Sharifah Yuslinda Syed Hussien

Optimal tuning of PID+PD controller by PFS for Gantry Crane System

This paper presents a combination of the Priority Fitness Scheme (PFS) and optimization techniques to find the optimal performances of the Gantry Crane System. Control algorithm that based on the PFS will be designed and used as fitness function in PSO and BPSO. PFS are prioritized based on Steady State Error (SSE), Overshoot (OS) and Settling Time (Ts) according to the requirements. The system model is derived using the Lagrange equation and PID+PD controller is developed for positioning and oscillation control. System responses, including trolley displacement and payload oscillation are observed and analyzed. It is expected the optimal load transfers offer significant time saving with limited swing and smooth motions via PFPSO and PFBPSO.

PSO-tuned PID controller for coupled tank system via priority-based fitness scheme

The industrial applications of Coupled Tank System (CTS) are widely used especially in chemical process industries. The overall process is require liquids to be pumped, stored in the tank and pumped again to another tank. Nevertheless, the level of liquid in tank need to be controlled and flow between two tanks must be regulated. This paper presents development of an optimal PID controller for controlling the desired liquid level of the CTS. Two method of Particle Swarm Optimization (PSO) algorithm will be tested in optimizing the PID controller parameters. These two methods of PSO are standard Particle Swarm Optimization (PSO) and Priority-based Fitness Scheme in Particle Swarm Optimization (PFPSO). Simulation is conducted within Matlab environment to verify the performance of the system in terms of settling time (Ts), steady state error (SSE) and overshoot (OS). It has been demonstrated that implementation of PSO via Priority-based Fitness Scheme (PFPSO) for this system is potential technique to control...

Motion control of nonlinear gantry crane system via priority-based fitness scheme in firefly algorithm

Advanced manufacturing technology made Gantry Crane System (GCS) is one of the suitable heavy machinery transporters and frequently employed in handling with huge materials. The interconnection of trolley movement and payload oscillation has a technical impact which needs to be considered. Once the trolley moves to the desired position with high speed, this will induce undesirable’s payload oscillation. This frequent unavoidable load swing causes an efficiency drop, load damages and even accidents. In this paper, a new control strategy of Firefly Algorithm (FA) will be developed to obtain five optimal controller parameters (PID and PD) via Priority-based Fitness Scheme (PFS). Combinations of these five parameters are utilized for controlling trolley movement and minimizing the angle of payload oscillation. This PFS is prioritized based on steady-state error (SSE), overshoot (OS) and settling time (Ts) according to the needs and circumstances. Lagrange equation will be chosen for modeling and simulation wi...

Robustness analysis for PID controller optimized using PFPSO for underactuated gantry crane system

Gantry Crane System is widely used for material transportation. In this system, uncontrolled oscillation always be found during the moving process. This problem may extend the carrying time and cause safety problem. In this paper, it presents a method for controlling a Gantry Crane System based on Proportional-Integral-Derivative (PID) controller strategy. A combination of the Priority Fitness Scheme and Particle Swarm Optimization (PFPSO) is used to optimize the parameters of PID and PD controller (KP, KI, KD, KPS and KDS). A disturbance rejection control technique in which PID controller is employed to control accurately and robustly the trolley along a desired position with the minimize payload oscillation. Results from the simulation study clearly show that PID controller is a robust controller as a disturbance rejection and able to move the trolley to a desired position with minimize payload oscillation.