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All Journal International Journal of Electrical and Computer Engineering TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Computer Science
Khairuddin Osman
Universiti Teknikal Malaysia Melaka
Computer Science & IT Electrical & Electronics Engineering

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Modified Predictive Control for a Class of Electro-Hydraulic Actuator Abdulrahman A.A. Emhemed; Rosbi Bin Mamat; Ahmad ‘Athif Mohd Faudzi; Mohd Ridzuan Johary; Khairuddin Osman
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 2: April 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (595.419 KB) | DOI: 10.11591/ijece.v6i2.pp630-638

Abstract

Many model predictive control (MPC) algorithms have been proposed in the literature depending on the conditionality of the system matrix and the tuning control parameters. A modified predictive control method is proposed in this paper. The modified predictive method is based on the control matrix formulation combined with optimized move suppression coefficient. Poor dynamics and high nonlinearities are parts of the difficulties in the control of the Electro-Hydraulic Actuator (EHA) functions, which make the proposed matrix an attractive solution. The developed controller is designed based on simulation model of a position control EHA to reduce the overshoot of the system and to achieve better and smoother tracking. The performance of the designed controller achieved quick response and accurate behavior of the tracking compared to the previous study.
Pneumatic positioning control system using constrained model predictive controller: Experimental repeatability test Siti Fatimah Sulaiman; M. F. Rahmat; Ahmad Athif Faudzi; Khairuddin Osman; S. I. Samsudin; A. F. Z. Abidin; Noor Asyikin Sulaiman
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp3913-3923

Abstract

Most of the controllers that were proposed to control the pneumatic positioning system did not consider the limitations or constraints of the system in their algorithms. Non-compliance with the prescribed system constraints may damage the pneumatic components and adversely affect its positioning accuracy, especially when the system is controlled in real-time environment. Model predictive controller (MPC) is one of the predictive controllers that is able to consider the constraint of the system in its algorithm. Therefore, constrained MPC (CMPC) was proposed in this study to improve the accuracy of pneumatic positioning system while considering the constraints of the system. The mathematical model of pneumatic system was determined by system identification technique and the control signal to the valves were considered as the constraints of the pneumatic system when developing the controller. In order to verify the accuracy and reliability of CMPC, repetitive experiments on the CMPC strategy was implemented. The existing predictive controller, that was used to control the pneumatic system such as predictive functional control (PFC), was also compared. The experimental results revealed that CMPC effectively improved the position accuracy of the pneumatic system compared to PFC strategy. However, CMPC not capable to provide a fast response as PFC.
A new technique to reduce overshoot in pneumatic positioning system Siti Fatimah Sulaiman; M. F. Rahmat; A. A. M. Faudzi; Khairuddin Osman
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 5: October 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i5.12807

Abstract

This paper presents a new approach for improving the performance of the pneumatic positioning system by incorporating a nonlinear gain function with observer system. System identification technique has been employed to represent the pneumatic system, while a model predictive control (MPC) with the observer system has been employed as the main controller to control the positioning of the system. The nonlinear gain function has been incorporated with the control strategy to compensate nonlinearities and uncertainties inherent in the parameters of the system. Unconstrained and constrained cases of control signals have been considered in this study. Simulation based on Matlab/Simulink indicated a reduction in overshoot of the system response for both cases due to additional nonlinear gain function in the strategy. Furthermore, remarkable enhancement was observed in effectiveness of this function while incorporated in constrained case, when this new strategy successfully improved the transient response in the pneumatic positioning system.
Modelling and proportional-integral-derivative controller design for position analysis of the 3-degree of freedom Nur Syahirah Eshah Budin; Khairuddin Osman
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp62-70

Abstract

A closed-loop system or which can also be known as a feedback system helps the system to achieve the desired output by comparing the input and the output values. If any difference is detected, the closed-loop system will create an error signal and automatically responds to it. Other than that, the proportional-integral-derivative (PID) controller has a feedback mechanism. Thus, this creates the curiosity whether the closed-loop system and PID which both have the characteristic of a feedback system, can give the same. In this paper, the comparison of the model of 3 degree of freedom (DOF) Mitsubishi RV2-AJ is being made between two models of a robot arm that has a closed-loop system but only one that is embedded with PID controller while the other one is not, these two are simulated for different positions. The new model is created by using Solidworks which is later exported to Matlab-Simulink. The results from MATLAB-Simulink show that the model which is equipped with a PID controller has better results in terms of the rise time and percentage of overshoot. These results confirm the effectiveness of PID controller in producing smaller errors in the systems even when both models are created together with closed-loop systems.
Modelling and PID control system integration for quadcopter DJI F450 attitude stabilization N. M. Salma; Khairuddin Osman
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 3: September 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i3.pp1235-1244

