Abstract
This paper investigates an Adaptive Fuzzy Gains-Scheduling Integral Sliding Mode Controller (AFGS-ISMC) design approach to deal with the attitude and altitude stabilization problem of an Unmanned Aerial Vehicles (UAV) precisely of a quadrotor. The Integral Sliding Mode Control (ISMC) seems to be an adequate control tool to remedy this problem. The selection of the controller parameters is done most of the time using repetitive trials-errors based methods. This method is not completely reliable and becomes a time-consuming and difficult task. Here we propose the tuning and selection of all ISMC gains adaptively according to a fuzzy supervisor. The sliding surface and its differential are declared as Fuzzy Logic Supervisor (FLS) inputs and the integral sliding mode control gains as the FLS outputs. The proposed fuzzy-based supervision mechanisms modify all ISMC gains to be time-varying and further enhance the performance and robustness of the obtained adaptive nonlinear controllers against uncertainties and external disturbances. The proposed adaptive fuzzy technique increases the effectiveness of the ISMC structure compared to the classical SMC strategy and excludes the dull and repetitive trials-errors process for its design and tuning. Various simulations have been carried out and followed by comparison and discussion of the results in order to prove the superiority of the suggested fuzzy gains-scheduled ISMC approach for the quadrotor attitude and altitude flight stabilization.
Highlights
Unmanned Aerial Vehicles (UAVs) are volant robots with no aviator that are capable of carrying out various missions in inimical and unsettled environments [1]
The purpose of the designed adaptive fuzzy sliding mode controllers is to drive the rotorcraft to rise to 4 meters high and keep hovering
The generated AFGS-based Integral Sliding Mode Control (ISMC) gains for the closed-loop altitude and attitude dynamics are shown in Fig. 7 to Fig. 10
Summary
Unmanned Aerial Vehicles (UAVs) are volant robots with no aviator that are capable of carrying out various missions in inimical and unsettled environments [1]. Incited by its noticeable draw in diverse control appliance as well as its straightforwardness in real-world implementation, the fuzzy control theory has been applied to attain advanced performances and robustness for complex and nonlinear systems [26]-[28].The tuning and selection of all ISMC gains, systematically and without any trials-errors based stage, thanks to a proposed fuzzy supervision mechanism, is a promising idea and efficient solution given the complexity and the hardness design of the conventional ISMC approach Such a proposed fuzzy gains-scheduling technique allows having variable gains over time based integral sliding mode controllers that are more appropriate and efficient to uncertainties, disturbances and faults of UAV rotorcrafts.
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