Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : Model Reference Control


Optimal H-infinity PID Model Reference Controller Design for Roll Control of a Tail-Sitter VTOL UAV

Ali H. Mhmood; Hazem I. Ali

Engineering and Technology Journal, 2021, Volume 39, Issue 4, Pages 552-564
DOI: 10.30684/etj.2021.168134

In this work, an optimal and robust controller based on consolidating the PID controller and H-infinity approach with the model reference control is proposed. The proposed controller is intended to accomplish a satisfactory transient response by including the reference model. A Tail-Sitter VTOL UAV system is used to show the effectiveness of the proposed controller. A dynamic model of the system is formulated using Euler method. To optimize the design procedure, the Black Hole Optimization (BHO) method is used as a new Calibration method. The deviation between the reference model output and system output will be minimized to obtain the required specifications. The results indicate that the proposed controller is very powerful in compensating the system parameters variations and in forcing the system output to asymptotically track the output of the reference model.

H-infinity Model Reference Controller Design for Magnetic Levitation System

H.I. Ali

Engineering and Technology Journal, 2018, Volume 36, Issue 1, Pages 17-26

In this paper, a new robust approach based on combining the model reference control with H-infinity technique is proposed. The goal of the proposed controller is to obtain an adequate transient response which may not be obtained when only H-infinity technique is used. This is done by adding the model reference block to the standard H-infinity feedback configuration. Then the overall block diagram is formulated by linear fractional transformation (LFT). The Magnetic Levitation which is a highly nonlinear, open loop unstable and uncertain system is used to show the effectiveness of the proposed controller. The results show that the proposed controller is very effective in compensating the system parameters variations with forcing the system output to track the output of the model reference. A variation of ±10% in system parameters is considered.