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Gasim Hayder; Mahmud Iwan Solihin; Khairul Faizal Bin Kushiar. A Performance Comparison of Various Artificial Intelligence Approaches for Estimation of Sediment of River Systems. Journal of Ecological Engineering 2021, 22, 20 -27.
AMA StyleGasim Hayder, Mahmud Iwan Solihin, Khairul Faizal Bin Kushiar. A Performance Comparison of Various Artificial Intelligence Approaches for Estimation of Sediment of River Systems. Journal of Ecological Engineering. 2021; 22 (7):20-27.
Chicago/Turabian StyleGasim Hayder; Mahmud Iwan Solihin; Khairul Faizal Bin Kushiar. 2021. "A Performance Comparison of Various Artificial Intelligence Approaches for Estimation of Sediment of River Systems." Journal of Ecological Engineering 22, no. 7: 20-27.
Stingless bee honey is a type of popular honey in Malaysia. In this study, a total of 30 stingless bee honey samples were exclusively collected from the beekeepers, honeybee suppliers, and honeybee farms in Malaysia. The quality of stingless bee honey is evaluated against the standard, while the near‐infrared (NIR) spectroscopy technique is implemented for detecting adulterated honey. One out of thirty (30) honey samples do not fulfill the requirements of moisture content and hydroxymethylfurfural content, according to Standard of Malaysia, while only five (5) honey samples fulfill the requirement of the pH value. Furthermore, the NIR spectra data interpretation using PCA (Principal Component Analysis) combined with Logistic Regression shows that the accuracy of above 98% is obtained for both train dataset and test dataset. This high accuracy of honey adulteration identification using the NIR spectrometer shows its promising immediate application for rapid non‐destructive fraud detection in honey.
Shi Hui Tan; Liew Phing Pui; Mahmud Iwan Solihin; Kong Seah Keat; Wei Hong Lim; Chun Kit Ang. Physicochemical analysis and adulteration detection in Malaysia stingless bee honey using a handheld near‐infrared spectrometer. Journal of Food Processing and Preservation 2021, e15576 .
AMA StyleShi Hui Tan, Liew Phing Pui, Mahmud Iwan Solihin, Kong Seah Keat, Wei Hong Lim, Chun Kit Ang. Physicochemical analysis and adulteration detection in Malaysia stingless bee honey using a handheld near‐infrared spectrometer. Journal of Food Processing and Preservation. 2021; ():e15576.
Chicago/Turabian StyleShi Hui Tan; Liew Phing Pui; Mahmud Iwan Solihin; Kong Seah Keat; Wei Hong Lim; Chun Kit Ang. 2021. "Physicochemical analysis and adulteration detection in Malaysia stingless bee honey using a handheld near‐infrared spectrometer." Journal of Food Processing and Preservation , no. : e15576.
Water resources management in Malaysia has become a crucial issue of concern due to its role in the economic and social development of the country. Kelantan river (Sungai Kelantan) basin is one of the essential catchments as it has a history of flood events. Numerous studies have been conducted in river basin modelling for the prediction of flow and mitigation of flooding events as well as water resource management. This paper presents river flow modelling based on meteorological and weather data in the Sungai Kelantan region using a cascade-forward neural network trained with particle swarm optimization algorithm (CFNNPSO). The result is compared with those trained with the Levenberg–Marquardt (LM) and Bayesian Regularization (BR) algorithm. The outcome of this study indicates that there is a strong correlation between river flow and some meteorological and weather variables (weighted rainfall, average evaporation and temperatures). The correlation scores (R) obtained between the target variable (river flow) and the predictor variables were 0.739, −0.544, and −0.662 for weighted rainfall, evaporation, and temperature, respectively. Additionally, the developed nonlinear multivariable regression model using CFNNPSO produced acceptable prediction accuracy during model testing with the regression coefficient (R2), root mean square error (RMSE), and mean of percentage error (MPE) of 0.88, 191.1 cms and 0.09%, respectively. The reliable result and predictive performance of the model is useful for decision makers during water resource planning and river management. The constructed modelling procedure can be adopted for future applications.
