Nur Asmiza Selamat

Optimal Performance of a Nonlinear Gantry Crane System via Priority-based Fitness Scheme in Binary PSO Algorithm

This paper presents development of an optimal PID and PD controllers for controlling the nonlinear gantry crane system. The proposed Binary Particle Swarm Optimization (BPSO) algorithm that uses Priority-based Fitness Scheme is adopted in obtaining five optimal controller gains. The optimal gains are tested on a control structure that combines PID and PD controllers to examine system responses including trolley displacement and payload oscillation. The dynamic model of gantry crane system is derived using Lagrange equation. Simulation is conducted within Matlab environment to verify the performance of system in terms of settling time (Ts), steady state error (SSE) and overshoot (OS). This proposed technique demonstrates that implementation of Priority-based Fitness Scheme in BPSO is effective and able to move the trolley as fast as possible to the various desired position.

Comparison of LQR and PID controller tuning using PSO for Coupled Tank System

Coupled Tank System is one of the widely used applications in industries. Like other process control, it require suitable controller to obtain the good system performances. Hence, this paper presents the study of Coupled Tank System using LQR and PID controller. Both controller parameters are tuned using Single-Objective Particle Swarm Optimization (PSO). The performance of the system is compared based on the transient response in term of of Rise Time (Tr), Settling Time (Ts), Steady State Error (ess) and Overshoot (OS). Simulation is conducted within MATLAB environment to verify the performances of the system. The result shows that both controller can be tuned using PSO, while LQR controller give slightly better results compared to PID controller.

Battery Parameters Identification Analysis Using Periodogram

Batteries are essential components of most electrical devices and one of the most important parameters in batteries is storage capacity. It represents the maximum amount of energy that can be extracted from the battery under certain specified condition. This paper presents the analysis of charging and discharging battery signal using periodogram. The periodogram converts waveform data from the time domain into the frequency domain and represents the distribution of the signal power over frequency. This analysis focuses on four types of batteries which are lead-acid (LA), lithium-ion (Li-ion), nickel-cadmium (Ni-Cd) and nickel-metal-hydride (Ni-MH). This paper used battery model from MATLAB/SIMULINK software and the nominal voltage of each battery is 6 and 12V while the capacity is 10 and 20Ah, respectively. The analysis is done and the result shows that varying capacity produce different power at a frequency and voltage at DC component.

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...

Lead Acid Battery Analysis Using Spectogram

Renewable energy is an alternative option that can be substituted for future energy demand. Many type of battery are used in commerce to propel portable power and this makes the task of selecting the right battery type is crucial. This paper presents the analysis of voltage charging and discharging for lead acid battery using time-frequency distribution (TFD) which is spectrogram. Spectogram technique is used to represent the signals in the time-frequency representation (TFR). The parameter of a signal such as instantaneous root mean square (RMS) voltage, direct current voltage (VDC) and alternating current voltage (VAC) are estimated from the TFR to identify the signal characteristics. This analysis, focus on lead-acid battery with nominal battery voltage of 6 and 12V and storage capacity from 5 until 50Ah. The battery is a model using MATLAB/SIMULINK and the results show that spectrogram technique is capable to identify and determine the signal characteristic of Lead Acid battery.