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Article
Publication date: 2 April 2019

Tayfun Abut and Servet Soyguder

This paper aims to keep the pendulum on the linear moving car vertically balanced and to bring the car to the equilibrium position with the designed controllers.

1288

Abstract

Purpose

This paper aims to keep the pendulum on the linear moving car vertically balanced and to bring the car to the equilibrium position with the designed controllers.

Design/methodology/approach

As inverted pendulum systems are structurally unstable and nonlinear dynamic systems, they are important mechanisms used in engineering and technological developments to apply control techniques on these systems and to develop control algorithms, thus ensuring that the controllers designed for real-time balancing of these systems have certain performance criteria and the selection of each controller method according to performance criteria in the presence of destructive effects is very helpful in getting information about applying the methods to other systems.

Findings

As a result, the designed controllers are implemented on a real-time and real system, and the performance results of the system are obtained graphically, compared and analyzed.

Originality/value

In this study, motion equations of a linear inverted pendulum system are obtained, and classical and artificial intelligence adaptive control algorithms are designed and implemented for real-time control. Classic proportional-integral-derivative (PID) controller, fuzzy logic controller and PID-type Fuzzy adaptive controller methods are used to control the system. Self-tuning PID-type fuzzy adaptive controller was used first in the literature search and success results have been obtained. In this regard, the authors have the idea that this work is an innovative aspect of real-time with self-tuning PID-type fuzzy adaptive controller.

Details

Industrial Robot: the international journal of robotics research and application, vol. 46 no. 1
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 18 October 2021

Zafer Bingul and Oguzhan Karahan

The purpose of this paper is to address a fractional order fuzzy PID (FOFPID) control approach for solving the problem of enhancing high precision tracking performance and…

Abstract

Purpose

The purpose of this paper is to address a fractional order fuzzy PID (FOFPID) control approach for solving the problem of enhancing high precision tracking performance and robustness against to different reference trajectories of a 6-DOF Stewart Platform (SP) in joint space.

Design/methodology/approach

For the optimal design of the proposed control approach, tuning of the controller parameters including membership functions and input-output scaling factors along with the fractional order rate of error and fractional order integral of control signal is tuned with off-line by using particle swarm optimization (PSO) algorithm. For achieving this off-line optimization in the simulation environment, very accurate dynamic model of SP which has more complicated dynamical characteristics is required. Therefore, the coupling dynamic model of multi-rigid-body system is developed by Lagrange-Euler approach. For completeness, the mathematical model of the actuators is established and integrated with the dynamic model of SP mechanical system to state electromechanical coupling dynamic model. To study the validness of the proposed FOFPID controller, using this accurate dynamic model of the SP, other published control approaches such as the PID control, FOPID control and fuzzy PID control are also optimized with PSO in simulation environment. To compare trajectory tracking performance and effectiveness of the tuned controllers, the real time validation trajectory tracking experiments are conducted using the experimental setup of the SP by applying the optimum parameters of the controllers. The credibility of the results obtained with the controllers tuned in simulation environment is examined using statistical analysis.

Findings

The experimental results clearly demonstrate that the proposed optimal FOFPID controller can improve the control performance and reduce reference trajectory tracking errors of the SP. Also, the proposed PSO optimized FOFPID control strategy outperforms other control schemes in terms of the different difficulty levels of the given trajectories.

Originality/value

To the best of the authors’ knowledge, such a motion controller incorporating the fractional order approach to the fuzzy is first time applied in trajectory tracking control of SP.

Details

Industrial Robot: the international journal of robotics research and application, vol. 49 no. 4
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 29 March 2011

Chun‐Fei Hsu, Chien‐Jung Chiu and Jang‐Zern Tsai

The proportional‐integral‐derivative (PID) controller has been a practical application in industry due to its simple architecture, being easily designed and its parameter tuning…

1001

Abstract

Purpose

The proportional‐integral‐derivative (PID) controller has been a practical application in industry due to its simple architecture, being easily designed and its parameter tuning without complicated computation. However, the traditional PID controller usually needs some manual retuning before being used for practical application in industry. The purpose of this paper is to propose an auto‐tuning PID controller (ATPIDC) which can automatically tune the controller parameters based on the gradient descent method and the Lyapunov stability theorem. Finally, a field‐programmable gate array (FPGA) chip is adopted to implement the proposed ATPIDC scheme for possible low‐cost and high‐performance industrial applications, and it is applied to a DC servomotor to show its effectiveness.

