University of Macau

About: University of Macau is a education organization based out in Macao, Macau, China. It is known for research contribution in the topics: Computer science & Population. The organization has 6636 authors who have published 18324 publications receiving 327384 citations. The organization is also known as: UM & UMAC.

Adaptive NN Controller Design for a Class of Nonlinear MIMO Discrete-Time Systems

Abstract: An adaptive neural network tracking control is studied for a class of multiple-input multiple-output (MIMO) nonlinear systems. The studied systems are in discrete-time form and the discretized dead-zone inputs are considered. In addition, the studied MIMO systems are composed of $N$ subsystems, and each subsystem contains unknown functions and external disturbance. Due to the complicated framework of the discrete-time systems, the existence of the dead zone and the noncausal problem in discrete-time, it brings about difficulties for controlling such a class of systems. To overcome the noncausal problem, by defining the coordinate transformations, the studied systems are transformed into a special form, which is suitable for the backstepping design. The radial basis functions NNs are utilized to approximate the unknown functions of the systems. The adaptation laws and the controllers are designed based on the transformed systems. By using the Lyapunov method, it is proved that the closed-loop system is stable in the sense that the semiglobally uniformly ultimately bounded of all the signals and the tracking errors converge to a bounded compact set. The simulation examples and the comparisons with previous approaches are provided to illustrate the effectiveness of the proposed control algorithm.

Ultrathin petal-like NiAl layered double oxide/sulfide composites as an advanced electrode for high-performance asymmetric supercapacitors

Abstract: Layered double hydroxide (LDH) is an important layer-structured material for supercapacitors because of its versatile compositions, high theoretical capacitance, environmental friendliness, and low cost. However, the high resistivity of this material results in capacity fading, limiting its application in energy storage. Herein, we develop a facile approach to synthesize ultrathin petal-like NiAl layered double oxide/sulfide (LDO/LDS) composites with high electrochemical activity using a hydrothermal reaction followed by a sulfidation process. Scanning electron micrographs show that the petal-like NiAl LDO/LDS composites are as thin as ∼10 nm with a mean lateral dimension of ∼1 μm. The NiAl LDO/LDS electrode delivers a remarkably high specific capacitance of 2250.5 F g−1 at 1 A g−1 compared with that of NiAl LDH (1740.5 F g−1 at 1 A g−1) and possesses a good cycling stability of 88.9% capacitance retention over 5000 cycles at 5 A g−1. An asymmetric supercapacitor (ASC) is fabricated using NiAl LDO/LDS and graphene as positive and negative electrodes, respectively. The NiAl LDO/LDS//G ASC exhibits a specific capacitance of 153.3 F g−1 at 1 A g−1, a high energy density of 47.9 W h kg−1 at a power density of 750 W kg−1, and a reliable cycling stability of 95.68% capacitance retention after 5000 cycles. The results highlight that NiAl LDO/LDS composites are promising materials for energy storage devices with long cycling stability.

Neural Network Filtering Control Design for Nontriangular Structure Switched Nonlinear Systems in Finite Time

Abstract: This paper solves the finite-time switching control issue for the nonstrict-feedback nonlinear switched systems. The controlled plants contain immeasurable states, arbitrarily switchings, and the unknown functions which are constructed with the whole states. Neural network is used to simulate the uncertain systems and a filter-based state observer is designed to estimate the immeasurable states in this paper, respectively. Based on the backstepping recursive technique and the common Lyapunov function method, a finite-time switching control method is presented. Due to the developed finite-time control strategy, the closed-loop signals can be ensured to be bounded under arbitrarily switchings, and the outputs of systems can quickly track the desired reference signals in finite time. The effectiveness of the proposed method is given through its application to a mass-spring-damper system.