Gasim Hayder; Mahmud Iwan Solihin; Hauwa Mohammed Mustafa. Modelling of River Flow Using Particle Swarm Optimized Cascade-Forward Neural Networks: A Case Study of Kelantan River in Malaysia. Applied Sciences 2020, 10, 8670 .
AMA StyleGasim Hayder, Mahmud Iwan Solihin, Hauwa Mohammed Mustafa. Modelling of River Flow Using Particle Swarm Optimized Cascade-Forward Neural Networks: A Case Study of Kelantan River in Malaysia. Applied Sciences. 2020; 10 (23):8670.
Chicago/Turabian StyleGasim Hayder; Mahmud Iwan Solihin; Hauwa Mohammed Mustafa. 2020. "Modelling of River Flow Using Particle Swarm Optimized Cascade-Forward Neural Networks: A Case Study of Kelantan River in Malaysia." Applied Sciences 10, no. 23: 8670.
Spectroscopy including Near infrared spectroscopy (NIRS) is a non-destructive and rapid technique applied increasingly for food quality evaluation, medical diagnosis, manufacturing, etc. The qualitative or quantitative information using NIRS is only obtained after spectra data calibration process based mathematical knowledge in chemometrics and statistics. This process naturally involves multivariate statistical analysis. Machine learning as a subset of AI (artificial intelligence), in addition to conventional multivariate statistical tools, seems to get more popularity for chemometric calibration of NIRS data nowadays. However, often the software/toolboxes in chemometrics are commercialized version which is not free. For the free versions, programming skills are required to deal with applications of machine learning in spectra data calibration. Therefore, this paper introduces a different approach of spectra data calibration based on visual programming approach using Orange data mining, a free software which is still rarely used by the research community in spectroscopy. The data used namely: pesticide sprayed on cabbage (to classify between pure cabbage and pesticide-sprayed cabbage with different level of pesticide solution), mango sweetness assessment (to predict sugar soluble content in mango based on Brix degree value). These two data represent classification and regression respectively. This approach is intended more for researchers who want to apply machine learning calibration in their spectroscopy data but don’t want to have rigorous programming jobs, i.e. for non-programmers.
Mahmud Iwan Solihin; Zheng Zekui; Chun Kit Ang; Fahri Heltha; Mohamed Rizon. Machine Learning Calibration for Near Infrared Spectroscopy Data: A Visual Programming Approach. Lecture Notes in Electrical Engineering 2020, 577 -590.
AMA StyleMahmud Iwan Solihin, Zheng Zekui, Chun Kit Ang, Fahri Heltha, Mohamed Rizon. Machine Learning Calibration for Near Infrared Spectroscopy Data: A Visual Programming Approach. Lecture Notes in Electrical Engineering. 2020; ():577-590.
Chicago/Turabian StyleMahmud Iwan Solihin; Zheng Zekui; Chun Kit Ang; Fahri Heltha; Mohamed Rizon. 2020. "Machine Learning Calibration for Near Infrared Spectroscopy Data: A Visual Programming Approach." Lecture Notes in Electrical Engineering , no. : 577-590.
This paper discusses an application of metaheuristic optimization algorithms for a single-objective constrained optimization in a robust feedback controller design of anti-swing gantry crane control. A set robust feedback controller gains is optimized based on plant’s linear model having structured parametric uncertainty, i.e. gantry crane system. A wedge region is assigned as the optimization constraint to specify the desired closed-loop poles location which is directly related to desired time-domain response. The simulation results of the proposed robust control design using multiswarm particle swarm optimization without velocity (MPSOWV) is presented. The control performance of the feedback system optimized with MPSOWV are compared with that of PSO (particle swarm optimization), DE (differential evolution) and TLBO-PSO (improved teaching-learning-based optimization with the social character of particle swarm optimization). The simulation studies show that the controller optimized by the proposed MPSOWV demonstrates the most robust performance as compared to the other peer algorithms used in this paper for being able to produce the largest stability radius \(\left( {r_{c} } \right)\) consistently, i.e. \(r_{c} = 3.4325\) in average for 20 runs.
