Particle Swarm Algorithm Sliding Mode Control on Spacecraft's Attitude with Switching Function Method Thorough Error Feedback

Small spacecraft requires capable processors with energy efficiency, low cost and low computational burden while maintaining the output tracking accuracy. This paper presents the extension of work in [1], to enhance the transient performance using particle swarm optimization (PSO) on decaying bounda...

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Bibliographic Details
Published inIOP conference series. Materials Science and Engineering Vol. 705; no. 1; pp. 12039 - 12046
Main Authors Hassrizal, H. B., Rossiter, J. A., Othman, Siti Marhainis, Ayob, M. N.
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.11.2019
Subjects
Algorithms
Attitudes
Boundary layers
chattering
control accuracy
Error feedback
Particle decay
Particle swarm optimization
PSO
Sliding mode control
small spacecraft
SMC
Spacecraft
spacecraft's attitude
Subsystems
Switching
switching function error feedback
Transient performance
Transient response
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Summary:Small spacecraft requires capable processors with energy efficiency, low cost and low computational burden while maintaining the output tracking accuracy. This paper presents the extension of work in [1], to enhance the transient performance using particle swarm optimization (PSO) on decaying boundary layer and switching function thorough error feedback (DBLSF) in Sliding Mode Control (SMC). Generally, SMC is known for having chattering as the main drawback which can introduce wear and tear to moving mechanical parts. As a solution, a DBLSF proposed in [1] and capable of eliminating the chattering in SMC while considering the essential requirements for small spacecraft operation. Then, the extension implemented on spacecraft's attitude, which is one-of-six subsystems in spacecraft, used to orient the spacecraft referred to reference objects and control the dynamics of a spacecraft time-to-time according to the needs. However, the SMC's transient response can be tuned using some coefficients in the SMC algorithm. The parameters in [1] were tuned using outputs observation technique. In this paper, then, an improvement is introduced to optimize the outputs by adding a PSO in the SMC-DBLSF in term of transient performances and accuracy while reducing the chattering permanently.
ISSN:1757-8981
1757-899X
DOI:10.1088/1757-899X/705/1/012039