This paper presents a searching method for parameters optimization of a third-order sampled-data tracker, which is called filter. The filter not only can track the position, velocity and acceleration signal, but also can reduce the measurement noise. In order to design an optimal third-order tracker, we propose utilizing a real-coded genetic algorithm (GA) to search the suitable parameter values for the filter. The experimental results indicate the optimized filter based on GA can provide the approximate position, velocity and acceleration signal and simultaneously decrease the noise disturbance as much as possible.
The 3 filter based on the Kalman-like estimation scheme has been recognized as a outstanding tool for estimating the position and velocity signals of moving objects. Nevertheless, the performance of estimation heavily depends on the parameters and . In general, the choice of parameters is a trade-off optimization problem between the tracking accuracy and noise reduction capability. In order to obtain the suitable design of 3 filter for some specifications, a combined fuzzy logic and evolutionary optimization method is proposed for determining the parameter values. The simulation results are employed to illustrate the developed 3 filter which is capable of tracking the desired signals accurately and, at the same time, reducing the noise disturbance remarkably.
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