VELOCITY CONTROL OF A UNICYCLE TYPE OF MOBILE ROBOT USING OPTIMAL PID CONTROLLER

2016 ◽  
Vol 78 (7-4) ◽  
Author(s):  
Norhayati A. Majid ◽  
Z. Mohamed ◽  
Mohd Ariffanan Mohd Basri
Keyword(s):  
Mobile Robot ◽  
Pid Controller ◽  
Fitness Function ◽  
Absolute Error ◽  
Pid Controllers ◽  
Reference Trajectory ◽  
Velocity Control ◽  
Drive Systems ◽  
The Right ◽  
Simplified Modeling

A unicycle model of control a mobile robot is a simplified modeling approach modified from the differential drive mobile robots. Instead of controlling the right speed,  and the left speed,  of the drive systems, the unicycle model is using  and  as the controller parameters. Tracking is much easier in this model. In this paper, the dynamic of the robot parameter is controlled using two blocks of Proportional-Integral-Derivative (PID) controllers. The gains of the PID are firstly determined using particle swarm optimization (PSO) in offline mode. After the optimal gain is determined, the tracking of the robot’s trajectory is performed online with optimal PID controller. The achieved results of the proposed scheme are compared with those of dynamic model optimized with genetic algorithm (GA) and manually tuned PID controller gains. In the algorithm, the control parameters are computed by minimizing the fitness function defined by using the integral absolute error (IAE) performance index. The simulation results obtained reveal advantages of the proposed PSO-PID dynamic controller for trajectory tracking of a unicycle type of mobile robot. A MATLAB-Simulink program is used to simulate the designed system and the results are graphically plotted. In addition, numerical simulations using 8-shape as a reference trajectory with several numbers of iterations are reported to show the validity of the proposed scheme.

PSO and GA tuned conventional and fractional order PID controllers for quadrotor control

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hasan Saribas ◽  
Sinem Kahvecioglu
Keyword(s):  
Fractional Order ◽  
Pid Controller ◽  
Controller Design ◽  
Optimization Problems ◽  
Parameter Tuning ◽  
Absolute Error ◽  
Cost Functions ◽  
Pid Controllers ◽  
Content Type ◽  
Quadrotor Control

Purpose This study aims to compare the performance of the conventional and fractional order proportional-integral-derivative (PID and FOPID) controllers tuned with a particle swarm optimization (PSO) and genetic algorithm (GA) for quadrotor control. Design/methodology/approach In this study, the gains of the controllers were tuned using PSO and GA, which are included in the heuristic optimization methods. The tuning processes of the controller’s gains were formulated as optimization problems. While generating the objective functions (cost functions), four different decision criteria were considered separately: integrated summation error (ISE), integrated absolute error, integrated time absolute error and integrated time summation error (ITSE). Findings According to the simulation results and comparison tables that were created, FOPID controllers tuned with PSO performed better performances than PID controllers. In addition, the ITSE criterion returned better results in control of all axes except for altitude control when compared to the other cost functions. In the control of altitude with the PID controller, the ISE criterion showed better performance. Originality/value While a conventional PID controller has three parameters (Kp, Ki, Kd) that need to be tuned, FOPID controllers have two additional parameters (µ). The inclusion of these two extra parameters means more flexibility in the controller design but much more complexity for parameter tuning. This study reveals the potential and effectiveness of PSO and GA in tuning the controller despite the increased number of parameters and complexity.

scholarly journals Speed Proportional Integrative Derivative Controller: Optimization Functions in Metaheuristic Algorithms

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Luis Fernando de Mingo López ◽  
Francisco Serradilla García ◽  
José Eugenio Naranjo Hernández ◽  
Nuria Gómez Blas
Keyword(s):  
Pid Controller ◽  
Fitness Function ◽  
Optimization Algorithms ◽  
Metaheuristic Algorithms ◽  
Mathematical Background ◽  
Speed Controller ◽  
Search Optimization ◽  
Metaheuristic Search ◽  
Self Driving Cars ◽  
The Right

