Sparse successive approximation for nonlinear H2 and H∞ optimal control problems under residual errors
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Zhong Wang1, Yan Li1, Yuqing Qiu1
1Department of Navigation, Guidance, and Control, Northwestern Polytechnical University, Xi'an, 710129, PR China.
Abstract:
Successive approximation techniques are effective approaches to solve the Hamilton-Jacobi-Bellman (HJB)/Hamilton-Jacobi-Isaacs (HJI) equations in nonlinear H2 and H∞ optimal control problems (OCPs), but residual errors in the solving process may destroy its convergence property, and related numerical methods also pose computational burden and difficulties. In this paper, the HJB/HJI partial differential equations (PDEs) for infinite-horizon nonlinear H2 and H∞ OCPs are handled in a unified formulation, and a sparse successive approximation method is proposed. Taking advantage of successive approximation techniques, the nonlinear HJB/HJI PDEs are transformed into sequences of easily solvable linear PDEs, to which the solutions can be computed point-wise by handling simple initial value problems. Extra constraints are also incorporated in the solving process to guarantee the convergence under residual errors. The sparse grid based collocation points and basis functions are then employed to enable efficient numerical implementation. The performance of the proposed method is also numerically demonstrated in simulations.
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