Mahmud Iwan Solihin; Wei Hong Lim; Sew Sun Tiang; Chun Kit Ang. Modified Particle Swarm Optimization for Robust Anti-swing Gantry Crane Controller Tuning. Lecture Notes in Electrical Engineering 2020, 1173 -1192.
AMA StyleMahmud Iwan Solihin, Wei Hong Lim, Sew Sun Tiang, Chun Kit Ang. Modified Particle Swarm Optimization for Robust Anti-swing Gantry Crane Controller Tuning. Lecture Notes in Electrical Engineering. 2020; ():1173-1192.
Chicago/Turabian StyleMahmud Iwan Solihin; Wei Hong Lim; Sew Sun Tiang; Chun Kit Ang. 2020. "Modified Particle Swarm Optimization for Robust Anti-swing Gantry Crane Controller Tuning." Lecture Notes in Electrical Engineering , no. : 1173-1192.
Robust control of underactuated nonlinear systems is a challenging task using conventional methods because of uncertainties which may lead to failure especially for mechanical and robotic applications. Fuzzy logic controller (FLC) is one of the methods specifically used for designing a robust controller that is able to deal with nonlinearity and achieve satisfactory performance for control applications. FLC uses heuristic information or expert operator knowledge to create its mechanism. However, nonlinearities exist in the control systems make its rule-based FLC design a non-trivial task. Manual trial and error tuning method is common way used for tuning the parameters of FLC to achieve the desired performance of the system. Hence, an automatic tuning using optimization algorithm is necessary. Meta-heuristic optimization algorithms are applied to tune the parameters of FLC automatically. In this paper, three popular meta-heuristic algorithms are used to optimize the scaling factors of FLC, i.e. Particle Swarm Optimization (PSO), Cuckoo Search (CS) and Differential Evolution (DE) to improve the effectiveness of FLC design. A gantry crane system, which is a nonlinear system, is used as test system for this project. The simulation of the optimization of FLC parameters by using meta-heuristics algorithms was successfully achieved. The simulation results show that the optimization techniques for FLC are effective to improve the performance of conventional FLC for gantry crane control, i.e. position control and anti-swing control. In addition, PSO performs better than CS and DE in optimization of FLC for gantry crane system.
Mahmud Iwan Solihin; Cheah Yong Chuan; Winda Astuti. Optimization of fuzzy logic controller parameters using modern meta-heuristic algorithm for gantry crane system (GCS). Materials Today: Proceedings 2020, 29, 168 -172.
AMA StyleMahmud Iwan Solihin, Cheah Yong Chuan, Winda Astuti. Optimization of fuzzy logic controller parameters using modern meta-heuristic algorithm for gantry crane system (GCS). Materials Today: Proceedings. 2020; 29 ():168-172.
Chicago/Turabian StyleMahmud Iwan Solihin; Cheah Yong Chuan; Winda Astuti. 2020. "Optimization of fuzzy logic controller parameters using modern meta-heuristic algorithm for gantry crane system (GCS)." Materials Today: Proceedings 29, no. : 168-172.
The aim of this study is to build a classifier model based on spectra data collected using handheld spectrometer that can classify between different types of food powders (flour and starch). A total of 70 samples were prepared from three different types of flour (whole wheat, organic wheat, and rice flour) and two different types of starch (corn and tapioca starch). Handpalm size handheld spectrometer is used to record the spectrum of each sample, the spectrometer has wavelength range of 900nm to 1700nm. The spectra data is pre-processed using gaussian smoothing to filter the data from noise and unrelated information. Multivariable data analysis method as principle component analysis (PCA) is used to eliminate irrelevant data and reduce the number of variables to three principle components for easier analysis and visualization. Support vector machine (SVM) is used to build a classification model. The training/calibration of the model was done by using 80% of the dataset while the remaining 20% was for testing the model. The results show that with proper pre-processing and PCA, classification of 100% accuracy can be achieved. This study indicates the potential future application of this approach for rapid detection in food powders fraud and adulteration.
Mohamed Yasser Mohamed; Mahmud Iwan Solihin; Winda Astuti; Chun Kit Ang; Wan Zailah. Food powders classification using handheld Near-Infrared Spectroscopy and Support Vector Machine. Journal of Physics: Conference Series 2019, 1367, 012029 .