Recent advancements in computer science include some optimization models that have been developed and used in real applications. Some metaheuristic search/optimization algorithms have been tested to obtain optimal solutions to speed controller applications in self-driving cars. Some metaheuristic algorithms are based on social behaviour, resulting in several search models, functions, and parameters, and thus algorithm-specific strengths and weaknesses. The present paper proposes a fitness function on the basis of the mathematical description of proportional integrative derivate controllers showing that mean square error is not always the best measure when looking for a solution to the problem. The fitness developed in this paper contains features and equations from the mathematical background of proportional integrative derivative controllers to calculate the best performance of the system. Such results are applied to quantitatively evaluate the performance of twenty-one optimization algorithms. Furthermore, improved versions of the fitness function are considered, in order to investigate which aspects are enhanced by applying the optimization algorithms. Results show that the right fitness function is a key point to get a good performance, regardless of the chosen algorithm. The aim of this paper is to present a novel objective function to carry out optimizations of the gains of a PID controller, using several computational intelligence techniques to perform the optimizations. The result of these optimizations will demonstrate the improved efficiency of the selected control schema.

scholarly journals Optimization of the PID coefficients for the line-follower mobile robot controller employing genetic algorithm

Informatics ◽  
2021 ◽  
Vol 18 (4) ◽  
pp. 53-68
Author(s):  
T. Yu. Kim ◽  
R. A. Prakapovich
Keyword(s):  
Genetic Algorithm ◽  
Control System ◽  
Mobile Robot ◽  
Software Package ◽  
Pid Controller ◽  
Fitness Function ◽  
Color Contrast ◽  
Robot Controller ◽  
Mobile Robot Control ◽  
Evolutionary Tuning

O b j e c t i v e s. To develop a control system for the movement of a mobile robot along a color-contrast line, as well as to find the values of the coefficients of a proportional-integral-differentiating (PID) controller that allows the robot to move along the line at a given speed.M e t ho d s. To adjust the values of the coefficients of the PID controller, methods of enumeration, automatic tuning and a genetic algorithm are used.Re s u l t s. A software package for tuning the PID controller of the educational mobile robot RoboCake, designed to move along a closed color-contrast line at a given speed, has been developed. The software package consists of a simulation model of the specified robot in the Simulink environment, several virtual traces-polygons and a specialized solver based on the developed genetic algorithm. With the help of the proposed fitness function, a mobile robot control system that satisfies the stated conditions is implemented. Based on the conducted model experiments, the desired values of the parameters of the PID controller are obtained.Co n c l u s i o n. A comparison of the effectiveness of various methods of tuning the PID controller is carried out. The developed software package is designed to solve the practical problem of moving a mobile robot along a color-contrast line at a speed of 1 m/s. The results obtained can be used to study methods of evolutionary tuning of stabilization systems for transport robots, ensuring their movement without overshoot.

scholarly journals Design and Implementation of PID, GA and Fuzzy logic Controllers for an Electrical Drive with Various Noise Disturbances

2020 ◽  
Vol 9 (3) ◽  
pp. 449-453
Keyword(s):  
Steady State ◽  
Pid Controller ◽  
Fitness Function ◽  
External Noise ◽  
Pid Controllers ◽  
Matlab Simulation ◽  
State Behavior ◽  
Intelligent Technique ◽  
Noise Disturbances ◽  
Transient And Steady State

It is a great challenge for human being to keep up the constant speed in drive when external Noise disturbances occur due to fluctuations of power supply. In order to avoid these issues, PID controllers are intended using predictable method such as Ziegler Nichols method. But finest level is not obtained in transient and steady state. During the MATLAB Simulation, the error is present transient and steady state behavior in conventional PID controllers. Hence it is necessary to design a PID controller with Novel intelligent technique for speed control of drive like fuzzy and Genetic Algorithm. It considers error as fitness function which is to be minimized using various GA operators such as mutation etc. The Drive will be operated with different external noises like sinusoidal noise, Saw tooth noise and Ramp noise and comparison between PID, GA and Fuzzy PID will be presented and their performances are studied.

scholarly journals Kalman Filter to Improve Performance of PID Control Systems on DC Motors

