Suboptimal Control Theory for Vehicle Attitude Control System Design

2012 ◽  
Vol 466-467 ◽  
pp. 976-980
Author(s):  
Guo Long Fan ◽  
Xiao Geng Liang ◽  
Yong Hua Fan
Keyword(s):  
Control System ◽  
Lyapunov Stability ◽  
Flight Control ◽  
Attitude Control ◽  
Stability Theory ◽  
Deflection Angle ◽  
Lyapunov Stability Theory ◽  
Suboptimal Control ◽  
System Control ◽  
Flight Control System

Base on the Lyapunov stability theory, an improved suboptimal control system scheme is advanced in this paper. Aiming at hypersonic reentry vehicle nonlinear properties of the actuator deflection angle rate and the deflection angle were studied. First, the mathematical model of the control system is established according to the flight control system control scheme. Considering the project realize easy, the flight control system is designed based on suboptimal control of Lyapunov stability theory. In order to close to the optimal control, then the suboptimal control design is improved. Finally the controller is applied to the instances, by analyzing the results confirmed the method is correctly.

Adaptive Attitude Control on Multiple Independently Targeted Reentry Vehicles (MIRV)

2014 ◽  
Vol 494-495 ◽  
pp. 1316-1319
Author(s):  
Xing Yu Chen ◽  
Fan Li ◽  
Jian Hui Zhao ◽  
Zhao Long Fan
Keyword(s):  
Numerical Simulation ◽  
Control System ◽  
Lyapunov Stability ◽  
Attitude Control ◽  
Stability Theory ◽  
Lyapunov Stability Theory ◽  
Adaptive Controller ◽  
Attitude Dynamics ◽  
Dynamics Model ◽  
Simulation Results

Based on the characteristics of releasing loads for many times, the attitude dynamics model of MIRV has established by using the Rodrigues representation, and we proposed a method of indirect multi-model adaptive attitude control. It was proved that the adaptive controller we designed can ensure the control system globally uniformly and bounded stable according to the Lyapunov stability theory, and the effectiveness of the controller was demonstrated by the numerical simulation results.

Modified shuffled frog leaping algorithm for optimization of UAV flight controller

2011 ◽  
Vol 4 (1) ◽  
pp. 25-39 ◽  
Author(s):  
Huangzhong Pu ◽  
Ziyang Zhen ◽  
Daobo Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Control System ◽  
Flight Control ◽  
Attitude Control ◽  
Optimization Method ◽  
Flight Control System ◽  
Shuffled Frog Leaping Algorithm ◽  
Swarm Optimization ◽  
Content Type ◽  
Shuffled Frog Leaping

PurposeAttitude control of unmanned aerial vehicle (UAV) is the purposeful manipulation of controllable external forces to establish a desired attitude, which is inner‐loop of the autonomous flight control system. In the practical applications, classical control methods such as proportional‐integral‐derivative control are usually selected because of simple and high reliability. However, it is usually difficult to select or optimize the control parameters. The purpose of this paper is to investigate an intelligent algorithm based classical controller of UAV.Design/methodology/approachAmong the many intelligent algorithms, shuffled frog leaping algorithm (SFLA) combines the benefits of the genetic‐based memetic algorithm as well as social behavior based particle swarm optimization. SFLA is a population based meta‐heuristic intelligent optimization method inspired by natural memetics. In order to improve the performance of SFLA, a different dividing method of the memeplexes is presented to make their performance balance; moreover, an evolution mechanism of the best frog is introduced to make the algorithm jump out the local optimum. The modified SFLA is applied to the tuning of the proportional coefficients of pitching and rolling channels of UAV flight control system.FindingsSimulation of a UAV control system in which the nonlinear model is obtained by the wind tunnel experiment show the rapid dynamic response and high control precision by using the modified SFLA optimized attitude controller, which is better than that of the original SFLA and particle swarm optimization method.Originality/valueA modification scheme is presented to improve the global searching capability of SFLA. The modified SFLA based intelligent determination method of the UAV flight controller parameters is proposed, in order to improve the attitude control performance of UAV.

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