Prosthetics hand is replacement of original hands that lose or damage because of war, trauma, accident or congenital anomalies. However, problems often occur on a prosthetics hand when dealing with the control capabilities and devising functional. Thus, an advanced mechanical design with control approach is required to improve the performance in terms of quality control in prosthetics hand and also enhance existing capabilities to the optimum level. This paper aims to develop a functional prosthetics hand at upper limb, which will focus on position of human hand particularly using the movement of finger instructions. In this paper, an intelligent controller, Fuzzy with Proportional-Integral-Derivative (Fuzzy-PID) controller is proposed to realize accurate force control with high performance. The performance of prosthetics hand model controlled by Fuzzy-PID controller is outperform the conventional PID controller and Fuzzy controller, where the improvement of the transient response and steady state error is achieved. Performance comparison of three different controllers has been presented through these evaluation process. 

<span>Underwater remotely operated vehicle (ROV) is important in underwater industries as well as for safety purposes. It can dive deeper than humans and can replace humans in a hazardous underwater environment. ROV depth control is difficult due to the hydrodynamic of the ROV itself and the underwater environment. Overshoot in the depth control may cause damage to the ROV and its investigated location. This paper presenting a new tuning approach of single input fuzzy logic controller (SIFLC) with gradient descent algorithm (GDA) and particle swarm optimization (PSO) implementation for ROV depth control. The ROV was modeled using system identification to simulate the depth system. Proportional integral derivative (PID) controller was applied to the model as a basic controller. SIFLC was then implemented in three tuning approaches which are heuristic, GDA, and PSO. The output transient was simulated using MATLAB Simulink and the percent overshoot (OS), time rise (Tr), and settling time (Ts) of the systems without and with controllers were compared and analyzed. The result shows that SIFLC GDA output has the best transient result at 0.1021% (OS), 0.7992s (Tr), and 0.9790s (Ts).</span>

Over the recent years, there has been a huge interest towards Electroencephalogram (EEG) based brain computer interface (BCI) system. BCI system enables the extraction of meaningful information directly from the human brain via suitable signal processing and machine learning method and thus, many researches have applied this technology towards rehabilitation and assistive robotics. Such application is important towards improving the lives of people with motor diseases such as Amytrophic Lateral Scelorosis (ALS) disease or people with quadriplegia/tetraplegia. This paper introduces features extraction method based on the Fast Fourier Transform (FFT) with logarithmic bin-ning for rapid classification using Support Vector Machine (SVM) algorithm, with an application towards a BCI system with a shared con-trol scheme. In general, subjects wearing a single channel EEG electrode located at F8 (10-20 international standards) were required to syn-chronously imagine a star rotating and mind relaxation at specific time and direction. The imagination of a star would trigger a mobile robot suggesting that there exists a target object at certain direction. Based on the proposed algorithm, we showed that our algorithm can distin-guish between mind relaxation and mental star rotation with up to 80% accuracy from the single channel EEG signals.

Recently, Vector Control also known as Field Oriented Control used in AC induction motor drive provides us of a way to control AC induction motor similar to that of a DC motor. This objective is achieved by transforming the time-varying, difficult to control stator currents into a simple time-invariant system by means of coordinate transformations. This in turn provides us with a systematical way towards designing a controller using classical control or modern state-space design methodologies. Purpose of this research is to use the latter in designing a controller towards regulating current responsible for torque response. A non-linear model of the AC Induction Motor is modeled in the rotating (d,q) reference frame for the control purposes. Then, a state feedback linearization controller was design based on the idea of “exact linearization” to transform the non-linear model into linear state-space model, thus enabling controller design using modern state-space approach. A Linear Quadratic optimal controller and Feedback+Feedforward controller is then designed and applied to the linearized induction motor model. For comparison purposes a classical P/PI controller was also designed. Simulation is then carried out using MATLAB/SIMULINK software and results shows good current regulation by controller design using modern state –space methodologies.

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Remotely Operated Vehicle (ROV) is an important vehicle to do underwater task. The uncertainty environment of underwater make it harder for ROV to maneuver and hold position at certain depth. Research on ROV controller for holding position had been conducted. Proportional, Integral and Derivative (PID), Fuzzy Logic Controller (FLC) and Single Input Fuzzy Logic Controller (SIFLC) was designed and compared. This paper discusses the modelling of developed ROV and tuning the SIFLC to get the best transient response. Steady state error (SSE), percent overshoot (%OS), time rise (Tr) and settling time (Ts) were analyzed to select the best controller.The result shows ROV depth can be controlled more precisely using SIFLC with 1.5 %OS, 11.5s Ts and 7.06s Tr.

This project aims at proposing an innovative way to implement the concept of fuzzy logic to an ABS model. The implementation of this project was conducted using simulation of ABS which is a combination from vehicle speed, wheel speed and slip through MATLAB Simulink software. By implementing fuzzy logic to the ABS system, the fuzzy logic can facilitate in improving the ABS abilities. The ABS model is developed and fuzzy logic controller is implemented to the model. The performance of the Fuzzy ABS is analyzed. The result shows that the fuzzy logic controller can facilitates the performance of the ABS by reducing the stopping time and mai ntaining the slip value near to 0.2.

This paper aim to provide a basic fundamental knowledge for researchers on underwater remotely operated vehicle (ROV) system and current trend of ROV controller. The vehicle is used for exploration, investigation or inspection of underwater environment as a replacement of human due to human limitation. It can dive deeper than human and can be manoeuvred into hazard environment. In this paper, the basic development and classification of ROV is discussed. The modelling of ROV, manoeuvrability and controller designed by researchers since 1990 also being discussed. It is expected that this paper will help readers in doing research on the controller of ROV.