Design/methodology/approach

To ensure the stability of the intelligent control system, a compensator usually should be designed. The most frequently used compensator is designed as a sliding‐mode control, which results in substantial chattering in the control effort. To tackle this problem, the proposed ATPIDC system is composed of a PID controller and a fuzzy compensator. The PID controller can automatically tune the gain factors of the controller gains based on the gradient descent method, and the fuzzy compensator is utilized to eliminate approximation error based on the Lyapunov stability theorem. The proposed fuzzy compensator not only can remove the chattering phenomena of conventional sliding‐mode control completely, but also can guarantee the stability of the closed‐loop system.

Findings

The proposed ATPIDC system is applied to a DC servomotor on a FPGA chip. The hardware implementation of the ATPIDC scheme is developed in a real‐time mode. Using the FPGA to implement, the ATPIDC system can achieve the characteristics of small size, fast execution speed and less memory. A comparison among the fuzzy sliding‐mode control, adaptive robust PID control and the proposed ATPIDC is made. Experimental results verify a better position tracking response can be achieved by the proposed ATPIDC method after control parameters training.

Originality/value

The proposed ATPIDC approach is interesting for the design of an intelligent control scheme. An on‐line parameter training methodology, using the gradient descent method and the Lyapunov stability theorem, is proposed to increase the learning capability. The experimental results verify the system stabilization, favorable tracking performance and no chattering phenomena can be achieved by using the proposed ATPIDC system. Also, the proposed ATPIDC methodology can be easily extended to other motors.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 4 no. 1
Type: Research Article
ISSN: 1756-378X

Keywords

Article
Publication date: 3 July 2017

Mehran Esmaeili, Hossein Shayeghi, Hamid Mohammad Nejad and Abdollah Younesi

This paper aims to propose an improved reinforcement learning-based fuzzy-PID controller for load frequency control (LFC) of an island microgrid.

Abstract

Purpose

This paper aims to propose an improved reinforcement learning-based fuzzy-PID controller for load frequency control (LFC) of an island microgrid.

Design/methodology/approach

To evaluate the performance of the proposed controller, three different types of controllers including optimal proportional-integral-derivative (PID) controller, optimal fuzzy PID controller and the proposed reinforcement learning-based fuzzy-PID controller are compared. Optimal PID controller and classic fuzzy-PID controller parameters are tuned using Non-dominated Sorting Genetic Algorithm-II algorithm to minimize overshoot, settling time and integral square error over a wide range of load variations. The simulations are carried out using MATLAB/SIMULINK package.

Findings

Simulation results indicated the superiority of the proposed reinforcement learning-based controller over fuzzy-PID and optimal-PID controllers in the same operational conditions.

Originality/value

In this paper, an improved reinforcement learning-based fuzzy-PID controller is proposed for LFC of an island microgrid. The main advantage of the reinforcement learning-based controllers is their hardiness behavior along with uncertainties and parameters variations. Also, they do not need any knowledge about the system under control; thus, they can control any large system with high nonlinearities.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 36 no. 4
Type: Research Article
ISSN: 0332-1649

Keywords

Article
Publication date: 7 March 2008

Srinivasan Alavandar and M.J. Nigam

The purpose of this paper is to present the control of a six degrees of freedom (DOF) robot arm (PUMA robot) using fuzzy PD + I controller. Numerical simulation using the dynamic…

1270

Abstract

Purpose

The purpose of this paper is to present the control of a six degrees of freedom (DOF) robot arm (PUMA robot) using fuzzy PD + I controller. Numerical simulation using the dynamic model of six DOF robot arm shows the effectiveness of the approach in trajectory tracking problems. Comparative evaluation with respect to PID and fuzzy PID controls are presented to validate the controller design. The results presented emphasize that a satisfactory tracking precision could be achieved using fuzzy PD + I controller combination than fuzzy PID controller.

