Attitude Control of a 3DOF Quadrotor Stand Using a Heuristic Nonlinear Controller

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Alizad Arabolye Bishe, Meysam | 2018

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 50487 (45)
University: Sharif University of Technology
Department: Aerospace Engineering
Advisor(s): Nobahari, Hadi
Abstract:
A new heuristic controller, called nonlinear model predictive control based on gravitational search algorithm, is proposed for nonlinear systems. Nonlinear model predictive control involves the solution at each sampling instant of a finite horizon optimal control problem subject to nonlinear system dynamics and constraints. The new controller formulates nonlinear model predictive control problem as a single stochastic dynamic optimization problem and uses a system of virtual masses to find the best control signal at each sampling instant. For this purpose, a cost function is defined to evaluate each point of the search space. This function minimizes simultaneously the tracking error, control effort, and control smoothness. Masses search the search space dynamically in a similar scheme to the optimization algorithm, known as gravitational search algorithm. The performance of the new controller is evaluated for five nonlinear problems. Then, the performance of it is evaluated for the Attitude Control of a 3DOF Quadrotor Stand in simulation and implementation. The obtained results confirm the successful performance of the proposed controller
Keywords:
Attitude Control ; Implementation ; Quadrotor ; Nonlinear Model Prediction ; Gravitational Search Algorithm

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