nonlinear neural predictive model
CONTROL OF NONLINEAR PROCESS USING NEURAL NETWORK BASED MODEL PREDICTIVE CONTROL
... Model predictive control (MPC) techniques have been recognized as efficient approaches to improve operating efficiency and ...non-linear model predictive control ...of predictive ...
9
Learning Based Approximate Model Predictive Control for Nonlinear Systems
... based neural network, is chosen for this task, because it has a simple, expressive structure, that depends on relatively few tuning param- eters and its training is fast and ...
6
Design of Model Predictive Control based Direct Neural Controller for Surge Tank Application
... selected nonlinear system with RBFN based neural controller is realized in environment of ...of nonlinear dynamic systems described by the differential ...The nonlinear system has ...
6
Comparative Study of PI Controller and Model Based Predictive Control for Mobile Robot
... the model-based predictive control is not a new control method, works dealing with model-based predictive control and wheeled robots are few and ...generalized predictive control is ...
11
Nonlinear System Identification in Frequent and Infrequent Operating Points for Nonlinear Model Predictive Control
... low nonlinear process up to 1000 for high nonlinear ...[5] model. Indeed, linear model with adaptive dynamic [6] or general nonlinear dynamic model has also been used [8] in some ...
10
EFFICIENT SCHEDULING OF WORKFLOW IN CLOUD ENVIORNMENT USING BILLING MODEL AWARE TASK CLUSTERING
... linear predictive coefficients (LPC), linear predictive cepstral coefficients (LPCC) and Mel-frequency cepstral coefficients ...RBFNN model enables nonlinear transformation followed by linear ...
6
Improving of Crystal Size Distribution Control Based on Neural Network Based Hybrid Model for Purified Terephthalic Acid Batch Crystallizer
... Model Predictive Control (MPC) is one of model based approaches which can handle most common process characteristics and industrial requirements in a satisfactory ...natured nonlinear dynamic ...
13
Hybrid Neural Network Controller Design for a Batch Reactor to Produce Methyl Methacrylate
... problem, neural networks studied and provided successfully to capture the dynamics of nonlinear and complex systems have been proposed and formulated ...[8-13]. Neural networks have several ...
18
Control of a Double -Effect Evaporator using Neural Network Model Predictive Controller
... recurrent neural network-based nonlinear model predictive control (NMPC) scheme in parallel with PI control ...simulation model of an industrial-scale five-stage ...in predictive ...
10
Constrained Nonlinear Model Predictive Control of a Polymerization Process via Evolutionary Optimization
... expert neural network as an internal model in control of solution polymerization of vinyl ...their neural network control with a classic PID ...non-linear model based on control strategy, ...
10
A Neural Network Predictive Model of Pipeline Internal Corrosion Profile
... input-output nonlinear relationship arbitrarily well, given enough hidden neurons: in the present case 20 hidden neurons are demonstrated to obtain the best network ...
6
The Design of Output Feedback Distributed Model Predictive Controller for a Class of Nonlinear Systems
... distributed model predictive control algorithm for interconnected systems based on neighbor-to-neighbor communication is ...distributed model predictive control when the dynamics and ...
19
Comparison between Cascade Forward and Multi-Layer Perceptron Neural Networks for NARX Functional Electrical Stimulation (FES)-Based Muscle Model
... The spinal cord is a collection of nerves that sends commands to muscles to induce movement. Damage to the spinal cord causes paraplegia that results in loss of sensation and voluntary movement. The level of spinal cord ...
7
Stochastic Binary Neural Networks for Qualitatively Robust Predictive Model Mapping
... or model identification, while statistical qualitative robustness for protection against outlier data is sought as ...binary neural networks which imple- ment predictive model mappings in real ...
6
An Improved Stock Price Prediction using Hybrid Market Indicators
... The fundamental variables consist of financial ratios such as price per annual earning (P/E), return on asset (ROA), and return on equity (ROE). P/E is equal to the market price per share of stock divided by the earning ...
12
Determination of the height of destressed zone above the mined panel: An ANN model
... Providing sufficient number of data is an important stage in ANN modeling. In this study, a vast collection of suitable dataset was prepared from the Iranian coalfields and comprehensive literature surveys and the ...
7
An explicit nonlinear model predictive ABS controller for electro-hydraulic braking systems
... explicit nonlinear model predictive controller (eNMPC) for an anti-lock braking system (ABS) for passenger cars, actuated through an electro-hydraulic braking (EHB) ...simulation model is used ...
11
DEVELOPMENT AND APPLICATION OF A STAGE GATE PROCESS TO REDUCE THE UNERLYING RISKS OF IT SERVICE PROJECTS
... a predictive model to diagnosis and associated with the accuracy results with SVM, an NN, a rough set (Rosetta), and logistic ...set model is accurate than the ...affinity predictive ...
10
PSS Tuning of the Combined Cycle Power Station by Neural Network
... Some techniques such as adapted control have been proposals as solution of the problem [5], [6]. However, the most of adapted controls is based on parameters identification on the system model in real time, but it ...
5
Nonlinear System Identification Using Hammerstein-Wiener Neural Network and subspace algorithms
... — Neural networks are applicable in identification from input-output ...block-oriented nonlinear systems where the linear dynamic block is sandwiched in between two static nonlinear blocks, which ...
8