AUT Journal of Electrical Engineering

AUT Journal of Electrical Engineering

Experimental Validation of Adaptive Sliding Mode Fuzzy Controller for an Inertially Stabilized Platform

Document Type : Research Article

Authors
Mohammad Nikkhoo 1
HASSAN SAYYADI 2
Mohammad saeid Seif 2
1 Kish International Campus of Sharif University of Technology, Kish, Iran
2 School of Mechanical Engineering, Centre of Excellence in Hydrodynamics and Dynamics of Marine Vehicles, Sharif University of Technology, Tehran, Iran.
10.22060/eej.2023.22068.5510
Abstract
The adaptive fuzzy control algorithm using the novel membership function was designed to suppress chattering phenomena in the performance of the three-axis Inertially Stabilized Platform (ISP) applied to the stabilization and tracking of the line of sight in optical cameras mounted on a moving boat. The stability of the nonlinear controller was proven through the Lyapunov method. For the theoretical evaluation of the controller performance, a series of numerical simulations were performed. The nonlinear kinematic and dynamic equations of the ISP were derived for this purpose. Due to the coupling between ISP frames, direct implementation of the suggested controller was not feasible. To this end, four simplified assumptions were applied to the ISP design. To evaluate the performance of the proposed control algorithm, both numerical simulation and experimental methods were used on the three-axis ISP, and the results of both methods were compared and validated. Further, the results of the proposed nonlinear control algorithm were compared with the optimal PID linear algorithm. Besides, experimentally obtained angular velocities of a boat were used for the base motion of the ISP in the numerical simulations. Despite the existence of uncertainties in dynamic system modeling, the outcomes of the implementation of the control algorithm and experimental tests indicated that the adaptive fuzzy sliding mode algorithm stabilized the line of sight with acceptable accuracy and improved its performance .
Keywords
Inertial navigation
Target tracking
Cameras
Fuzzy logic
Adaptive control
Stabilization
Subjects
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