Design of a Model Predictive Control Flight Control System for a Reusable Launch Vehicle

2003 ◽  
Author(s):  
Piero Miotto ◽  
Robert LePome
Keyword(s):  
Control System ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Flight Control ◽  
Launch Vehicle ◽  
Flight Control System ◽  
Reusable Launch Vehicle ◽  
Control Flight

A Linear Quadratic Integral Design Approach for the Automatic Control System of a Launch Vehicle

2015 ◽  
Vol 772 ◽  
pp. 410-417 ◽  
Author(s):  
Adrian Mihail Stoica ◽  
Cristian Emil Constantinescu ◽  
Silvia Nechita
Keyword(s):  
Control System ◽  
Flight Control ◽  
Launch Vehicle ◽  
Design Approach ◽  
Flight Control System ◽  
Linear Quadratic ◽  
Atmospheric Disturbances ◽  
Modeling Uncertainties ◽  
Quadratic Integral ◽  
The Stability

This paper presents a design approach for the automatic flight control system of a launch vehicle using a linear quadratic integral technique together with a fixed gain Kalman filter. Its purpose is to analyse the stability and tracking robustness performances of the control system designed via this approach when atmospheric disturbances, modeling uncertainties and structural flexible modes of the launcher are taken into account.

scholarly journals Nonlinear Predictive Control of Mass Moment Aerospace Vehicles Based on Ant Colony Genetic Algorithm Optimization

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaoyu Zhang ◽  
Peng Li ◽  
Dexin Xu ◽  
Ben Mao ◽  
Kunpeng He
Keyword(s):  
Genetic Algorithm ◽  
Control System ◽  
Predictive Control ◽  
Flight Control ◽  
Nonlinear Dynamical System ◽  
Ant Colony ◽  
Flight Control System ◽  
Aerospace Vehicles ◽  
Nonlinear Predictive Control ◽  
Mass Moment

Based on the mathematical model of the mass moment aerospace vehicles (MMAV), a coupled nonlinear dynamical system is established by rational simplification. The flight control system of MMAV is designed via utilizing nonlinear predictive control (NPC) approach. Aiming at the parameters of NPC is generally used the trial-and-error method to optimize and design, a novel kind of NPC parameters optimization strategy based on ant colony genetic algorithm (ACGA) is proposed in this paper. The method for setting NPC parameters with ACA in which the routes of ants are optimized by the genetic algorithm (GA) is derived. And then, a detailed realized process of this method is also presented. Furthermore, this optimization algorithm of the NPC parameters is applied to the flight control system of MMAV. The simulation results show that the system not only meets the demands of time-response specifications but also has excellent robustness.

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