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Gao Tian
Northwestern Polytechnical University

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An Adaptive Fuzzy Control Method for Spacecrafts Based on T-S Model Wang Qi; Gao Tian; He He
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 11: November 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

A model reference adaptive control method is proposed for uncertain nonlinear characteristics of spacecraft attitude control system. This method combines fuzzy control methodology and nonlinear feedback linearization methodology, which made the closed-loop system stable and the state of fuzzy system track the state of reference model according to the parallel distributed compensation theory and the rational design of the fuzzy state feedback control law. The nonlinear closed-loop system was linearized by selecting fuzzy state feedback parameters and fuzzy membership function. Then an adaptive control law was designed by Lyapunov function. As a result the system can be adaptive to all kinds of parameter uncertainties and robust to modeling inaccuracy and external disturbance. Meanwhile, the simulation results indicate that the control law can quickly guarantee the stability of the spacecraft attitude and be robust to model perturbations and external disturbances. DOI: http://dx.doi.org/10.11591/telkomnika.v11i11.3549
Target Recognition Algorithm Based on BP Networks and Invariant Moments Gao Tian; Wang Qi
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 2: February 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

On the basis of multi-sensor fusion algorithm, a target recognition algorithm based on Back Propagation (BP) neural networks and invariant moments was proposed. Invariant moment takes advantage of overall information of the targets. It has good differentiating effect and high identification technique. On the other hand, BP neural networks not only have the adaptive learning ability, but also are insensitive to imperfection of input mode. Therefore, it has proper classification and extensibility. It is effective for the algorithm based on BP neural networks and invariant moments that decrease the adverse impacts for the images, which are always subject to the changes of imaging distance, direction and position. Simulation results show that the algorithm has strong recognition capability for surface targets from infrared image sensors. DOI: http://dx.doi.org/10.11591/telkomnika.v11i2.2062
Co-Authors He He Wang Qi