2021 ◽  
Vol 5 (3) ◽  
pp. 96
Author(s):  
Seta Yuliawan ◽  
Oyas Wahyunggoro ◽  
Nurman Setiawan
Keyword(s):  
Kalman Filter ◽  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Absolute Error ◽  
Pid Controllers ◽  
Electronic Components ◽  
Improve Performance ◽  
Noise Sources ◽  
Dc Motors

A proportional–integral–derivative (PID) controller is a type of control system that is most widely applied in industrial world. Various tuning models have been developed to obtain optimal performance in PID control. However, the methods are designed under ideal circumstances. This means that the control system which has been built will not work optimally when noise exists. Noise can come from electrical vibrations, inference of electronic components, or other noise sources. Thus, it is necessary to design PID control system that can work optimally without being disturbed by noise. In this research, Kalman filter was used to improve the performance of PID controllers. The application of Kalman filter was used to reduce the noise of the input signal so that it could generate output signal which is in accordance with the expected output. Simulation result showed that the PID performance with Kalman filter was more optimal than the ordinary one to minimize the existing noise. The resulting speed of DC motor with Kalman filter had a lower overshoot than PID control without Kalman filter. This method resulted lower integral of absolute error (IAE) than ordinary PID controls. The IAE value for the PID controller with the Kalman filter was 25.4, the PID controller with the observer was 31.0, while the IAE value in the ordinary controller was only 60.9.

scholarly journals Optimum PID controller for airplane wing tires based on gravitational search algorithm

2021 ◽  
Vol 10 (4) ◽  
pp. 1905-1913
Author(s):  
Ammar Hussein Mutlag ◽  
Omar Nameer Mohammed Salim ◽  
Siraj Qays Mahdi
Keyword(s):  
Pid Controller ◽  
Transfer Functions ◽  
Search Algorithm ◽  
Fitness Function ◽  
Gravitational Search Algorithm ◽  
Harmony Search ◽  
Absolute Error ◽  
Airplane Wing ◽  
Gravitational Search ◽  
Opening And Closing

In this paper, the gravitational search algorithm (GSA) is proposed as a method for controlling the opening and closing of airplane wing tires. The GSA is used to find the optimum proportional-integral-derivative (PID) controller, which controls the wing tires during take-off and landing. In addition, the GSA is suggested as an approach for overcoming the absence of the transfer function, which is usually required to design the optimum PID. The use of the GSA is expected to improve the system. Two of the most popular optimisation algorithms-the harmony search algorithm (HSA) and the particle swarm optimisation (PSO)-were used for the sake of comparison. Moreover, the GSA-, HSA- and PSO-based optimum PID controllers were compared with one of the most important PID tuning methods, the Ziegler-Nichols (ZN) method. In this study, the integral time absolute error (ITAE) was used as a fitness function. First, four transfer functions for different applications were used to compare the performance of the GSA-based PID (PID-GSA), HSA-based PID (PID-HSA), PSO-based PID (PID-PSO) and Ziegler-Nichols-based PID (PID-ZN). Next, the GSA was used to design the optimum PID controller for the opening and closing systems of the airplane wing tires. The results reveal that the GSA provides better outcomes in terms of ITAE when compared with the other adopted algorithms. Furthermore, the GSA demonstrates a fast and robust response to reference variation.

scholarly journals IMPROVING THE WALL-FOLLOWING ROBOT PERFORMANCE USING PID-PSO CONTROLLER

2019 ◽  
Vol 81 (3) ◽  
Author(s):  
Andi Adriansyah ◽  
Heru Suwoyo ◽  
Yingzhong Tian ◽  
Chenwei Deng
Keyword(s):  
Mobile Robot ◽  
Pid Controller ◽  
Optimization Method ◽  
Pid Controllers ◽  
Robust Controller ◽  
Convergence Process ◽  
Robot Behavior ◽  
Robot Performance ◽  
A New Technique ◽  
Wall Following

