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Empirical Mode Decomposition(EMD) is an advanced method for analyzing non-stationary signal, but there is an involved end issue in the course of getting two envelops of the data using spline interpolation. In this paper a novel method based on grey prediction model is proposed to restrain the end effect of empirical mode decomposition. In the grey prediction endpoint extension process, based on the...
In order to improve forecasting model accuracy of BP neural network, an improved prediction method of optimized BP neural network based on modified particle swarm optimization algorithm (PSO) was proposed. In this modified PSO algorithm, an adaptive mutation operator was proposed in PSO to change positions of the particles plunged in the local optimization. The modified PSO was used to optimize the...
Considering the limited data of spare parts consumption and the stochastic and uncontrollable of the inducing factors, a new rolling forecasting model of grey least square support vector machine (LSSVM) is proposed through analyzing disadvantages of current spare parts consumption forecasting models. The new model not only develops the advantages of accumulation generation of the grey forecasting...
In order to improve the information processing capabilities of the traditional neural network, and improve the forecast accuracy of the wind speed series, a new hysteretic neural network based on the hysteretic neurons is proposed. The hysteretic neuron is constructed by adding a hysteretic operator into the activation function. The hysteretic characteristic can make the response of the neuron is...
The grate-kiln system for iron ore pellet induration is a nonlinear, high coupling and large delay process. Considering the deviation between assumption and actual results, it is hard to build accurate kinetic models. Besides, the pure kinetic model also has the limitations to describe the induration process. In this paper, based on kinetic modeling, a hybrid model is built via neural network ensemble...
The main contribution of this paper is the development of hybrid model predictive control and fault detection strategy for wind energy conversion system (WECS) based on mixed logic dynamic (MLD) model framework. The MLD model for WECS including multiple work regions is established. Also the hybrid model predictive control method based on the MLD model of WECS is adopted to implement the variable speed...
As a feedforward control strategy, iterative learning control (ILC) is used to track a pre-defined reference and reject repetitive disturbances iteratively, but it is incapable of compensating for non-repetitive disturbances. Thus, ILC is often combined with a well-designed feedback controller. Considering nonlinear process, this paper presents an integrated ILC and on-line model predictive (MPC)...
Supervisory predictive control based on GPC theory is an effective control algorithm for complex industrial process which can be realized by adding a supervisory optimal level without modifying the regulatory level. In this paper supervisory predictive control is studied and applied in drum-type boiler-turbine system which is characterized by nonlinearity. Therefore, T-S fuzzy model is used to approximate...
The study presented in this paper sets up a new mixing sample update strategy based on the Kriging model to address the issue of accuracy in complicated engineering optimization problems by adding points dynamically. First, a new optimized Latin Hypercube Sampling experiment design method is established to increase the homogeneity of the sample. Second, a sample update strategy based on local optimization...
This article established the mathematical model of system identification of composite trimaran pitching and heave motion model based on the genetic optimization algorithm, using VB language to write the recognition software, Design and produce a composite trimaran test model, doing the free pitching and heaving decay test, then completing the pitching and heave motion system identification according...
A new approach to identification of multi-input multi-output (MIMO) Hammerstein-Wiener system is presented. The output nonlinear block consists of several single-input single-output (SISO) blocks, one of which is dead zone and saturation nonlinearity. The hinging hyperplane (HH) model expresses the character. The MIMO input nonlinear block is described by multi layer feed forward neural networks....
In semiconductor manufacturing, it is important to produce multiple products on the same equipment to enhance the overall equipment effectiveness so as to improve the productivity. However, the “high-mix” production is difficult to control due to the time-varying model. To address this problem, an adaptive exponentially weighted moving average (EWMA) control method of which the core content is online...
A tracking guidance scheme based on nonlinear model predictive control is proposed for low-thrust transfer trajectory. According to the optimal nominal transfer trajectory, the NMPC is used to design the predictive model of perturbed orbit. Performance index of receding optimization is established, which can indicate the difference between the nominal trajectory and prediction trajectory. Taking the...
For the fault diagnosis problems of the underwater vehicle sensor systems, the solution is combined by the Principal Component Analysis (PCA) and Self-Organizing Fuzzy Cerebellar Model Articulation Controller (SOFCMAC). The signal prediction model approach based on PCA and SOFCMAC is proposed in this paper. According to the history data, it can predict the signal data in the future time using the...
Components and sensors in VAV (Variable Air Volume) air distribution systems often suffer from failure easily, which result in energy waste, performance degradation or totally out of control. However, there is no applicable automatic commissioning tool for the VAV systems by now. Fault detection and diagnosis (FDD) models for VAV terminal units based on heat-mass balance of air conditioning areas...
The 2.4m×2.4m wind tunnel is a system with the properties of strong nonlinear, multiple variables, serious coupling, large lagging, time-varying, etc. The complexity of all these phenomena makes the development of suitable dynamic Mach number models based on the aerodynamics laws very difficult. As an alternative, the Ensemble Neural Networks (ENN) model based on the feature subsets is proposed to...
It is established that population structure prediction time-varying restriction system model, and its controllability of the system is analyzed through grey system theory and control theory. Based on Liapunov central limit theorem, the conclusion that child-bearing age of women is subject to the normal distribution is obtained, and the density function of fertility age is given. Fertility restricted...
According to the features of gas mixing process, an integrated modeling method based on mechanism and subspace is proposed in this paper. First, on the basis of analyzing mechanism characteristics and process data, the mechanism models of the gas flow of blast furnace and coke oven are acquired through applying butterfly valve flow characteristic formula. Then, subspace identification method is used...
Fuzzy supervisory predictive control based on genetic algorithm optimization is proposed. For the nonlinear model, through a general objective function dynamically optimized to determine the optimal set-point for a given regulatory level, by using genetic algorithm in order to solve the nonlinear optimization problem for the setpoint, and compared with the supervisory predictive control based on linear...
The main factors that affect the Determine of spare parts varieties are analyzed, the introduction of grey situation decision method to solve the varieties of spare parts in order to determine the maintenance level, a new spare parts varieties quantitative method is provided.
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