Sun Mingwei

Optimization of periodic optimal cruise for a hypersionic vehicle

Raising the fuel efficiency per mile is a crucial criterion of trajectory design for a hypersonic vehicle. This paper presents several numerical methods to such problem based on HL-20 model. This is a typical Optimal Periodic Control (OPC) problem. By simplifying the HL-20 model, the new high-fidelity guess is given to obtain a more reliable optimal solution. Furthermore, the optimal solutions are obtained by applying the software-SNOPT and IMSL to solve the nonlinear optimization problems with enough constraints and then the contrast between the obtained results is shown by using different auxiliary calculation tools. Actually, the cruising mode with periodic altitude and velocity is more fuel-efficient than the previous results also by the methods of OPC, thus, better than the traditional one with constant altitude and velocity. Therefore, an improved trajectory can be realized based on the constant optimal mode. The simulation results verify the effectiveness of the method.

A continuous second-order sliding mode guidance against highly maneuverable targets

Conventional proportional navigation or augmented proportional navigation guidance laws are widely used for intercepting maneuverable targets; however, they are effective only in intercepting a target with a constant velocity or a known acceleration. In this paper, a continuous second-order sliding mode guidance law is designed to intercept a highly maneuverable target in connection with the super-twisting algorithm. Meanwhile, the target maneuver information, regarded as unpredictable disturbance, is coped with by an extended state observer (ESO) and then is compensated in the guidance law. In the proposed guidance scheme, no information about target motion is needed. The closed-loop error can be guaranteed to be bounded by using Lyapunov method. The simulation results demonstrate the effectiveness and robustness of the proposed guidance method against a highly maneuverable target.

Recursive algorithm for constrained receding horizon predictive control

This paper recursively obtains the solution of constrained receding-horizon predictive control (CRHPC) in order to avoid inversion of higher-dimensional matrices. This method reduces the calculation load greatly.