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In this paper, sliding mode control is used to develop two passive fault tolerant controllers for an AscTec Pelican UAV quadrotor. In the first approach, a regular sliding mode controller (SMC) augmented with an integrator uses the robustness property of variable structure control to tolerate partial actuator faults. The second approach is a cascaded sliding mode controller with an inner and outer SMC loops. In this configuration, faults are tolerated in the fast inner loop controlling the velocity system. Tuning the controllers to find the optimal values of the sliding mode controller gains is made using the ecological systems algorithm (ESA), a biologically inspired stochastic search algorithm based on the natural equilibrium of animal species. The controllers are tested using SIMULINK in the presence of two different types of actuator faults, partial loss of motor power affecting all the motors at once, and partial loss of motor speed. Results of the quadrotor following a continuous path demonstrated the effectiveness of the controllers, which are able to tolerate a significant number of actuator faults despite the lack of hardware redundancy in the quadrotor system. Tuning the controller using a faulty system improves further its ability to afford more severe faults. Simulation results show that passive schemes reserve their important role in fault tolerant control and are complementary to active techniques.

In this paper, two passive fault tolerant controllers based on Sliding Mode Control theory are designed for AscTec Pelican quadrotor. The first controller is a regular Sliding Mode Controller (SMC) that uses the robustness of SMC and its insensitivity to model uncertainties and disturbances to tolerate two different types of actuator faults. The latter controller is a cascaded SMC (CascSMC) with an inner loop fast SMC controlling the velocity system and tolerating its faults, and an outer loop SMC controlling the inner system (inner SMC and velocity system) with integrator. To tune the parameters of the controllers for their optimal values, a bio-inspired search algorithm called Ecological Search Algorithm (ESA) is used. SIMULINK results show that the proposed controllers are successful in controlling the quadrotor performing a helical path in the space in presence of two different actuator faults. Tests show that the cascaded SMC outperforms the regular SMC in handling tougher faults by compensating them quickly in its fast inner loop.