A wall-following robot is one of the main issues in autonomous mobile robot behavior. However, a wall-following robot needs a robust controller to perform specific tasks accurately. This paper presents an optimization method termed Particle Swarm Optimization (PSO). It was used to automatically produce necessary parameters of the PID controller; henceforth, it was termed as PID-PSO Controller. A new technique of PSO was introduced to enhance the ability of a PID controller to maintain the linear velocity of a mobile robot. The PID-PSO controller was applied to a wheeled wall-following robot. A number of experiments were carried out, and the simulated results were adopted and performed in real applications. Based on several experimental results it can be obtained that the accumulative errors the robot use PID controllers tuned manually, tuned by GA and tuned by PSO are 0.7866, 0.78543 and 0.74619, respectively. Also, the convergence process of PID parameters using the proposed PSO is faster and more optimal than GA. Therefore, it can be said that the proposed system can improve the performance of wall-following robots by decreasing the accumulative error of up to 9%. 

scholarly journals PID Tuning Method Using Chaotic Safe Experimentation Dynamics Algorithm for Elastic Joint Manipulator

2021 ◽  
Vol 54 (5) ◽  
pp. 693-698
Author(s):  
Mohd Ikhmil Fadzrizan Mohd Hanif ◽  
Mohd Ashraf Ahmad ◽  
Julakha Jahan Jui
Keyword(s):  
Pid Controller ◽  
Vibration Suppression ◽  
Fitness Function ◽  
Pid Controllers ◽  
Elastic Joint ◽  
Tuning Method ◽  
Pid Tuning ◽  
Self Tuning ◽  
Angle Tracking ◽  
Control Challenge

This paper proposed the chaotic safe experimentation dynamics algorithm (CSEDA) to regulate angular tracking and vibration of the self-tuning PID controller for elastic joint manipulators. CSEDA was a modified version of the safe experimentation dynamics algorithm (SEDA) that used a chaos function in the updated equation. The chaos function increased the exploration capability, thus improving the convergence accuracy. In this study, two self-tuning PID controllers were used to regulate the rotating angle tracking and vibration for elastic joint manipulators in this control challenge. The suggested self-tuning PID controller's performance was evaluated in angular motion trajectory tracking, vibration suppression, and the pre-determined control fitness function. A self-tuned PID controller based on CSEDA could achieve superior control accuracy than a traditional SEDA and its variants.

scholarly journals Position Control of a Mobile Robot through PID Controller

2019 ◽  
Vol 71 (1) ◽  
pp. 14-20
Author(s):  
Alexandru Bârsan
Keyword(s):  
Mobile Robot ◽  
Pid Controller ◽  
Position Control ◽  
Pid Controllers ◽  
Engineering Faculty ◽  
Entertainment Robot ◽  
Differential Steering

Abstract In this paper, the implementation and tuning steps of the PID controllers were proposed for the position control of a mobile robot with differential steering. The purpose of this robot was the participation in a European amateur robotics contest, the mobile robot being developed in the Engineering Faculty of Sibiu, Department of Industrial Machines and Equipment. After a brief introduction of the mobile entertainment robot, followed by description of the robot’s different components and traction principles, several principles of tuning the PID controller for the mobile robot are presented. The paper ends with some general conclusions based upon the results obtained from studying the research and considering all the ideas that were introduced.

scholarly journals SIMULATION AND PERFORMANCE OF LIQUID LEVEL CONTROLLERS FOR LINEAR TANK

2020 ◽  
Vol 82 (3) ◽  
Author(s):  
Qahtan A. Mahmood ◽  
Amer T. Nawaf ◽  
Shaho A. Mohamedali
Keyword(s):  
Pid Controller ◽  
Absolute Error ◽  
Liquid Level ◽  
Pid Controllers ◽  
Water Tank ◽  
Level Control ◽  
Tuning Method ◽  
Squared Error ◽  
And Performance ◽  
Tuning Methods

Level control of liquid in a tank or any similar container is widely used in applications such as chemical and oil industrial processes. Control the level at desired value is very important. This paper studies the performance of P, PI, and PID controllers in controlling the level of a liquid. Mass balance is used to find mathematical model of water tank level. Ziegler-Nichol (Z-N) and Cohen-Coon (C-C) tuning methods are used to evaluate parameters of the controllers. The error indices such as Integral Absolute Error (IAE) and Integral Squared Error (ISE) are used to compare between performances of the controllers. MATLAB is used to test the control system performance and compare the results with real values. Both simulation and experimental results show that liquid level system can be controlled effectively by using Z-N tuning method. The result shows that the PI controller gives better performance in comparison with P and PID controller.

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