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A PID-like neural network nonlinear adaptive controller is proposed with the combination of neural network principle and PID controller. The adaptive update law of PID parameters is obtained by resilient back-propagation algorithm with sign, and then the value of learning rate is derived applying discrete Lyapunov direct method to insure control system stability. Finally, based on the simulation software...
Depth parking control is important for the HTPE (HydroThermal Plume Explorer). It aims to have a more accurate parking depth and a less oscillation at the target depth. The plant approaching and motion forecasting model based on RBF neural network is built to self-adjust and approach online motion law of HTPE in ideal circumstance of the sea, and simulate output of given control quantity after an...
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