the design of an intelligent proportional-integral-derivative (PID) controller to improve the regulatory response performance to disturbance in an IPTD, and addresses problems related to optimally tuning each parameter of the controller with a real coded genetic algorithm (RCGA). Each gain of the nonlinear PID (NPID) controller consists of a product of the gains of the linear PID controller and a simple nonlinear function. Each of these nonlinear functions changes the gains in the controller to on line by nonlinearly scaling the error signal. A lead-lag compensator or first-order filter is also added to the controller to mitigate noise, which is a disadvantage of ideal derivative action. The parameters in the controller are optimally tuned by minimizing the integral of time-weighted absolute error (ITAE) using a RCGA. The proposed method is compared with three other methods through simulation to verify its effectiveness.

scholarly journals Design of Neutrosophic Self-Tuning PID Controller for AC Permanent Magnet Synchronous Motor Based on Neutrosophic Theory

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Zhongliang Fu ◽  
Chunping Liu ◽  
Shengyi Ruan ◽  
Kun Chen
Keyword(s):  
Genetic Algorithm ◽  
Permanent Magnet ◽  
Pid Controller ◽  
Permanent Magnet Synchronous Motor ◽  
System Response ◽  
Permanent Magnet Synchronous Motors ◽  
Response Characteristics ◽  
Cosine Measure ◽  
Self Tuning ◽  
Different Response

In practical control applications, AC permanent magnet synchronous motors need to work in different response characteristics. In order to meet this demand, a controller which can independently realize the different response characteristics of the motor is designed based on neutrosophic theory and genetic algorithm. According to different response characteristics, neutrosophic membership functions are constructed. Then, combined with the cosine measure theorem and genetic algorithm, the neutrosophic self-tuning PID controller is designed. It can adjust the parameters of the controller according to response requirements. Finally, three kinds of controllers with typical system response characteristics are designed by using Simulink. The effectiveness of the designed controller is verified by simulation results.

scholarly journals Optimization of Proportional Integral Derivative Parameters of Brushless Direct Current Motor Using Genetic Algorithm

2020 ◽  
pp. 24-32
Author(s):  
Isaiah Adebayo ◽  
David Aborisade ◽  
Olugbemi Adetayo
Keyword(s):  
Genetic Algorithm ◽  
Direct Current ◽  
Pid Controller ◽  
Absolute Error ◽  
Dc Motor ◽  
Brushless Dc Motor ◽  
Bldc Motor ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Brushless Dc

Optimal performance of the Brushless Direct Current (BLDC) motor is to be realized using an efficient Proportional Integral Derivative (PID) controller. However, conventional tuning technique fails to perform satisfactorily under parameter variations, nonlinear conditions and time delay. Also using conventional technique to tune the parameters gain of the PID controller is a difficult task. To overcome these difficulties, modern heuristic optimization technique are required to optimally tune the Proportional, Integral, Derivative of the controller for optimal speed control of three phase BLDC motor. Thus, genetic algorithm (GA) based PID controller was used to achieve a high dynamic control performance. The Brushless DC Motor mathematical equation which describes the voltage and corresponding rotational angular speed and torque of the brushless DC motor was employed using electrical DC Machines theorem. The Genetic algorithm was further analyzed by adopting the three common performance indices i.e. Integral Time Absolute Error (ITAE), Integral Square Error (ISE) and Integral Absolute Error (IAE) in order to capture and compare the most suitable BLDC Motor speed and torque control characteristics. All simulations were done using MATLAB (R2018a). The simulation result showed that the system with GA-PID controller had the better system response when compared with the existing technique of ZN-PID controller.

Design and Application of Self-Tuning PI Controller

2010 ◽  
Vol 43 ◽  
pp. 160-164 ◽  
Author(s):  
Xiao Hong Kong ◽  
Bao Jian Zhang ◽  
Xin Hua Mao ◽  
Yan Feng Chen ◽  
Chang Yuan Song
Keyword(s):  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Permanent Magnet Synchronous Motor ◽  
Pi Controller ◽  
Compound Control ◽  
Self Tuning ◽  
Fuzzy Pi Controller ◽  
Overall Performance ◽  
Application Fields

The permanent magnet synchronous motor (PMSM) is popularly used in many application fields for such advantages as having the speed-torque characteristics similar to that of a DC motor. Nevertheless, the overall performance of the PMSM is largely dependent on that of the control system. The classical PID controller, which has acquired wide applications in many fields, is only suitable for the design of the linear system and cannot meet the requirements of the nonlinear system like the PMSM. In this paper, a compound control system combining the classical PID control and the fuzzy control is presented to meet the requirements of control system. Simulation results show that the fuzzy PI controller has better performance than that of the classical PI controller.

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