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-l...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.展开更多
The fuzzy neural networks has been used as means of precisely controlling the air-fuel ratio of a lean-burn compressed natural gas (CNG) engine. A control algorithm, without based on engine model, has been (utilized) ...The fuzzy neural networks has been used as means of precisely controlling the air-fuel ratio of a lean-burn compressed natural gas (CNG) engine. A control algorithm, without based on engine model, has been (utilized) to construct a feedforward/feedback control scheme to regulate the air-fuel ratio. Using fuzzy neural networks, a fuzzy neural hybrid controller is obtained based on PI controller. The new controller, which can adjust parameters online, has been tested in transient air-fuel ratio control of a CNG engine.展开更多
聚焦绿色高性能混凝土(Green High Performance Concrete,GHPC)的最佳配合比,旨在实现保持卓越性能的同时最大限度地利用工业废渣,如粉煤灰、超细矿渣、硅灰等。通过深入研究最佳配合比,能够精确调控GHPC的工作性能、强度和耐久性,以满...聚焦绿色高性能混凝土(Green High Performance Concrete,GHPC)的最佳配合比,旨在实现保持卓越性能的同时最大限度地利用工业废渣,如粉煤灰、超细矿渣、硅灰等。通过深入研究最佳配合比,能够精确调控GHPC的工作性能、强度和耐久性,以满足可持续建筑的标准。研究采用了贝叶斯算法优化后的高斯过程回归模型,通过125组试验结果进行训练,最终确定了FL 11%、SF 0%、SL 16%的最佳混合比。通过对比预测与试验结果,验证了模型的可靠性,误差控制在2%以内。该研究为GHPC的配合比提供了科学依据,为推动环保建筑材料的可持续发展提供了实用的指导。展开更多
In this paper, we study the best-mixture ratio of biodiesel-ethanol-diesel for diesel engines. The simulation results show that the integrated indexes including engine power, cost-effectiveness and emission properties...In this paper, we study the best-mixture ratio of biodiesel-ethanol-diesel for diesel engines. The simulation results show that the integrated indexes including engine power, cost-effectiveness and emission properties are rather better with different optimizing index when the ratio of bio-diesel, ethanol and diesel are 71.58:2.72:25.70 and 50:2.4127:47.5873.展开更多
针对新型调频式谐振特高压试验电源(UHV frequencytuned resonant test power supply,UHV-FTRTPS)输出信号频率较宽,不易获得最佳波形这一问题,提出了一种新的特高压试验电源方案。在167～300 Hz高频率段,采用同步正弦脉宽调制(sinusoid...针对新型调频式谐振特高压试验电源(UHV frequencytuned resonant test power supply,UHV-FTRTPS)输出信号频率较宽,不易获得最佳波形这一问题,提出了一种新的特高压试验电源方案。在167～300 Hz高频率段,采用同步正弦脉宽调制(sinusoidal pulse-width modulation,SPWM),把载波比N的数值选择与输出滤波器本身结构相结合,得到合理的最佳N值和滤波器最小视在功率。同时,在30～167 Hz低频率段,采用特定次谐波消除方法在线计算各开关角度,消弱低次谐波,把低次谐波转移到高次谐波,以利于输出滤波器滤除。最后,在输出滤波器电容上串联1个虚拟电阻,在不增加硬件及不改变输出滤波器结构的基础上,从软件控制方法上来增强其阻尼性,使之更好地滤除高次谐波。仿真及试验结果验证了该方案的正确性和有效性,对新型特高压试验电源的工程应用及产品化具有一定的指导和借鉴作用。展开更多
文摘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.
文摘The fuzzy neural networks has been used as means of precisely controlling the air-fuel ratio of a lean-burn compressed natural gas (CNG) engine. A control algorithm, without based on engine model, has been (utilized) to construct a feedforward/feedback control scheme to regulate the air-fuel ratio. Using fuzzy neural networks, a fuzzy neural hybrid controller is obtained based on PI controller. The new controller, which can adjust parameters online, has been tested in transient air-fuel ratio control of a CNG engine.
文摘In this paper, we study the best-mixture ratio of biodiesel-ethanol-diesel for diesel engines. The simulation results show that the integrated indexes including engine power, cost-effectiveness and emission properties are rather better with different optimizing index when the ratio of bio-diesel, ethanol and diesel are 71.58:2.72:25.70 and 50:2.4127:47.5873.
文摘针对新型调频式谐振特高压试验电源(UHV frequencytuned resonant test power supply,UHV-FTRTPS)输出信号频率较宽,不易获得最佳波形这一问题,提出了一种新的特高压试验电源方案。在167～300 Hz高频率段,采用同步正弦脉宽调制(sinusoidal pulse-width modulation,SPWM),把载波比N的数值选择与输出滤波器本身结构相结合,得到合理的最佳N值和滤波器最小视在功率。同时,在30～167 Hz低频率段,采用特定次谐波消除方法在线计算各开关角度,消弱低次谐波,把低次谐波转移到高次谐波,以利于输出滤波器滤除。最后,在输出滤波器电容上串联1个虚拟电阻,在不增加硬件及不改变输出滤波器结构的基础上,从软件控制方法上来增强其阻尼性,使之更好地滤除高次谐波。仿真及试验结果验证了该方案的正确性和有效性,对新型特高压试验电源的工程应用及产品化具有一定的指导和借鉴作用。