AMA StyleMohamed Yasser Mohamed, Mahmud Iwan Solihin, Winda Astuti, Chun Kit Ang, Wan Zailah. Food powders classification using handheld Near-Infrared Spectroscopy and Support Vector Machine. Journal of Physics: Conference Series. 2019; 1367 (1):012029.
Chicago/Turabian StyleMohamed Yasser Mohamed; Mahmud Iwan Solihin; Winda Astuti; Chun Kit Ang; Wan Zailah. 2019. "Food powders classification using handheld Near-Infrared Spectroscopy and Support Vector Machine." Journal of Physics: Conference Series 1367, no. 1: 012029.
Quality determines the shelf-life and selling prices of fresh mango, and therefore quality observation and control of fresh mango are of utmost significance in the processing and management of its supply chain. Mango fruit (mangifera indica) quality methods are mostly destructive in nature. Different mechanical, electromagnetic and non-destructive methods are increasingly important nowadays because of the ease of operation, speed, and reliability of the process. This project aims to develop a non-destructive assessment of mango quality using handheld micro NIR (near-infrared) spectroscopic device. NIR spectra data and Brix levels, which indicate the sugar content of the plant, i.e. indicating the sweetness of the mango, were collected from three different types of Mango (Chokanan, Rainbow, and Kai Te), resulting 80 samples (i.e. 60 samples for training and 20 samples for testing) in this project. NIR spectra can be converted mathematically to obtain quantitative information of chemical and physical nature by multivariate calibration. The spectra data is pre-processed using Gaussian smoothing and extended multiplicative signal correction (EMSC) for the elimination of uncontrollable path length or scattering effects. These samples were then used to develop a predictive model using both Support Vector Machine (SVM) regression and Partial Least Squares regression (PLS) methods. The coefficient of determination (R2) obtained from SVM for training/calibration and testing dataset are 0.96 and 0.95 respectively. Meanwhile, the coefficient of determination (R2) obtained from PLS for calibration/training and testing dataset are 0.89 and 0.86 respectively. The results obtained from this project indicate that the handheld NIR has potential use for non-destructive assessment of mango fruits quality.
Dheya Galal Abdullah Al-Sanabani; Mahmud Iwan Solihin; Liew Phing Pui; Winda Astuti; Chun Kit Ang; Lim Wei Hong. Development of non-destructive mango assessment using Handheld Spectroscopy and Machine Learning Regression. Journal of Physics: Conference Series 2019, 1367, 012030 .
AMA StyleDheya Galal Abdullah Al-Sanabani, Mahmud Iwan Solihin, Liew Phing Pui, Winda Astuti, Chun Kit Ang, Lim Wei Hong. Development of non-destructive mango assessment using Handheld Spectroscopy and Machine Learning Regression. Journal of Physics: Conference Series. 2019; 1367 (1):012030.
Chicago/Turabian StyleDheya Galal Abdullah Al-Sanabani; Mahmud Iwan Solihin; Liew Phing Pui; Winda Astuti; Chun Kit Ang; Lim Wei Hong. 2019. "Development of non-destructive mango assessment using Handheld Spectroscopy and Machine Learning Regression." Journal of Physics: Conference Series 1367, no. 1: 012030.
A robust feedback controller is designed to maximize complex stability radius via single objective constrained optimization using Cuckoo Search Optimization (CSO) in this paper. A set robust feedback controller gains is optimized based on plant’s linear model having structured parametric uncertainty, i.e. two mass benchmark system. A wedge region is assigned as the optimization constraint to specify the desired closed-loop poles location which is directly related to desired time-domain response. The simulation results show that the robustness performance is achieved in the presence of parameter variations of the plant. In addition, the feedback controller optimized by CSO performs slightly better than that optimized by differential evolution algorithm previously designed.
Mahmud Iwan Solihin; Rini Akmeliawati. Robust Feedback Controller Design Using Cuckoo Search Optimization to Maximize Stability Radius. Communications in Computer and Information Science 2019, 62 -75.
AMA StyleMahmud Iwan Solihin, Rini Akmeliawati. Robust Feedback Controller Design Using Cuckoo Search Optimization to Maximize Stability Radius. Communications in Computer and Information Science. 2019; ():62-75.
