This paper concentrates on the problem of control of a hybrid energy storage system (HESS) for an improved and optimized operation of load-frequency control applications. The HESS consists of a supercapacitor serving as the main power source and a fuel cell serving as the auxiliary power source. First, a Hammerstein-type neural network is proposed to identify the HESS, which formulates the Hammerstein model with a nonlinear static gain in cascade with a linear dynamic block. It provides the model information for the controller to achieve the adaptive performance. Second, a feedforward neural network based on a back-propagation training algorithm is designed to formulate the proportional-integral-derivative (PID)-type neural network, which is used for the adaptive control of the HESS. Meanwhile, a dynamic antiwindup signal is designed to solve the operational constraint of the HESS. Then, an appropriate power reference signal for the HESS can be generated. Third, the stability and the convergence of the whole system are proved based on the Lyapunov stability theory. Finally, simulation experiments are followed through on a four-area interconnected power system to demonstrate the effectiveness of the proposed control scheme.

In this paper, a new model-free adaptive integral sliding-mode-constrained control scheme is presented for autonomous four-wheeled mobile vehicle (4WMV) parking systems. The proposed control strategy includes: 1) online identification for the object model based on a data-driven technique is presented for 4WMV and 2) an integral sliding-mode controller with control input constraints and stability analysis is provided. For online data-driven model identification, a compact-form dynamic linearization-based observer formulation is constructed for 4WMV. For integral sliding-mode controller design, a dynamic antiwindup compensator is introduced to solve integral saturation and actuator saturation problems in the autonomous 4WMV parking system. The designed control scheme only utilizes the body angle and steering angle of the vehicle under the condition that the precise mechanism model of the autonomous 4WMV parking system is not available to us. Finally, simulation comparisons between the model-free adaptive integral sliding-mode-constrained control scheme, PID control, and model-free adaptive control algorithms with coordinate compensation are given for two different vehicles. The simulation results show that a better control performance is achieved with the proposed new sliding-mode controller than the traditional control method when actuator or control input saturation exists in the autonomous 4WMV parking system.

In this paper, a terminal sliding mode control strategy with projection operator adaptive law is proposed in hybrid energy storage system. The objective of the proposed control strategy is to provide power for load in time, get good tracking performance of the current of fuel cell, battery and supercapacitor, and obtain stable voltage of the DC bus. At first, the topological structure of the system is proposed, and the mathematical models are derived. Then, on the basis of the working characteristics of energy storage unit, the load power is reasonably and effectively distributed to increase the service life of hybrid energy storage system and improve energy efficiency. Meanwhile, according to the tracking errors of reference and actual values, the terminal sliding surfaces can be set out. And the controller can be designed by the constraint condition, combining the projection operator adaptive law. In addition, the hybrid energy storage system with the proposed control is proved to be asymptotically stable by using Lyapunov method. Finally, simulation results show that the proposed control strategy can make the whole system stable, and the control objective can also be better realized.

In this article, a nonsingular fast terminal sliding mode (NFTSM) control strategy is proposed based on the high-order super-twisting observer (HOSTO) to acquire a fast and precise tracking performance for position regulation of permanent magnet linear synchronous motor. First, the NFTSM control is introduced to achieve fast convergence of the position tracking error. However, the lumped disturbances result in incompleteness of the system state information, and the robustness of the system is guaranteed through a large switching gain for the NFTSM, which causes system chattering. Therefore, the HOSTO is utilized to estimate the state information. Then, the NFTSM controller is designed based on the estimated state variables. The system’s stability under the proposed control is demonstrated using Lyapunov stability theory. Finally, real-time experiments are carried out to illustrate the efficiency and superiority of the proposed control strategy.

With the aim to solve the problems related to the power distribution and current chattering in a distributed energy storage system (DESS), which can be considered as a multi-agent system in DC microgrid, a model-free cooperative sliding mode control scheme with a directed-graph-based observer is proposed in this paper. First, a state-of-charge (SoC)-based droop control strategy is combined with a directed-graph-based voltage regulation method to balance the SoCs of each energy storage unit (ESU), allocate the power and maintain the bus voltage stability. Besides, a directed-graph-based observer is designed to estimate the battery current considering the communication between the ESUs, and based on this observer, an estimation algorithm for adaptive coefficients is developed. Then, the multi-agent sliding mode control strategy with an anti-windup compensator of input constraint is developed to track the reference current with little chattering in the DESS, and the stability proof is given. Finally, the simulations are conducted to validate the effectiveness and superiority of the newly designed control strategy for the DESS.