Data-Driven for Affine Nonlinear System via Adaptive Control and LDI technology

This paper investigates a novel optimal control scheme for affine nonlinear systems. With the complexity of Hamilton-Jacobi-Bellman function and the linear differential inclusion based on neural network model is used to linearize the affine system, Meanwhile, a data-driven policy iterative algorithm is proposed to solve the relevant optimal solution. Finally, a simulation example is given to demonstrates the feasibility and applicability of the designed algorithm.