A study of the quadratic performance index for a VTOL prefilter model reference attitude control system

For the steering engine fault of ducted fan UAV that may arise during the hovering, designing adaptive controller for attitude control. First, concentrating on modeling of the hovering state of ducted fan UAV, and getting the relationship between steering engine and attitude control. Then analyzing the impact of steering engine fault on the attitude control system basing on the control model. Finally, designing model reference adaptive controller basing on the fault model, so that the ducted fan UAV can maintain good attitude control if steering engine fault occurs during the hovering. Simulation results show that when steering engine fault occurs, the model reference adaptive controller can effectively inhibit the adverse effects brought by steering engine fault, so the attitude control system has strong adaptability and robustness.

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Weighting matrix of quadratic performance index and design method of optimal deadbeat control system

Electrical Engineering in Japan ◽

10.1002/1520-6416(200010)133:1<53::aid-eej6>3.0.co;2-x ◽

2000 ◽

Vol 133 (1) ◽

pp. 53-63

Author(s):

Yuichi Matsushima ◽

Shinichiro Wakamiya ◽

Hiroshi Murata

Keyword(s):

Control System ◽

Performance Index ◽

Design Method ◽

Deadbeat Control ◽

Weighting Matrix ◽

Quadratic Performance Index ◽

Quadratic Performance

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INNOSAT ATTITUDE CONTROL SYSTEM BASED ON ADAPTIVE NEURO-CONTROLLER

Journal of Information and Communication Technology ◽

10.32890/jict.10.2011.8108 ◽

2011 ◽

Author(s):

Siti Maryam Sharun ◽

Mohd Yusoff Mashor ◽

Norhayati Mohd Nazid ◽

Sazali Yaacob ◽

Wan Nurhadani Wan Jaafar

Keyword(s):

Control System ◽

Attitude Control ◽

Reference Model ◽

Operating Conditions ◽

Least Square ◽

Recursive Least Square ◽

Attitude Control System ◽

Model Reference ◽

Mlp Network ◽

Neuro Controller

The current research focuses on the designing of an intelligent controller for the Attitude Control System (ACS) of the Innovative Satellite (InnoSAT). The InnoSAT mission is to demonstrate local innovative space technology amongst the institutions of higher learning in the space sector. In this study, an Adaptive Neuro-controller (ANC) based on the Hybrid Multi Layered Perceptron (HMLP) network has been developed. The Model Reference Adaptive Control (MRAC) system is used as a control scheme to control a time varying systems where the performance specifications are given in terms of a reference model. The Weighted Recursive Least Square (WRLS) algorithm will adjust the controller parameters to minimize error between the plant output and the model reference output. The objective of this paper is to analyse the time response and the tracking performance of the ANC based on the HMLP network and the ANC based on the standard MLP network for controlling an InnoSAT attitude. These controllers have been tested using an InnoSAT model with some variations in operating conditions such as varying gain, measurement noise and disturbance torques. The simulation results indicated that the the ANC based on the HMLP network is adequate to control satellite attitude and give better results than the ANC based on the MLP network.

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Model reference adaptive attitude control for near space hypersonic vehicle with mismatched uncertainties

Transactions of the Institute of Measurement and Control ◽

10.1177/0142331218776713 ◽

2018 ◽

Vol 41 (5) ◽

pp. 1301-1312

Author(s):

Jianguo Guo ◽

Tianbao Zhang ◽

Cheng Cheng ◽

Jun Zhou

Keyword(s):

Control System ◽

Attitude Control ◽

Angular Rate ◽

Hypersonic Vehicle ◽

Control Loop ◽

Attitude Control System ◽

Model Reference ◽

Near Space ◽

Mismatched Uncertainties ◽

Model Reference Adaptive

In this paper, a new model reference adaptive attitude control based on backstepping approach is presented for near space hypersonic vehicle with mismatched uncertainties. Firstly, the attitude dynamic model of near space hypersonic vehicle is divided into two control loops, which is composed of an attitude angle control loop and an attitude angular rate control loop. Secondly, a novel model reference adaptive attitude control approach is proposed by introducing reference model to avoid the calculating expansion problem in backstepping technique. Meanwhile, the reference models for every loop are independently designed to improve the tracking performance. The stability of attitude control system is strictly proven by using Lyapunov stability theory. Finally, the simulation results demonstrate that the attitude control system by applying the proposed method has good stability, dynamic property and strong robustness in the presence of input constraints and parameters perturbation.

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