Search

Abstract By relying on the input–output feedback linearization approach, a novel adaptive controller for flexible joint robots is proposed in this work. First, a model‐based controller is developed to get a structure that is useful in the development of the adaptive controller. The adaptive version is developed by using two techniques. To stabilize the output function, an adaptive neural network controller is used, which approximates the non‐linear function that contains the uncertainties. The desired rotor position required by the input–output feedback linearization controller is defined with the structure of a link dynamics adaptive regressor‐based controller. The main reason to adopt the mentioned structure in the definition of the desired rotor link position is to guarantee its differentiability. Real‐time experiment comparisons among the model‐based controller, a model‐based controller with desired compensation, an adaptive controller based on joint torque feedback, and an adaptive neural network‐based controller are carried out. Experimental results support the theory reported in this document and the accuracy of the proposed approach.

Abstract The main purpose of this paper is to extract the maximum power from the variable speed wind turbine (VSWT), which is modelled using fractional calculus. The use of the fractional‐order operator can harden the practical implementation and numerical simulation of the fractional‐order systems. To apply the fractional calculus theory, we assume that the orders of all fractional derivatives of the system have a small deviation from the nearest integers. By defining this small deviation as a perturbation parameter, an integer‐order approximation method is presented for approximating the fractional‐order system into a perturbed integer‐order system in the time domain. Then, a new adaptive second‐order sliding mode control (SOSMC) method is proposed using the terminal proportional integral derivative (TPID) sliding surface to achieve maximum power extraction and reduce mechanical loads and chattering. A TPID sliding surface is employed to ensure better tracking, have a zero steady‐state error, decrease the mechanical stresses, and eliminate the chattering phenomenon. The stability of the adaptive SOSMC based on the obtained integer‐order approximation is analyzed using the Lyapunov stability criterion. The simulation results of the proposed method are presented and compared with some designed controllers for wind turbines (WTs) modelled with fractional and integer derivatives. The obtained results show the effectiveness of the proposed strategy.

Abstract This paper is concerned with security problems for cyber‐physical systems (CPSs) under dynamic load altering attacks (DLAA) and false data injection attacks (FDIA). The smart grid, as a typical CPS system, is taken as an example in this paper. Since the communication channel is vulnerable to FDIA and DLAA, the stability of the smart grid may be influenced. For enhancing resilience and stability of smart grids, first of all, the power system model including both DLAA and FDIA is introduced. Second, an adaptive sliding mode controller is proposed. The controller can ensure the reliable operation of the power system in the case of unknown attack information by using the adaptive mechanism online estimating the upper bound of attack signal to automatically eliminate the effect of mixed attacks. Finally, a power system with three generators and six buses is taken as an illustrative example, and simulation and experiment results obtained by using MATLAB and Hardware‐in‐time platform built by Sartsim verify the effectiveness of the proposed resilient defense strategy.

Abstract This paper proposes a control strategy integrating the non‐linear extended state observer (NLESO) and the non‐singular terminal sliding mode control (NTSMC) for the trajectory tracking of wheeled mobile robots subject to bounded disturbances. A new transformation method of chained model in terms of Lie derivative is presented to simplify the controller design. A specific NLESO combining linear term and non‐linear term is designed to estimate the disturbances with a faster convergence performance. A scheme for determining the gain range of NLESO is explicitly given to facilitate the tuning of experimental parameters. Meanwhile, the NTSMC achieves finite time convergence of the tracking error system and the chattering phenomenon in NTSMC is dramatically alleviated with the compensation from NLESO. The experimental results validate the strong robustness and good performance of the proposed control strategy.

Abstract One of the control problems drawing engineers' and researchers' attention is the tracking control with predicted reference signals. The applications of this control problem are found in electric power control systems, automatic driving systems, and so on. The difficulty of the tracking control with the predicted signal is that the prediction errors lead to performance degradation of control systems. This paper aims to shape the predicted signals based on past information of reliable reference signal and system dynamics information to reduce the performance degradation caused by prediction errors. First, a signal shaping mechanism called prediction governor was proposed, and its optimal design problem was formulated. Then, an optimal solution for the design problem was analytically derived and the performance limitation of the prediction governor was clarified. The proposed optimal prediction governor is tailor‐made for a given control system. By adding it to the control system, the influence of the prediction error generated by a given prediction tool can be minimised. Finally, the usefulness of the proposed optimal prediction governor was illustrated through an electric power balancing control problem with a microgrid system.

Abstract Here, a switching control mechanism for the stabilization of a DC–DC zeta converter operating in continuous conduction mode is proposed. The switching control algorithm is based on a control Lyapunov function and extends the method proposed for a two‐dimensional boost converter model presented in the literature to a four‐dimensional zeta converter model. The local asymptotical stability of the operating point is established using LaSalle's invariance principle for differential inclusions. By applying spatial regularization, a modified switching control algorithm reduces the switching frequency and keeps the state‐trajectory around a neighbourhood of the operating point. The method works well even if the operation point changes significantly and it is valid for both step‐up and step‐down operations. Furthermore, by approximating the state‐trajectory near the operating point, an explicit relation between the modified switching algorithm and the switching frequency is obtained, which allows to choose systematically the desired switching frequency for the converter to operate. The effectiveness of the proposed method is illustrated with simulation results.

Abstract This paper is devoted to the application of a recently proposed globally convergent adaptive position observer to non‐salient permanent magnet synchronous motors. Following the Dynamic Regressor Extension and Mixing Based Adaptive Observer (DREMBAO) approach, a new finite‐time robust observer is presented that allows to track adaptively the rotor position by measuring only the currents and voltages and without knowledge of mechanical, electrical and magnetic parameters. A numerical example for the case with different rotor speeds and time‐varying load torque is considered to reveal the advantages of the proposed approach in comparison with other existing methods. Experimental studies of the proposed robust nonlinear observer implementation are presented to illustrate the efficiency of the new design technique in different speed modes together with adaptive estimation of unknown parameters.

Abstract This paper investigates the memory‐based integral sliding mode control (SMC) design for nonlinear doubly fed induction generator model. The proposed nonlinear doubly fed induction generator model is equivalent to linear sub‐systems via fuzzy membership functions by utilising the Takagi–Sugeno fuzzy approach. Then, a memory‐based sliding surface is intended, which is different from the conventional sliding surface. Based on suitable Lyapunov functionals and slack matrices, sufficient conditions are obtained, which guaranty the memory‐based Takagi–Sugeno fuzzy system to be globally asymptotically stable under the designed memory‐based sliding mode control through linear matrix inequality. Further, the desired memory‐based fuzzy SMC control gain is obtained by solving the concerned linear matrix inequality. Also, a memory‐based SMC law and an adaptive SMC law are incorporated to make the system state trajectories onto the pretend sliding switching manifold in a finite‐time. The derived conditions are verified in the numerical section with the nonlinear doubly fed induction generator model, which are formulated for reflecting the characteristics of the proposed wind turbine model.