Optimal Adjustment Control of SISO Nonlinear Systems Based on Multi-Dimensional Taylor Network only by Output Feedback

Abstract

On the basis of the original multi-dimensional Taylor network, the control input item is added to constitute the nonlinear dynamic model, which is used to optimally control SISO nonlinear system only by output feedback without both meeting the Lipschitz condition and needing the state observer or the system disturbance estimation. Parameters of the multi-dimensional network with the control input item are trained by the conjugate gradient method. Through the simulation, it is demonstrated that the multi-dimensional Taylor network used as the optimal SISO nonlinear system regulator is effective.