Adaptive Air-Fuel Ratio Control with MLP Network

This paper presents an application of adaptive neural network model-based predictive control (MPC) to the air-fuel ratio of an engine simulation. A multi-layer perceptron (MLP) neural network is trained using two on-line training algorithms: a back propagation algorithm and a recursive least squares (RLS) algorithm. It is used to model parameter uncertainties in the nonlinear dynamics of internal combustion (IC) engines. Based on the adaptive model, an MPC strategy for controlling air-fuel ratio is realized, and its control performance compared with that of a traditional PI controller. A reduced Hessian method, a newly developed sequential quadratic programming (SQP) method for solving nonlinear programming (NLP) problems, is implemented to speed up nonlinear optimization in the MPC. Keywords Air-fuel ratio control - IC engine - adaptive neural networks - nonlinear programming - model predictive control Shi-Wei Wang PhD student, Liverpool John Moores University; MSc in Control Systems, University of Sheffield, 2003; BEng in Automatic Technology, Jilin University, 2000; Current research interests automotive engine control, model predictive control, sliding mode control, neural networks.Ding-Li Yu obtained B.Eng from Harbin Civil Engineering College, Harbin, China in 1981, M.Sc from Jilin University of Technology, Changchun, China in 1986 and PhD from Coventry University, U.K. in 1995, all in control engineering. He is currently a Reader in Process Control at Liverpool John Moores University, U.K. His current research interests are in process control, engine control, fault detection and adaptive neural nets. He is a member of SAFEPROCESS TC in IFAC and an associate editor of the IJMIC and the IJISS.

Research on the Orientated Effective Components of Huangqi in Huangqi Jianzhong Tang Against Chronic Atrophic Gastritis Based on Multi-Spectrum–Effect Correlation

Objective: This study aimed to investigate the orientated effective components of Astragali Radix Huangqi(HQ) in HQ Jianzhong Tang(HQJZ), a classical formula of traditional Chinese medicine(TCM) used for treating chronic atrophic gastritis(CAG), using HQ as a monarch medicine. Materials and Methods: The spectra of HQJZ containing different polar parts of HQ were obtained using ultra-high-performance liquid chromatography-Q-Exactive mass spectrometry. Furthermore, the efficacy of HQJZ, which contains different polar parts of HQ, in treating rats with CAG was evaluated using traditional pharmacodynamic and nuclear magnetic resonance-based metabonomics. Grey relation analysis and partial least squares analysis were applied to analyze the spectrum–effect relationship and to screen out the orientated effective components related to HQ in the treatment of CAG. Results: Spectrum–effect relationship analysis showed that 24 compounds identified from the fingerprint spectrum were strongly correlated with efficacy. Compounds 8(calycosin-7-O-glc-6”-O-acetate), 9(3-hydroxy-9, 10-dimethoxyptercarpan), and 22(astragaloside II) were ranked among the top three. Conclusions: This study showed that integrating metabolomics and spectrum–effect relationship analysis is a powerful tool for obtaining orientated effective components of Chinese medicine in a given TCM formula.

Study of Viscoelastic Properties of White Carbon Black Reinforced Synthetic Polyisoprene

The viscoelastic properties of synthetic polyisoprenes （PI） reinforced by white carbon black （WCB） have been investigated and compared with WCB reinforced natural rubber （NR）, including cure characteristics, physio-mechanical and dynamic mechanical properties. Compared with NR, PI loaded with the same amount of WCB （PI/WCB） exhibited shorter scorch time and optimal cure time, indicating that WCB fillers are comparatively easier to conjugate with PI. The tensile strength and elongation at break decreased with WCB filling in both PI and NR vulcanizates. The hardness of the rubber vulcanizates increased with the WCB filling in the rubber matrix. PI/WCB blends exhibited smaller hardness data, lower tensile strength, as well as lower elongation at break and tensile stress. Increasing the amount of WCB in rubber matrix induced the Payne effect. However, the Payne effect is much more obvious for the PI/WCB system, and PI/WCB also displayed higher storage modulus whereas lower loss modulus and loss tangent than NR/WCB, which could all be attributed to the poor dispersibilities of WCB in the PI matrix.