Design/methodology/approach

Control of a six DOF robot arm (PUMA Robot) using fuzzy PD + I controller.

Findings

The performance of fuzzy PD + I controllers improves appreciably compared to their respective fuzzy PID only or conventional PID counterparts.

Originality/value

Complexity of the proposed fuzzy PID controller is minimized as possible and only two design variables are used to adjust the rate of variations of the proportional gain and derivative gain.

Details

Industrial Robot: An International Journal, vol. 35 no. 2
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 9 April 2018

Arpit Jain, Satya Sheel and Piyush Kuchhal

The purpose of this paper is to study the application of entropy based optimized fuzzy logic control for a real-time non-linear system. Optimization of the fuzzy membership…

Abstract

Purpose

The purpose of this paper is to study the application of entropy based optimized fuzzy logic control for a real-time non-linear system. Optimization of the fuzzy membership function (MF) is one of the most explored areas for performance improvement of the fuzzy logic controllers (FLC). Conversely, majority of previous works are motivated on choosing an optimized shape for the MF, while on the other hand the support of fuzzy set is not accounted.

Design/methodology/approach

The proposed investigation provides the optimal support for predefined MFs by using genetic algorithms-based optimization of fuzzy entropy-based objective function.

Findings

The experimental results obtained indicate an improvement in the performance of the controller which includes improvement in error indices, transient and steady-state parameters. The applicability of proposed algorithm has been verified through real-time control of the twin rotor multiple-input, multiple-output system (TRMS).

Research limitations/implications

The proposed algorithm has been used for the optimization of triangular sets, and can also be used for the optimization of other fussy sets, such as Gaussian, s-function, etc.

Practical implications

The proposed optimization can be combined with other algorithms which optimize the mathematical function (shape), and a potent optimization tool for designing of the FLC can be formulated.

Originality/value

This paper presents the application of a new optimized FLC which is tested for control of pitch and yaw angles in a TRMS. The performance of the proposed optimized FLC shows significant improvement when compared with standard references.

Details

World Journal of Engineering, vol. 15 no. 2
Type: Research Article
ISSN: 1708-5284

Keywords

Article
Publication date: 17 October 2016

Chunchao Chen, Jinsong Li, Jun Luo, Shaorong Xie and Hengyu Li

This paper aims to improve the adaptability and control performance of the controller, a proposed seeker optimization algorithm (SOA) is introduced to optimize the controller…

528

Abstract

Purpose

This paper aims to improve the adaptability and control performance of the controller, a proposed seeker optimization algorithm (SOA) is introduced to optimize the controller parameters of a robot manipulator.

Design/methodology/approach

In this paper, a traditional proportional integral derivative (PID) controller and a fuzzy logic controller are integrated to form a fuzzy PID (FPID) controller. The SOA, as a novel algorithm, is used for optimizing the controller parameters offline. There is a performance comparison in terms of FPID optimization about the SOA, the genetic algorithm (GA), particle swarm optimization (PSO) and ant colony optimization (ACO). The DC motor model and the experimental platform are used to test the performance of the optimized controller.

Findings

Compared with GA, PSO and ACO, this novel optimization algorithm can enhance the control accuracy of the system. The optimized parameters ensure a system with faster response speed and better robustness.

Originality/value

A simplified FPID controller structure is constructed and a novel SOA method for FPID controller is presented. In this paper, the SOA is applied on the controller of 5-DOF manipulator, and the validation of controllers is tested by experiments.

Details

Industrial Robot: An International Journal, vol. 43 no. 6
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 13 December 2017

Ali Alouache and Qinghe Wu

The aim of this paper is to propose a robust robot fuzzy logic proportional-derivative (PD) controller for trajectory tracking of autonomous nonholonomic differential drive…

Abstract

Purpose

The aim of this paper is to propose a robust robot fuzzy logic proportional-derivative (PD) controller for trajectory tracking of autonomous nonholonomic differential drive wheeled mobile robot (WMR) of the type Quanser Qbot.