Chicago/Turabian StyleMahmud Iwan Solihin; Rini Akmeliawati. 2019. "Robust Feedback Controller Design Using Cuckoo Search Optimization to Maximize Stability Radius." Communications in Computer and Information Science , no. : 62-75.
Every region of foot is not equally divided in terms of plantar pressure distribution (PPD) during free standing. This paper is focusing on studying PPD on flat plane and inclined plane and the results obtained from this study may contribute to biomedical researcher in designing orthotic devices. 24 healthy young adults age ranging from 19 to 24 years old and weigh between 50 to 80 kg were invited for experiments purpose. Six regions of both feet were measured which were hallux, medial forefoot, central forefoot, lateral forefoot, lateral midfoot and hindfoot. Remarkable differences were seen in the result as right foot exerted more pressure generally in every region of the foot as to compared with left foot respectively. This is true especially for region such as hallux, medial forefoot and lateral forefoot. On a flat surface, PPD on the hindfoot is the highest. However, at an elevation of 25°, test subjects began to shift their PPD to forefoot regions. While studies of PPD are common, this study provides a new insight for the first time into PPD while standing on different angle of walking plane.
Chun Kit Ang; Mahmud Iwan Solihin; Weng Jun Chan; Yien Yien Ong. Study of Plantar Pressure Distribution. MATEC Web of Conferences 2018, 237, 01016 .
AMA StyleChun Kit Ang, Mahmud Iwan Solihin, Weng Jun Chan, Yien Yien Ong. Study of Plantar Pressure Distribution. MATEC Web of Conferences. 2018; 237 ():01016.
Chicago/Turabian StyleChun Kit Ang; Mahmud Iwan Solihin; Weng Jun Chan; Yien Yien Ong. 2018. "Study of Plantar Pressure Distribution." MATEC Web of Conferences 237, no. : 01016.
Grasp stability is considered to be an important aspect in object manipulation of a multifingered robot hand. Multifingered hand contacts the object at some arbitrary locations during the object manipulation and applies the gripping force to hold and manipulate the object without slip. It is desirable to use the optimum gripping force during the grasp manipulation for two reasons; firstly, to prevent the object from damages, secondly, to decrease the cost of the manipulation. With these objectives in mind, a three-fingered soft hand is designed, and gripping force and stability analysis are done experimentally. DC motors are used to actuate the joints of fingers and force sensors are used to measure the internal force at contact points. PID controller is used to controlling the internal force exerted at the contact points, and the control parameters are tweaked until a satisfactory response is achieved. The minimum gripping force required to handle the object with / without external disturbances is measured. The position variables and frictional coefficients are evaluated from the contact forces at the contact points. In future, the optimization algorithm will be integrated to carry out these tasks in constrained and unconstrained environments.
Elango Natarajan; Mahmud Iwan Solihin; Jeunn Hao Chong. Grasp Stability Analysis of an Isotropic Direct Driven Three-Finger Soft Robot Hand. International Journal on Advanced Science, Engineering and Information Technology 2017, 7, 1627 -1631.
AMA StyleElango Natarajan, Mahmud Iwan Solihin, Jeunn Hao Chong. Grasp Stability Analysis of an Isotropic Direct Driven Three-Finger Soft Robot Hand. International Journal on Advanced Science, Engineering and Information Technology. 2017; 7 (5):1627-1631.
Chicago/Turabian StyleElango Natarajan; Mahmud Iwan Solihin; Jeunn Hao Chong. 2017. "Grasp Stability Analysis of an Isotropic Direct Driven Three-Finger Soft Robot Hand." International Journal on Advanced Science, Engineering and Information Technology 7, no. 5: 1627-1631.
Cuckoo Search (CS) and Differential Evolution (DE) algorithms are considerably robust meta-heuristic algorithms to solve constrained optimization problems. In this study, the performance of CS and DE are compared in solving the constrained optimization problem from selected benchmark functions. Selection of the benchmark functions are based on active or inactive constraints and dimensionality of variables (i.e. number of solution variable). In addition, a specific constraint handling and stopping criterion technique are adopted in the optimization algorithm. The results show, CS approach outperforms DE in term of repeatability and the quality of the optimum solutions.
