Luo Jianjun

Applying Genetic Algorithm to Optimization Parameters of Missile Control System

Proportion integral differential(PID) control is widely used for missile control systems, but it is difficult to achieve parameter optimization because the three control parameters Kp, Ki, Kd are empirically selected. Genetic algorithm is a search algorithm that is based on natural selection and genetics principles and randomly generates the initial population of the PID control parameters according to the calculation of selection, crossover and mutation, thus optimizing the control parameters. In this paper, a missile attitude control system in longitudinal channel is taken as an example, and the minimum time integral of error absolute value is chosen as the performance assessment index. The genetic algorithm is used to optimize the parameters of the attitude angle control system and obtain their optimal solutions.

R-bar guidance strategy design for the final translation of space rendezvous and docking

Aimed at the problem of forced motion along Line of sight of final translation phase of space rendezvous and docking, straight line guidance algorithms of R-bar based on Clohessy-Wiltshire equation are investigated. The guidance laws using impulsive propulsion and finite thrust are designed, and the guidance conditions for optimal-fuel are obtained. Numerical simulation is done to illustrate and analyze the guidance algorithms, and simulation results show that the proposed approaches are simple and efficient, and the guidance law using impulsive thrust costs less fuel and time than that using finite thrust.