Magnetorheological valve offers several advantages such as controllability, small in size and no moving part during operation. Thus, many researchers are working on developing an actuator based on this valve. However, this actuator required feedback system to improve it precision. This research is focusing on developing of machine vision based positioning system for MRF actuator. Image processing algorithms coded using Matlab software and directly connect to MRF valve controller. As a result, the system shows a fast response with processing time only 0.6 millisecond, system resolution is 0.1 millimeter and finally repeatability is 0.01. As a conclusion, the machine vision system are applicable for MRF actuator positioning system. This study is significant in order to developing a low cost and robust positioning system.
Complexity in modeling an underwater thruster analytically, leave system identification approached a good option on developing accurate dynamic model for underwater thruster. Nonlinearity of the system due to fluid solid interaction such as, hydrodynamic force hitting the propeller blade make the system identification became a trivial task. This paper presents nonlinear modeling and identification of the underwater thruster from input–output measurement. The system was fully submerged, and current was varied as the input and the output thrust was measured using load cell. Nonlinear Hammerstein method is chosen for identification of the system. The results are numerically and graphically presented. The nonlinear system identification with second order linear dynamics gave the best result, where is the model, can fit up to 82 % of the real response of the thrust. The finding of the model can be utilized in the future to improve underwater vehicle performance by developing optimum control algorithm.
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