Nonlinear Attitude Control of Satellite Using Optimal Adaptive and Fuzzy Control Methods

Navabi, M.; Hashkavaei, Nazanin Safaei

doi:10.1109/cfis49607.2020.9238733

Cited by 1 publication

(1 citation statement)

References 26 publications

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“…To this date, a number of efficient control approaches have been successfully applied on aerospace systems. [2][3][4][5][6][7][8][9] For example, linear controllers such as proportionalintegral-derivative (PID) 10,11 and linear quadratic regulator [12][13][14] and nonlinear control approaches such as fuzzy-adaptive extended Kalman filter, 15 model predictive, 16 θ-D-based nonlinear tracking, 17 immersion and invariance-based adaptive theory, 18 nonlinear L 1 adaptive control, 19 sliding mode controller, 20,21 feedback linearization, 22,23 and backstepping [24][25][26] have been investigated for aerospace systems with fully known dynamics. What is more, several control methods have been developed to tackle the uncertain dynamic model of a dynamic system.…”

Section: Introductionmentioning

confidence: 99%

Trajectory tracking of under-actuated quadcopter using Lyapunov-based optimum adaptive controller

Navabi

Davoodi

Mirzaei

2021

Proceedings of the Institution of Mechanical Engineers, Part G:

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In this article, optimum adaptive sliding mode controller (ASMC) optimized by particle swarm optimization (PSO) algorithm is designed to solve the trajectory tracking control problems of a quadcopter with model parameter uncertainties. Quadcopters have nonlinear, multi-input multi-output, coupled and under-actuated dynamics. For comparison with the designed controller, an adaptive integral backstepping controller approach is applied to compensate mass and inertia uncertainties of the flying robot. These methods guarantee stability of closed-loop system and force the states to track desired reference signals. The performance of both controllers is evaluated by numerical simulations. The obtained results demonstrate the better effectiveness of the designed PSO ASMC in stabilization of tracking particularly with parameter uncertainties.

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