A diagonal recurrent neural network-based hybrid direct adaptiveSPSA control system |
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Authors: | Ji XD Familoni BO |
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Affiliation: | Dept. of Electr. Eng., Memphis Univ., TN; |
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Abstract: | A direct adaptive simultaneous perturbation stochastic approximation (DA SPSA) control system with a diagonal recurrent neural network (DRNN) controller is proposed. The DA SPSA control system with DRNN has simpler architecture and parameter vector size that is smaller than a feedforward neural network (FNN) controller. The simulation results show that it has a faster convergence rate than FNN controller. It results in a steady-state error and is sensitive to SPSA coefficients and termination condition. For trajectory control purpose, a hybrid control system scheme with a conventional PID controller is proposed |
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