A novel hybrid model predictive control design with application to a quadrotor helicopter. (15th January 2018)

• Record Type: Journal Article
• Authors: Jalili, Sadegh; Rezaie, Behrooz; Rahmani, Zahra
• Is Part Of: Optimal control applications and methods. Volume 39:Number 4(2018)
• Page Start: 1301
• Page End: 1322
• Publication Date: 2018-01-15
• Subjects: fuzzy logic controller -- nonlinear model predictive control -- optimization -- quadrotor -- receding horizon; Control theory -- Periodicals; Mathematical optimization -- Periodicals; 629.8312
• DOI: 10.1002/oca.2411
• Languages: English
• ISSNs: 0143-2087

Abstract

Summary: In this paper, a novel control design strategy based on a hybrid model predictive control in combination with fuzzy logic control is presented for a quadrotor helicopter system. In the proposed scheme, a 2‐part control structure is used. In the first part, a linear model predictive controller with receding horizon design strategy is combined with a nonlinear model predictive controller, which is applied as the main controller. In the second part, a 2‐level fuzzy logic controller is utilized to assist the first controller when the error exceeds a predefined value. The proposed nonlinear predictive control method utilizes a novel approach in which a prediction of the future outputs is used in the modeling stage. Using this simple technique, the problem can be solved using linear methods and, thereby, due to considerable reduction in the computational cost, it will be applicable for the systems with fast dynamics. Moreover, the fuzzy logic controller is used as a supervisor to adjust a proportional‐integral‐derivative controller to enhance the system performance by decreasing the tracking error. The proposed scheme is applied to a model of quadrotor system such that the difference between the predicted output of the system and the reference value is minimized while there are some constraints on inputs and outputs of the nonlinear quadrotor system. Simulation results demonstrate the efficiency of the proposed control scheme for the quadrotor system model.