Mahmud Iwan Solihin; Mohd Fauzi Zanil. Performance Comparison of Cuckoo Search and Differential Evolution Algorithm for Constrained Optimization. IOP Conference Series: Materials Science and Engineering 2016, 160, 012108 .
AMA StyleMahmud Iwan Solihin, Mohd Fauzi Zanil. Performance Comparison of Cuckoo Search and Differential Evolution Algorithm for Constrained Optimization. IOP Conference Series: Materials Science and Engineering. 2016; 160 (1):012108.
Chicago/Turabian StyleMahmud Iwan Solihin; Mohd Fauzi Zanil. 2016. "Performance Comparison of Cuckoo Search and Differential Evolution Algorithm for Constrained Optimization." IOP Conference Series: Materials Science and Engineering 160, no. 1: 012108.
Swarm robotics come into the picture of replacing humans on life-risking jobs because of its decentralization concept, i.e. a damaged unit do not affect the entire system performance. Airborne type swarm robotics have high flexibility since they can bypass most obstacles. Swarm robotics can be utilized to scout unknown terrain, target searching or S.A.R applications. In this project, simulation to visualize the swarm quadcopters’ performance onto an assigned environment using robotic software simulator called V-REP software is presented. Robotic simulator software take account of real-life physics which increases the accuracy for simulation and retrieves reliable results from the simulation. Hence, robotic simulator software could replace real-life testing for at least initial ideas exploration to real-life situation.
Yeong Yie; Mahmud Iwan Solihin; Ang Chun Kit. Development of Swarm Robots for Disaster Mitigation Using Robotic Simulator Software. Lecture Notes in Electrical Engineering 2016, 377 -383.
AMA StyleYeong Yie, Mahmud Iwan Solihin, Ang Chun Kit. Development of Swarm Robots for Disaster Mitigation Using Robotic Simulator Software. Lecture Notes in Electrical Engineering. 2016; ():377-383.
Chicago/Turabian StyleYeong Yie; Mahmud Iwan Solihin; Ang Chun Kit. 2016. "Development of Swarm Robots for Disaster Mitigation Using Robotic Simulator Software." Lecture Notes in Electrical Engineering , no. : 377-383.
Rotary crane system is extensively used in many applications to carry payload from one position to another position. The cart and jib of the crane will start to accelerate in linear and rotational motions respectively when input signal to the crane system is applied. This will cause the swinging or swaying of the payload. Therefore, an anti-swing for automatic crane is usually proposed. This project presents the modeling and intelligent control system design for a rotary crane. The modeling and simulation was done using MATLAB Simscape Toolbox which is physical approach of modeling. The mathematical model of the crane was also derived for comparison. The intelligent control system is implemented as Fuzzy-PID controller. The physical modeling approach using MATLAB Simscape Toolbox can ease the modeling process since mathematical modeling approach is usually tedious. The results obtained in the simulation shows that the implemented fuzzy-PID controller is capable of suppressing the sway angle of the load and fast settling time can be observed.
R. S. Arvin; Mahmud Iwan Solihin; F. Heltha; Rodney H. G. Tan; A. M. A. Ammar. Modeling and control design for rotary crane system using MATLAB Simscape Toolbox. 2014 IEEE 5th Control and System Graduate Research Colloquium 2014, 170 -175.
AMA StyleR. S. Arvin, Mahmud Iwan Solihin, F. Heltha, Rodney H. G. Tan, A. M. A. Ammar. Modeling and control design for rotary crane system using MATLAB Simscape Toolbox. 2014 IEEE 5th Control and System Graduate Research Colloquium. 2014; ():170-175.
Chicago/Turabian StyleR. S. Arvin; Mahmud Iwan Solihin; F. Heltha; Rodney H. G. Tan; A. M. A. Ammar. 2014. "Modeling and control design for rotary crane system using MATLAB Simscape Toolbox." 2014 IEEE 5th Control and System Graduate Research Colloquium , no. : 170-175.