Abstract

In this paper we focus on the overall overview of the mathematical modelling of the DJI F450 UAV quadcopter, the hardware and software system integration based on PID control system for the attitude feedback. The parameter specification of the DJI F450 is fed into the mathematical model and implement a basic PID for the system. Future research using the DJI F450 model can benefit from this observation by implementing the modelling and tune in their own variable that varies, such as the overall of their weight. The data of PID control system simulation using the quadcopter frame model type DJI F450 parameter. The mathematical model for the quadcopter modelled DJI F450 is developed using Newton-Euler method. Altitude data for the control system is obtain from the analysis data of the Simulink simulation. The simulation is done using the Simulink toolbox inside the MATLAB software. From this paper, we can more understand the step involves in making a full control system of a quadcopter. The mathematical model for other type of quadcopter model can be implemented using the steps with their own parameter and achieve fast development.
Design of proportional integral and derivative controller using particle swarm optimization technique for gimbal system Mohd Hafiez Ahmad; Khairuddin Osman; Sharatul Izah Samsudin
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp714-722

Abstract

This paper presents the development of an optimal proportional, integral and derivative (PID) controller for controlling camera gimbal on unmanned aerial systems (UAV). Three optimal controller improvements are obtained using the suggested particle swarm optimization (PSO) technique. The PSO algorithm is initially built and integrated with the PID controller to control the DC motor gimbal. Before comparing the performance of a DC motor with PSO-PID with a DC motor with Zeigler-Nichols controller, the impacts of iteration numbers are explored. Finally, bode analysis was conducted to validate the stability of the proposed PSO-PID controller. Simulation is conducted within the MATLAB environment to verify the system's performance in terms of settling time, steady-state error and overshoot. The simulation results show has a longer settling time (0.91656 sec) than the Ziegler-Nichols controller (0.14316 sec) but a shorter rising time (0.091686 sec) than the Ziegler-Nichols controller (0.00094 sec). Furthermore, the overshoot was lowered from 12.941% to 0.959% as a result. As a result, the suggested PSO-PID controller technique outperforms the Ziegler-Nichols controller in terms of overshoot and rise time. Further study will investigate the integration of other optimisation methodologies such as fuzzy logic for better performance.
Enhancement in pneumatic positioning system using nonlinear gain constrained model predictive controller: experimental validation Siti Fatimah Sulaiman; M. F. Rahmat; Ahmad Athif Faudzi; Khairuddin Osman; N. H. Sunar
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1385-1397

Abstract

The issues of inaccurate positioning control have made an industrial use of pneumatic actuator remains restricted to certain applications only. Non-compliance with system limits and properly control the operating system may also degrade the performance of pneumatic positioning systems. This study proposed a new approach to enhance pneumatic positioning system while considering the constraints of system. Firstly, a mathematical model that represented the pneumatic system was determined by system identification approach. Secondly, model predictive controller (MPC) was developed as a primary controller to control the pneumatic positioning system, which took into account the constraints of the system. Next, to enhance the performance of the overall system, nonlinear gain function was incorporated within the MPC algorithm. Finally, the performances were compared with other control methods such as constrained MPC (CMPC), proportional-integral (PI), and predictive functional control with observer (PFC-O). The validation based on real-time experimental results for 100 mm positioning control revealed that the incorporation of nonlinear gain within the MPC algorithm improved 21.03% and 2.69% of the speed response given by CMPC and PFC-O, and reduced 100% of the overshoot given by CMPC and PI controller; thus, providing fast and accurate pneumatic positioning control system.
Co-Authors A. A. M. Faudzi A. F. Z. Abidin Abdulrahman A.A. Emhemed Ahmad Athif Faudzi Ahmad ‘Athif Mohd Faudzi M. F. Rahmat Mohd Hafiez Ahmad Mohd Ridzuan Johary N. H. Sunar N. M. Salma Noor Asyikin Sulaiman Nur Syahirah Eshah Budin Rosbi Bin Mamat S. I. Samsudin Sharatul Izah Samsudin Siti Fatimah Sulaiman