This paper proposes a novel adaptive sliding mode based control allocation scheme for accommodating simultaneous actuator faults. The proposed control scheme includes two separate control modules with virtual control part and control allocation part, respectively. As a lowlevel control module, the control allocation/re-allocation scheme is used to distribute/redistribute virtual control signals among the available actuators under fault-free or faulty cases, respectively. In the case of simultaneous actuator faults, the control allocation and re-allocation module may fail to meet the required virtual control signal which will degrade the overall system stability. The proposed online adaptive scheme can seamlessly adjust the control gains for the high-level sliding mode control module and reconfigure the distribution of control signals to eliminate the effect of the virtual control error and maintain stability of the closed-loop system. In addition, with the help of the boundary layer for constructing the adaptation law, the overestimation of control gains is avoided, and the adaptation ceases once the sliding variable is within the boundary layer. A significant feature of this study is that the stability of the closed-loop system is guaranteed theoretically in the presence of simultaneous actuator faults. The effectiveness of the proposed control scheme is demonstrated by experimental results based on a modified unmanned multirotor helicopter under both single and simultaneous actuator faults conditions with comparison to a conventional sliding mode controller and a linear quadratic regulator scheme.

An adaptive sliding mode fault‐tolerant control strategy is proposed for a quadrotor unmanned aerial vehicle in this article to accommodate actuator faults and model uncertainties. First, a new reaching law is proposed, with which a sliding mode control (SMC) law is constructed. The proposed reaching law is made up of a sliding variable and the distance between it and a designated boundary layer, and it can effectively suppress the unexpected control chattering while preserving the necessary system tracking performance. Then, an adaptive SMC scheme is proposed to further solve the fault and uncertainty compensation problem. The proposed adaptation law helps to prevent overestimation of the adaptive control parameters, as well as avoiding control chattering. Finally, a number of comparative simulation tests are carried out to validate the effectiveness and superiority of the proposed control strategy. The demonstrated quantitative comparison results confirm its advantages.

Sliding mode control (SMC) is known as a robust control method to maintain system performance and keep it insensitive to system uncertainties. To achieve this objective, the knowledge of the uncertainty bound is usually needed, but sometimes it could be a hard task. Hence, the adaptive technology is introduced to be synthesized with SMC. In this paper, a novel adaptive SMC (ASMC) scheme is proposed to accommodate system uncertainties caused by actuator faults. An integral sliding mode controller is used as the baseline controller. When actuator faults occur, there is no need to know the exact bound of the uncertainties in control effectiveness matrix. The post-fault control effectiveness matrix can be estimated by the proposed adaptive control scheme, and the control inputs will be changed accordingly. In such a way, the robustness of the controller to actuator faults is improved. With the help of adaptive change of both continuous and discontinuous control parts, a minimum value of the discontinuous control gain can be guaranteed. In this case, the resulting control effort is reduced accordingly to avoid control chattering effect. Owing to the minimized control effort to accommodate uncertainties compared to the conventional SMC, the proposed ASMC can still maintain the system performance when severer faults occur. The effectiveness of the developed algorithm is demonstrated by the simulation results based on an unmanned quadrotor helicopter under various faulty conditions.

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