PID (proportional+integral+derivative) controller is well known as a simple and easy-to-implement controller. However, the design procedure is not straightforward for multi-input multi-output (MIMO) systems. It is even more complicated when robustness criterion must be handled. In this paper, a stable robust PID controller for anti-swing control of automatic gantry crane is proposed. The proposed method employs an automatic tuning using DE (differential evolution) to search for a set of PID controller gains that satisfy Kharitonovs polynomials robust stability criterion. This robust stability criterion is used to deal with parametric uncertainty occurs in gantry crane model. The simulation results show that a satisfactory robust PID control performance can be achieved. The PID controller is able to quickly move the cart of the crane while suppressing the swing of the payload for various conditions, i.e. payload mass and cable length variations.
Mahmud Iwan Solihin; Mah Chia Wen; Fahri Heltha; Lim Chong Lye. Robust PID Controller Tuning for 2D Gantry Crane Using Kharitonov's Theorem and Differential Evolution Optimizer. Advanced Materials Research 2014, 903, 267 -272.
AMA StyleMahmud Iwan Solihin, Mah Chia Wen, Fahri Heltha, Lim Chong Lye. Robust PID Controller Tuning for 2D Gantry Crane Using Kharitonov's Theorem and Differential Evolution Optimizer. Advanced Materials Research. 2014; 903 ():267-272.
Chicago/Turabian StyleMahmud Iwan Solihin; Mah Chia Wen; Fahri Heltha; Lim Chong Lye. 2014. "Robust PID Controller Tuning for 2D Gantry Crane Using Kharitonov's Theorem and Differential Evolution Optimizer." Advanced Materials Research 903, no. : 267-272.
In this paper, a two-degree of freedom (2DOF) controller is designed for a ball and beam system. The controller is developed based on the algebraic method. The ball and beam system is one of the most popular laboratory experiments for control education. The controller is designed such that the ball can track a square wave with a certain design specification. The advantages of 2DOF controller are the feedback controller takes care of the uncertainty and the feedforward filter ensures the tracking of the reference command. Though the control method is not new, the application of the technique on such unstable system is of interest. Controlling the ball on the beam is a challenging task because of the instability of the system and the fact that the output, i.e. the ball position, increases almost without limit for a fixed input beam angle. The controller needs to regulate the position of the ball by changing the angle of the beam at the pivot point. It is a difficult control task as the ball moves with an acceleration which is proportional to the tilt angle of the beam. Two types of 2DOF controllers are considered; based on dominant pole design and based on integral time absolute error (ITAE) design. The performances of the resulting controllers are compared. Simulations were run over various frequencies. The results indicate the effectiveness of the designed 2DOF controllers in achieving the design specification.
N N Abdul Aziz; M I Yusoff; M I Solihin; R Akmeliawati. Two degrees of freedom control of a ball and beam system. IOP Conference Series: Materials Science and Engineering 2013, 53, 012070 .
AMA StyleN N Abdul Aziz, M I Yusoff, M I Solihin, R Akmeliawati. Two degrees of freedom control of a ball and beam system. IOP Conference Series: Materials Science and Engineering. 2013; 53 ():012070.
Chicago/Turabian StyleN N Abdul Aziz; M I Yusoff; M I Solihin; R Akmeliawati. 2013. "Two degrees of freedom control of a ball and beam system." IOP Conference Series: Materials Science and Engineering 53, no. : 012070.
This paper presents a robust feedback controller design for parametric uncertainty systems via constrained optimization. The proposed controller design employs modern optimization tools (Particle Swarm Optimization and Differential Evolution) in a single objective constrained optimization. The objective of the optimization is to search for a set of robust controller gains such that the stability radius of the closed-loop system is maximized. The constraint of the optimization is a closed-loop poles region which is directly related to the desired time-domain control performance. The proposed controller design is applied to control of pendulum-like systems (gantry crane, flexible joint and inverted pendulum). The results show the robust performance of the designed controller.
Mahmud Iwan Solihin; Rini Akmeliawati; Ari Legowo. Robust controller design for uncertain parametric systems using modern optimization approach. 2011 4th International Conference on Mechatronics (ICOM) 2011, 1 -6.
