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Amar Faiz Zainal Abidin

Researcher at Universiti Teknikal Malaysia Melaka

Publications -  73
Citations -  639

Amar Faiz Zainal Abidin is an academic researcher from Universiti Teknikal Malaysia Melaka. The author has contributed to research in topics: Particle swarm optimization & Control theory. The author has an hindex of 13, co-authored 72 publications receiving 512 citations. Previous affiliations of Amar Faiz Zainal Abidin include Universiti Teknologi Malaysia.

Papers
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Proceedings ArticleDOI

PSO-tuned PID controller for a nonlinear gantry crane system

TL;DR: Development of an optimal PID controller for control of a nonlinear gantry crane system is presented and it is demonstrated that the controller is effective to move the trolley as fast as possible to the desired position with low payload oscillation technique.
Journal ArticleDOI

Adaptive modified Stanley controller with fuzzy supervisory system for trajectory tracking of an autonomous armoured vehicle

TL;DR: The development of an adaptive controller with fuzzy supervisory system for trajectory tracking control of an autonomous armoured vehicle is presented and experimental results for the controller are presented to evaluate the proposed controller.
Journal ArticleDOI

Modelling and PSO fine-tuned PID control of quadrotor UAV

TL;DR: In this article, a nonlinear dynamics model of x-configuration quadrotor using Newton-Euler modelling technique is described, and an individual PID controller for each roll, pitch, yaw and z where 12 parameters consist of kp, ki, and kd are fine-tuned using particle swarm optimization algorithms.
Proceedings ArticleDOI

A Particle Swarm Optimization Approach to Robotic Drill Route Optimization

TL;DR: A new model that implements Particle Swarm Optimization (PSO) in order to find optimized routing path when using the PCB Robotic Drill is proposed and is capable to find the shortest path for the robot to complete its task.
Journal ArticleDOI

Dynamic Behaviour of a Nonlinear Gantry Crane System

TL;DR: In this paper, a nonlinear Gantry Crane System (GCS) is derived using Lagrange equation and various system parameters of the system are tested to observe the actual behaviour of the dynamic model system.