Syafiq Fauzi Kamarulzaman

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A learning based control system for rapid position control of aerial hovering vehicles is proposed. An aerial hovering vehicle uses angular orientation to accelerate during position control where target angle is preserve to produce acceleration. By arranging target angle, the acceleration and deceleration during position control can be configured, thus able(More)
Multi-tasking in actions help humans produce actions that satisfy the need of multiple purposes. Even though humans may apply multi-tasking when producing actions, a control device mainly produces a control action that can only satisfies a single task. In this research, a method of Learning Control that utilizes compound function in developing and applying(More)
Knowledge acquisition is important in order to build a knowledge based system. One of the methods used in acquiring knowledge is reinforcement learning. Reinforcement learning is commonly defined as a try and error style learning that occurred in episodes. This is difficult to ensure a real control object safety condition since a control object is(More)
Aerial hovering vehicles represent application of non-linear devices in real environment. Controls of such devices are difficult due to instability in certain states of operation. Operating such device requires skills, and such knowledge of skills are even hard to develop as autonomous control system. In this research, a Compound Learning Control System for(More)
A learning based control system which can consider control-interfering-constraints is proposed. Reinforcement learning is applied into the system to make it possible to learn to control upon achieving its control objective. Constraints could exist whether in the system manipulate-able parameter or even in non-manipulate-able parameters as in a non-linear(More)
Moth-flame Optimization (MFO) algorithm is a relatively new optimization algorithm which is classified as Swarm Intelligence (SI). It is inspired by unique behavior of moths in nature. Despite its young age, this algorithm has been proven to be able to address many optimization problems. With respect to that matter, this work introduces a new hybrid(More)
A safe and reliable control operation can be difficult due to limitations in operator’s skills. A self-developing control system could help assist or even replaces the operators in providing the required control operations. However, the self-developing control system is lack of flexibility in determining the necessary control option in multiple conditions(More)
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