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14 results on '"Kok, Kai Yit"'

2. Anisotropic Median Bilateral Filtering

Author

Kok, Kai Yit, Rajendran, Parvathy, Chaari, Fakher, Series Editor, Haddar, Mohamed, Series Editor, Kwon, Young W., Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Rajendran, Parvathy, editor, Mazlan, Nurul Musfirah, editor, Rahman, Aslina Anjang Ab, editor, Suhadis, Nurulasikin Mohd, editor, Razak, Norizham Abdul, editor, and Abidin, Mohd Shukur Zainol, editor

Published
2020
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9. Proportional-derivative linear quadratic regulator controller design for improved longitudinal motion control of unmanned aerial vehicles

Author

Lim Kah Wee, Parvathy Rajendran, and Kok Kai Yit

Subjects
0209 industrial biotechnology, Computer science, Settling time, Linear model, Aerospace Engineering, PID controller, Control engineering, 02 engineering and technology, Linear-quadratic regulator, Motion control, 020901 industrial engineering & automation, Control theory, 0202 electrical engineering, electronic engineering, information engineering, Overshoot (signal), 020201 artificial intelligence & image processing, Micro air vehicle, MATLAB, computer, computer.programming_language
Abstract

This study investigates the longitudinal motion control of unmanned aerial vehicles through a simulation in MATLAB. The linear model of an unmanned aerial vehicle is applied to controllers to explicate the longitudinal motion of the unmanned aerial vehicle. The ideal performance for an unmanned aerial vehicle is to achieve the desired response instantly with 100% precision. However, currently available controllers need further improvements. Thus, a proportional-derivative linear quadratic regulator controller is developed and compared with a proportional-integral-derivative controller, a linear quadratic regulator controller, and a proportional linear quadratic regulator controller. The proportional-derivative linear quadratic regulator controller enhances the response of the system by reducing settling time by more than 95% compared with other available controllers. Additionally, the proportional-derivative linear quadratic regulator improves the root mean square error by almost 50% compared with the proportional linear quadratic regulator controller and improves rise time by almost 96% with reasonable overshoot.

Published
2016

10. Enhanced Longitudinal Motion Control of UAV Simulation by Using P-LQR Method

Author

Kok Kai Yit and Parvathy Rajendran

Subjects
Engineering, Control theory, business.industry, Control system, Linear model, Open-loop controller, Aerospace Engineering, PID controller, Control engineering, business, Motion control, Motion (physics)
Abstract

This paper describes studies the longitudinal motion control of unmanned aerial vehicles (UAVs) by using a proportional-integral-derivative (PID) controller, linear-quadratic-regulator (LQR) controller, and P-LQR controller. The non-linear model of the motion is changed into a linear model and is implemented in the controllers to elucidate the longitudinal motion of UAVs. The control performance of the aircraft improves when the UAV reaches the desired response instantaneously and precisely. However, the performance of currently available controllers is not ideal, and a 10% improvement in controller performance can lead to a significant effect. Thus, the P-LQR controller is developed. This controller significantly improves the response times of the control system by at least 38.55% compared with other existing controllers. Hence, an alternative longitudinal motion control for UAVs has been proposed.

Published
2015

12. THE OPTIMIZATION OF A GENETIC ALGORITHM FOR UNMANNED AERIAL VEHICLE PATH PLANNING.

Author

Rajendran, Parvathy and Kok, Kai Yit

Subjects
GENETIC algorithms, DRONE aircraft, EVOLUTIONARY algorithms, MONTE Carlo method, MUTATIONS (Algebra)
Abstract

Genetic algorithm has been widely used in numerous fields, including in solving structural optimization problems, financial decision problems, and docking of flexible ligands, among others. Recently, researchers have developed significant interest in applying genetic algorithm in unmanned aerial vehicle path planning. Despite the advantages of genetic algorithm, several parameter inputs are required before using this algorithm. They include waypoint, population size, crossover rate, and mutation rate. The performance of this algorithm is dependent on these parameter settings. Thus, parameter optimization is performed on this algorithm to skip the tuning parameter process during unmanned aerial vehicle path planning. Results show that truncation selection at 20% is highly recommended for genetic algorithm path planning application because of its low average path and computational costs. In addition, a population size of 40 is suitable in unmanned aerial vehicle path planning. Last but not least, the optimum mutation rate of 10% is recommended based on the average path and computational cost for this algorithm. [ABSTRACT FROM AUTHOR]

Published
2017

14. Proportional-derivative linear quadratic regulator controller design for improved longitudinal motion control of unmanned aerial vehicles.

Author

Kok Kai Yit, Rajendran, Parvathy, and Lim Kah Wee

Subjects
*DRONE aircraft, *STANDARD deviations, *SIMULATION methods & models, *DERIVATIVES (Mathematics), *VEHICLE design & construction
Abstract

This study investigates the longitudinal motion control of unmanned aerial vehicles through a simulation in MATLAB. The linear model of an unmanned aerial vehicle is applied to controllers to explicate the longitudinal motion of the unmanned aerial vehicle. The ideal performance for an unmanned aerial vehicle is to achieve the desired response instantly with 100% precision. However, currently available controllers need further improvements. Thus, a proportional-derivative linear quadratic regulator controller is developed and compared with a proportional-integral-derivative controller, a linear quadratic regulator controller, and a proportional linear quadratic regulator controller. The proportional-derivative linear quadratic regulator controller enhances the response of the system by reducing settling time by more than 95% compared with other available controllers. Additionally, the proportional-derivative linear quadratic regulator improves the root mean square error by almost 50% compared with the proportional linear quadratic regulator controller and improves rise time by almost 96% with reasonable overshoot. [ABSTRACT FROM AUTHOR]

Published
2016
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