This study presents the implementation of adaptive notch filter (ANF) as reference signal extraction for shunt active power filter (APF) in indirect current control (ICC) and direct current control (DCC) modes for three phase system. The ANF functions to filter the signal that inputted to it by producing a fundamental signal and harmonics signal. The advantage of applying the ANF algorithm is based on its simple design that giving the ANF advantages to be utilize in microcontroller. The performance of the ANF is validated though MATLAB simulation in ICC dan DCC configurations. Based on the simulation results, the ANF is capable to work efficiently for both ICC and DCC modes, but in term of efficiency, the ICC mode is clearly showing a better harmonics mitigation result. Base on the result also it shown that the ANF is capable of mitigate the harmonics below the standard required by the IEEE 519-92. The application of ANF is useful to be applied due to its simple design and filtering method.
Industrial tank system is widely used in consumer liquid processing and chemical processing industry. In liquid-based product manufacturing system, one of the main components consists of an industrial tank. This paper explores the applications of two swarm intelligence algorithms in optimizing the PID controller parameters. These swarm intelligence algorithms are Particle Swarm Optimization (PSO) and Firefly Algorithm (FA). Each agent of the swarm intelligence will represent a possible solution of the problem where each dimension corresponds to the PID controllers parameters. Result obtained shows that there are potential in improving these algorithms to replace the conventional way of obtaining PID controllers parameters
<span lang="EN-US">Multilevel inverter (MLI) becomes more significant in Active Power Filter (APF) application due to capability to its produce low harmonic output current in which at the same time improving performance of APF. Among the topologies of MLI, Cascaded H-Bridge (CHB) is the most popular topology with less power devices requirement and simple design. MLI CHB is also capable to produce possible output voltage at twice of the number of DC source which in this case of APF is the best suited topology to replace with the conventional six -step inverter. This paper presents the performance of three- phase three-wire CHB MLI used in Shunt Active Power Filter (SAPF) based on Direct Current Control (DCC) and Indirect Current Control (ICC) schemes. Both schemes are developed and verified in MATLAB/Simulink. The simulation results show that both current control algorithms are capable to mitigate load current with Total Harmonic Distortion below than the permissible value based on IEEE 519 standard.</span>
The price of the wood according to the type of wood. Classification of the woods can be done by studying its texture. This paper introduces Fuzzy k Nearest Neighbor to classify 25 types of wood. The woods images have been taken from the Wood Database of the Centre for Artificial Intelligence & Robotics, Universiti Teknologi Malaysia. The features of wood images are extracted using Local Binary Pattern. The results of this paper shows improvement in wood classification compare to the previous literature.
In this paper, Robust Composite Nonlinear Feedback (CNF) was implemented on Active Front Steering (AFS) vehicle system for yaw stability control. In this control system, the main objective is to get excellent transient response of vehicle yaw rate and at the same time resist to side wind disturbance. To cater unknown constant disturbance, non-integral function for Robust CNF version is used. Meanwhile for vehicle model, 7 degree of freedom vehicle body with Pacejka Tire formula model for typical passenger car is used to simulate controlled vehicle. The computer simulation by Matlab software is performed to evaluate the system performance in J-Turn and Single sine steer with magnitude from 1 to 3.1 degree with additional 400 Nm external side wind disturbance. By using typical Proportional Integration and Derivative (PID) control auto-tuned by Matlab as comparison, the new designed controller demonstrates higher capability to track reference signal faster and having minimal tracking error during disturbance occur where having less than 0.01 degree compared 0.22 degree by PID. The Robust CNF based designed control system is able to compensate disturbance effect efficiently and also has super-fast tracking as classical CNF.
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