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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.

One direction in optimizing wind farm production is reducing wake interactions from upstream turbines. This can be done by optimizing turbine layout as well as optimizing turbine yaw and pitch angles. In particular, wake steering by optimizing yaw angles of wind turbines in farms has received significant attention in recent years. One of the challenges in yaw optimization is developing fast optimization algorithms which can find good solutions in real-time. In this work, we developed a random search algorithm to optimize yaw angles. Optimization was performed on a layout of 39 turbines in a 2 km by 2 km domain. Algorithm specific parameters were tuned for highest solution quality and lowest computational cost. Testing showed that this algorithm can find near-optimal (<1% of best known solutions) solutions consistently over multiple runs, and that quality solutions can be found under 200 iterations. Empirical results show that as wind farm density increases, the potential for yaw optimization increases significantly, and that quality solutions are likely to be plentiful and not unique.

Both backstepping control (BC) and sliding mode control (SMC) have been studied extensively over the past few decades, and many variations of controller designs based on them can be found in the literature. In this paper, sliding mode control in a backstepping framework (SBC) for a class of nonlinear systems is proposed and its connections to SMC studied. SMC is shown to be a special case of SBC. Without losing generality, the regulation control problem is studied, while tracking control is achieved by replacing the states with the difference between the states and their desired values. The SBCs are designed for nonlinear single-input-single-output (SISO) and multiple-input-multiple-output (MIMO) systems with the presence of bounded uncertainties from unmodeled dynamics, parametric variations, disturbances, and measurement noise, and the closed loop systems are proven to be asymptotically stable using the Lyapunov stability theory. The comparison of SBC to SMC from the design process, chattering effects, and chatter reduction are also discussed. SBC inherits the merits of backstepping control in choosing gains independently, while leveraging useful nonlinear dynamics for controller design simplification. Hence, it provides more flexibility in controller design in the sense of controlling coverage speed and making use of useful nonlinearities in the dynamics. To demonstrate the effectiveness of SBC, an application on cruise tracking control of an autonomous underwater vehicle was studied.