Northeastern University (China)

About: Northeastern University (China) is a education organization based out in Shenyang, China. It is known for research contribution in the topics: Microstructure & Control theory. The organization has 36087 authors who have published 36125 publications receiving 426807 citations. The organization is also known as: Dōngběi Dàxué & Northeastern University (东北大学).

Particle Swarm Optimization With Composite Particles in Dynamic Environments

Abstract: In recent years, there has been a growing interest in the study of particle swarm optimization (PSO) in dynamic environments. This paper presents a new PSO model, called PSO with composite particles (PSO-CP), to address dynamic optimization problems. PSO-CP partitions the swarm into a set of composite particles based on their similarity using a “worst first” principle. Inspired by the composite particle phenomenon in physics, the elementary members in each composite particle interact via a velocity-anisotropic reflection scheme to integrate valuable information for effectively and rapidly finding the promising optima in the search space. Each composite particle maintains the diversity by a scattering operator. In addition, an integral movement strategy is introduced to promote the swarm diversity. Experiments on a typical dynamic test benchmark problem provide a guideline for setting the involved parameters and show that PSO-CP is efficient in comparison with several state-of-the-art PSO algorithms for dynamic optimization problems.

A Separated Approach to Control of Markov Jump Nonlinear Systems With General Transition Probabilities

Abstract: This paper is devoted to the control of Markov jump nonlinear systems with general transition probabilities (TPs) allowed to be known, uncertain, and unknown. With the help of the S-procedure to dispose the system nonlinearities and the TP property to eliminate the coupling between unknown TP and Lyapunov variable, an extended bounded real lemma for the considered system to be stochastically stable with the prescribed ${\mathcal {H}}_{{\infty }}$ performance is established in the framework of linear matrix inequalities. To handle the nonlinearity incurred by uncertain TP for controller synthesis, a separated method is proposed to decouple the interconnection between Lyapunov variables and controller gains. A numerical example is given to show the effectiveness of the proposed method.

NO2 sensing properties of one-pot-synthesized ZnO nanowires with Pd functionalization

Abstract: The application of NO2 sensor based on metal oxide semiconductor is limited due to high operating temperature and poor selectivity. In this work, a low-temperature and high-performance NO2 sensor based on Pd-functionalized ZnO nanowires (Pd-ZNWs) prepared by a facile one-pot hydrothermal method was reported. The Pd was formed and self-assembled onto the surface of ZnO nanowires (ZNWs) during this one-pot hydrothermal process. Microstructure characterization of Pd-ZNWs indicated that the obtained ZNWs with diameter of 100–250 nm and length of 2–10 μm had a single crystal hexagonal structure, and Pd/PdO nanoparticles of approximately 2–5 nm in diameter were distributed on their surface. Gas sensing measurement showed that Pd-ZNWs exhibited higher response, lower optimal operating temperature, and faster response/recovery speeds towards NO2 than those of pure ZNWs. The maximum responses of 1 mol%, 2 mol%, and 5 mol% Pd-ZNWs towards 1 ppm NO2 were 13.5, 9.4, and 9.4, respectively, which were obtained at a low operating temperature of 100 °C and 30% RH. Pd-ZNWs also showed a significant improvement in sensing selectivity towards NO2. At a high RH condition of 60%, the sensors based on pure and Pd-ZNWs still exhibited noticeable responses, fast response/recovery speeds, and good long-term stability to NO2 gas. The sensing mechanism of Pd-ZNWs towards NO2 was discussed by the combination of electronic and chemical sensitization.