This paper presents a robust adaptive sliding mode controller scheme as applied to a class of uncertain nonlinear systems with parametric uncertainties and external disturbances. First, a sliding mode control technique is designed. Then, the proposed robust adaptive control schemes are applied to estimate the parametric uncertainties and the upper bound value of the external disturbances by using adaptive laws, ensure robustness in presence of parametric uncertainties and external disturbances, and reduce chattering problem by introducing an hyperbolic tangent function. Lyapunov stability theory is used to analyze the stability of the closed-loop system. As an exemplar, the schemes have been applied to a quadrotor unmanned aerial vehicle (QUAV) model. Simulation results for the control of the QUAV model are provided to illustrate the performance of the proposed robust adaptive sliding mode control scheme and demonstrate that the proposed method has good tracking performance. The simulation results clearly prove the effectiveness of our approach.

In this article, an immersion and invariance based adaptive command filtered backstepping control method (I&I ACFBC) is proposed for a class of single-input and single-output (SISO) uncertain nonlinear systems in strict-feedback form. The problem of the explosion of complexity inherent to the traditional adaptive backstepping control design is solved by applying the proposed adaptive control technique, and the compensating signals are constructed to reduce the effect of the known filtering errors produced by the command filters. The adaptive laws are achieved by an immersion and invariance method. The Lyapunov stability theory is utilized to ensure the boundedness of all the signals in the closed-loop system. The feasibility and validity of the proposed adaptive control scheme are demonstrated by the simulation and experimental results on a DC-DC buck converter system.

The concept of fractional-order control (F-oC) is exploited in this paper to synchronize fractional-order dynamical systems. The addressed systems in this paper reflect the real physical phenomena characterized by the complicated relationship between supply and demand for energy resources in the Shanghai area. Thus, we provide the developed fractional energy resource attractor and the simulation results regarding synchronization under the proposed control law of the same fractional energy resource attractor. Note that most of the synchronization methods achieved excellent performance when dealing with complex continuous systems; however, no method addressed the synchronization problem of fractional-order energy resource systems based on the F-oC and modern optimization techniques, to the best of our knowledge. By designing the finite-time control theory, the finite-time full synchronization of two identical fractional-order energy resources demand-supply hyperchaotic systems (F-oERDSHSs) is investigated due to its performance. The advanced prediction-based fractional-order control law (Pb-FoCL) is established for finite-time synchronization of F-oERDSHSs. The design procedure becomes a multiobjective optimization problem of the knowledge base of the developed controller while satisfying the desired performance requirements. The Finite-Time Stability (F-TS) of the control-loop system is proved by using the finite-time Lyapunov stability theory. Furthermore, the Improved Artificial Hummingbird Algorithm (I-AHA) is used to find an optimal knowledge base of Pb-FoCL while achieving the design constraints. Simulation results are provided to verify the efficiency of the proposed control strategy.