University of Science and Technology Beijing

About: University of Science and Technology Beijing is a education organization based out in Beijing, China. It is known for research contribution in the topics: Microstructure & Alloy. The organization has 41558 authors who have published 44473 publications receiving 623229 citations. The organization is also known as: Beijing Steel and Iron Institute.

Value Iteration Adaptive Dynamic Programming for Optimal Control of Discrete-Time Nonlinear Systems

Abstract: In this paper, a value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon undiscounted optimal control problems for discrete-time nonlinear systems. The present value iteration ADP algorithm permits an arbitrary positive semi-definite function to initialize the algorithm. A novel convergence analysis is developed to guarantee that the iterative value function converges to the optimal performance index function. Initialized by different initial functions, it is proven that the iterative value function will be monotonically nonincreasing, monotonically nondecreasing, or nonmonotonic and will converge to the optimum. In this paper, for the first time, the admissibility properties of the iterative control laws are developed for value iteration algorithms. It is emphasized that new termination criteria are established to guarantee the effectiveness of the iterative control laws. Neural networks are used to approximate the iterative value function and compute the iterative control law, respectively, for facilitating the implementation of the iterative ADP algorithm. Finally, two simulation examples are given to illustrate the performance of the present method.

Adaptive Neural Network Control of a Marine Vessel With Constraints Using the Asymmetric Barrier Lyapunov Function

Abstract: In this paper, we consider the trajectory tracking of a marine surface vessel in the presence of output constraints and uncertainties. An asymmetric barrier Lyapunov function is employed to cope with the output constraints. To handle the system uncertainties, we apply adaptive neural networks to approximate the unknown model parameters of a vessel. Both full state feedback control and output feedback control are proposed in this paper. The state feedback control law is designed by using the Moore–Penrose pseudoinverse in case that all states are known, and the output feedback control is designed using a high-gain observer. Under the proposed method the controller is able to achieve the constrained output. Meanwhile, the signals of the closed loop system are semiglobally uniformly bounded. Finally, numerical simulations are carried out to verify the feasibility of the proposed controller.

Efficient Semitransparent Organic Solar Cells with Tunable Color enabled by an Ultralow-Bandgap Nonfullerene Acceptor

Abstract: Semitransparent organic solar cells (OSCs) show attractive potential in power-generating windows. However, the development of semitransparent OSCs is lagging behind opaque OSCs. Here, an ultralow-bandgap nonfullerene acceptor, "IEICO-4Cl", is designed and synthesized, whose absorption spectrum is mainly located in the near-infrared region. When IEICO-4Cl is blended with different polymer donors (J52, PBDB-T, and PTB7-Th), the colors of the blend films can be tuned from purple to blue to cyan, respectively. Traditional OSCs with a nontransparent Al electrode fabricated by J52:IEICO-4Cl, PBDB-T:IEICO-4Cl, and PTB7-Th:IEICO-4Cl yield power conversion efficiencies (PCE) of 9.65 ± 0.33%, 9.43 ± 0.13%, and 10.0 ± 0.2%, respectively. By using 15 nm Au as the electrode, semitransparent OSCs based on these three blends also show PCEs of 6.37%, 6.24%, and 6.97% with high average visible transmittance (AVT) of 35.1%, 35.7%, and 33.5%, respectively. Furthermore, via changing the thickness of Au in the OSCs, the relationship between the transmittance and efficiency is studied in detail, and an impressive PCE of 8.38% with an AVT of 25.7% is obtained, which is an outstanding value in the semitransparent OSCs.

Digital Signal Processing for Short-Reach Optical Communications: A Review of Current Technologies and Future Trends

Abstract: Driven primarily by cloud service and data-center applications, short-reach optical communication has become a key market segment and growing research area in recent years. Short-reach systems are characterized by direct detection-based receiver configurations and other low-cost and small form factor components that induce transmission impairments unforeseen in their coherent counterparts. Innovative signaling and digital signal processing (DSP) play a pivotal role in enabling these components to realize their ultimate potentials and meet data rate requirements in cost-effective manners. This paper presents an overview of recent DSP developments for short-reach communications systems and discusses future trends.