Abstract
This paper aims to design an enhanced self-adaptive interval type-2 fuzzy control system (ESAF2C) for stabilization of a quadcopter drone under external disturbances. Due to the ability to accommodate the footprint-of-uncertainty (FoU), an interval type-2 Takagi-Sugeno fuzzy scheme is employed to directly address the uncertainties in the nonlinear system. Sliding mode control (SMC) is utilized to optimize the upper and lower parameters of our proposed ESAF2C system using a self-tuning technique. The ‘Enhanced Iterative Algorithm with Stop Condition’ type-reducer is accommodated in the proposed design for its suitability to real-time implementation. To handle external disturbances and the ground effect in the closed-loop flight control system, a robustness term is added to the control effort. Lyapunov theory is applied to prove the stability of our closed loop control system. Moreover, we study the measurement noise effect for different levels of noise powers using our proposed technique. The efficacy of the proposed controller is investigated in a hovering quadcopter drone through numerical simulations and real-time flight tests in the presence of external disturbances. We highlight the disturbance rejection capability of our proposed control system with respect to type-1 fuzzy and conventional PID controllers.
Highlights
D RONES, a prominent nickname for unmanned aerial vehicles (UAVs), have been attracting a large amount of consideration in the last few decades
interval type-2 fuzzy logic control systems (IT2FLCs) are used to speed up the response to uncertain input for membership functions, allowing more flexibility in designing the desired control law and providing the capacity to handle additional uncertainties commonly found in nonlinear systems [14], [40]
RELATED WORK Since IT2FLCs provide an extra degree of freedom to handle uncertainties in nonlinear systems, they have been applied for navigating quadcopter UAVs
Summary
D RONES, a prominent nickname for unmanned aerial vehicles (UAVs), have been attracting a large amount of consideration in the last few decades They have been used in a myriad of applications There are inevitable uncertainties in aerial robots, (e.g. lack of modeling, mechanical wear, rotor damage, battery drain and sensor and actuator faults [18], [19]) Another aerodynamic challenge when flying a rotorcraft vehicle at a reasonably low altitude is ground effect, which occurs due to the distortion of rotor downwash due to the ground obstruction [20], [21]. Since uncertainty information is not incorporated in the membership function of type-1 fuzzy sets (T1FSs), controlling nonlinear systems subjected to uncertainties cannot be handled precisely. IT2FLCs are used to speed up the response to uncertain input for membership functions, allowing more flexibility in designing the desired control law and providing the capacity to handle additional uncertainties commonly found in nonlinear systems [14], [40]
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