AMA StyleMahmud Iwan Solihin, Rini Akmeliawati, Ari Legowo. Robust controller design for uncertain parametric systems using modern optimization approach. 2011 4th International Conference on Mechatronics (ICOM). 2011; ():1-6.
Chicago/Turabian StyleMahmud Iwan Solihin; Rini Akmeliawati; Ari Legowo. 2011. "Robust controller design for uncertain parametric systems using modern optimization approach." 2011 4th International Conference on Mechatronics (ICOM) , no. : 1-6.
In this paper, a robust state feedback control design using particle swarm optimisation-based constrained optimisation is proposed. The feedback controller is designed based on state space model of the plant with structured uncertainty such that the closed-loop system would have maximum stability radius. A wedge region is assigned as a constraint to locate desired closed loop poles. The proposed method is applied into design of anti-swing control of an automatic gantry crane experiment. A comparison with that of LQR-based controller is made. The result shows that the proposed method effectively locates the closed loop poles within the prescribed wedge region and its robust performance is guaranteed.
Mahmud Iwan Solihin; Rini Akmeliawati; Ari Legowo. Robust feedback control design using PSO-based optimisation: a case study in gantry crane control. International Journal of Mechatronics and Automation 2011, 1, 121 .
AMA StyleMahmud Iwan Solihin, Rini Akmeliawati, Ari Legowo. Robust feedback control design using PSO-based optimisation: a case study in gantry crane control. International Journal of Mechatronics and Automation. 2011; 1 (2):121.
Chicago/Turabian StyleMahmud Iwan Solihin; Rini Akmeliawati; Ari Legowo. 2011. "Robust feedback control design using PSO-based optimisation: a case study in gantry crane control." International Journal of Mechatronics and Automation 1, no. 2: 121.
Mahmud I. Solihin; Rini Akmeliawati; Ismaila B. Tijani; Ari Legowo. ROBUST STATE FEEDBACK CONTROL DESIGN VIA PSO-BASED CONSTRAINED OPTIMIZATION. Control and Intelligent Systems 2011, 39, 1 .
AMA StyleMahmud I. Solihin, Rini Akmeliawati, Ismaila B. Tijani, Ari Legowo. ROBUST STATE FEEDBACK CONTROL DESIGN VIA PSO-BASED CONSTRAINED OPTIMIZATION. Control and Intelligent Systems. 2011; 39 (3):1.
Chicago/Turabian StyleMahmud I. Solihin; Rini Akmeliawati; Ismaila B. Tijani; Ari Legowo. 2011. "ROBUST STATE FEEDBACK CONTROL DESIGN VIA PSO-BASED CONSTRAINED OPTIMIZATION." Control and Intelligent Systems 39, no. 3: 1.
Computational intelligence has been successfully applied into many engineering applications including control engineering problems. In this paper, a robust state feedback control design via constrained optimization based on Differential Evolution (DE) is proposed. The feedback controller is designed based on state space model of the plant with structured uncertainty such that the closed-loop system would have maximum stability radius. A wedge region is assigned as a constraint to locate desired closed loop poles. The proposed method is applied into design of anti-swing control of an automatic gantry crane. The experimental result is shown and comparison with that of LQ (linear quadratic) optimal controller is made. The proposed method effectively locates the closed loop poles within the prescribed wedge region and its robust performance is guaranteed.
Mahmud Iwan Solihin; Rini Akmeliawati; Riza Muhida; Ari Legowo. Guaranteed robust state feedback controller via constrained optimization using Differential Evolution. 2011 IEEE 7th International Colloquium on Signal Processing and its Applications 2010, 1 -6.
AMA StyleMahmud Iwan Solihin, Rini Akmeliawati, Riza Muhida, Ari Legowo. Guaranteed robust state feedback controller via constrained optimization using Differential Evolution. 2011 IEEE 7th International Colloquium on Signal Processing and its Applications. 2010; ():1-6.
Chicago/Turabian StyleMahmud Iwan Solihin; Rini Akmeliawati; Riza Muhida; Ari Legowo. 2010. "Guaranteed robust state feedback controller via constrained optimization using Differential Evolution." 2011 IEEE 7th International Colloquium on Signal Processing and its Applications , no. : 1-6.