Design/methodology/approach

Fuzzy robot control approach is used for developing a robust fuzzy PD controller for trajectory tracking of a nonholonomic differential drive WMR. The linear/angular velocity of the differential drive mobile robot are formulated such that the tracking errors between the robot’s trajectory and the reference path converge asymptotically to zero. Here, a new controller zero-order Takagy–Sugeno trajectory tracking (ZTS-TT) controller is deduced for robot’s speed regulation based on the fuzzy PD controller. The WMR used for the experimental implementation is Quanser Qbot which has two differential drive wheels; therefore, the right/left wheel velocity of the differential wheels of the robot are worked out using inverse kinematics model. The controller is implemented using MATLAB Simulink with QUARC framework, downloaded and compiled into executable (.exe) on the robot based on the WIFI TCP/IP connection.

Findings

Compared to other fuzzy proportional-integral-derivative (PID) controllers, the proposed fuzzy PD controller was found to be robust, stable and consuming less resources on the robot. The comparative results of the proposed ZTS-TT controller and the conventional PD controller demonstrated clearly that the proposed ZTS-TT controller provides better tracking performances, flexibility, robustness and stability for the WMR.

Practical implications

The proposed fuzzy PD controller can be improved using hybrid techniques. The proposed approach can be developed for obstacle detection and collision avoidance in combination with trajectory tracking for use in environments with obstacles.

Originality/value

A robust fuzzy logic PD is developed and its performances are compared to the existing fuzzy PID controller. A ZTS-TT controller is deduced for trajectory tracking of an autonomous nonholonomic differential drive mobile robot (i.e. Quanser Qbot).

Details

Industrial Robot: An International Journal, vol. 45 no. 1
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 21 May 2013

G. Wang, K. Guo and B. Zhang

The filling paste blending system is the core part in a paste backfill mining scheme. Its precision directly determines the flow properties and condensation curing performance of…

Abstract

The filling paste blending system is the core part in a paste backfill mining scheme. Its precision directly determines the flow properties and condensation curing performance of the filling slurry, thus it affects the filling effect of the underground mining working face. The research fuzzy PID control algorithm is introduced into the filling paste blending automatic control system in order to achieve a better control effect (Geng, 2007). Detailed introduces fuzzy PID controller design process, through the simulation experiment shows that fuzzy PID controller improves the system of external disturbance, and adapt to the internal parameters change robustness, ensure the precision of the burden system.

Details

World Journal of Engineering, vol. 10 no. 2
Type: Research Article
ISSN: 1708-5284

Keywords

Article
Publication date: 21 March 2016

Manfen Han, Huapeng Wu, Yuntao Song, Yong Cheng and Heikki Handroos

The purpose of this paper is to investigate an intelligent control for water hydraulic position servo system which is intent to be used in remote control robot for fusion reactor…

Abstract

Purpose

The purpose of this paper is to investigate an intelligent control for water hydraulic position servo system which is intent to be used in remote control robot for fusion reactor. The dynamic model of water hydraulic servo control system is built and proportional–integral–derivative (PID) controller is used.

Design/methodology/approach

PID control is the most common control algorithm used in industry and has been a conventional tool used to operate closed-loop control system; however, it is very difficult to achieve high accuracy and fast response by using the traditional way to tune its perimeters. To improve the control performance, optimization algorithm can be applied to search the best parameters of PID. This paper presents a search algorithm using particle swarm with H2 control standards objective function to optimize PID parameters.

Findings

By comparing simulation and mock-up experiments’ results from different control methods, the particle swarm optimization algorithm presents better performance and is more effective for tuning PID parameters.

Originality/value

This paper presents an effective way to ensure safety and efficiency for remote handling maintenances of China Fusion Engineering Test Reactor.

Details

Industrial Robot: An International Journal, vol. 43 no. 2
Type: Research Article
ISSN: 0143-991X

Keywords

1 – 10 of 491