Li Yongyuan

Off-line self-scheduled robust predictive tracking control of linear parameter-varying systems

This paper presents a novel robust model predictive control (RMPC) method for a class of plants with fast time-varying parameters, strong uncertainty, and large operating envelope, which means the states of the plants vary widely. First, a linear parameter-varying model is built to describe model uncertainty and the large envelope. The model is of polytopic form augmented with integrals of tracking errors; the uncertainty of the model vertices is considered. Second, a set of RMPC controllers are designed for each polytope vertex sharing the same asymptotic stable invariant set. During the design, an additional stability constraint should be satisfied. With the additional constraint, global robust stability can be proven with Lyapunov theory. Lastly, a sample application of Rockwell Space Shuttles attitude controller is provided. Simulation results reveal that the tracking error of off-line self-scheduled RMPC controller is smaller than the RMPC controller, and it also shows a convergence trend, while the RMPC controllers does not.

An on-board profile-planning entry guidance

This paper presents an on-board profile-planning entry guidance scheme that enhances the safety and flexibility of entry vehicle. The profile is generated and corrected on-board to meet the terminal requirements and entry trajectory constraints. A linearized feedback tracking law is applied to track the reference profile with a nominal angle-of-attack, which is prescribed in consideration of system constraints and mission requirements. Compared to other on-board entry guidance, the on-board profile-tracking entry guidance focuses more on entry safety, wide mission ranges and low computational complexity. Additionally, Monte-Carlo simulation results are presented to demonstrate the validity and robustness of the algorithm.

Trajectory Optimization and Analysis for Reusable Launch Vehicles

According to the disadvantages of indirect method for trajectory optimization, that initial value the for conjugate variables are highly sensitive and can not obtain the global optimal solution, this paper introduced hybrid genetic algorithm to search initial value of conjugate variables, solved equations to obtain the track of Reusable Launch Vehicles at unpowered gliding phase. In the optimization process, the author takes the constraints of heating rate, dynamic pressure and overload into consideration, and optimizes the trajectory of under different initial factors. Numerical simulations confirm the applicability of the presented algorithm. Considering practical applications, some typical Reusable Launch Vehicles gliding trajectory are optimized. The discussion of the numerical simulations gives some valuable opinions in practical applications.