Prediction based DC servo control system in robotic arm

Two approaches to the accurate trajectory control of a robotic arm with payload are presented. One is the fixed parameter algorithm and the other is the self-tuning algorithm. Both methods use an ARMA (autoregressive moving average) process model. In the first method the model is fixed and in the second the model parameters are tuned online. These techniques are based on long-range position prediction and can easily be implemented in real-time systems because of their simplicity. Simulation results of a one-degree-of-freedom DC motor servo system indicate that these algorithms, especially the self-tuning one, are effective for position control of a robotic arm.<
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