nonlinear neural predictive control
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 ...complex control problems in the process ...the control of ...
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Neural predictive control of broiler chicken and pig growth
... Active control of the growth of broiler chickens and pigs has potential ben- efits for farmers in terms of improved production efficiency, as well as for animal welfare in terms of improved leg health in broiler ...
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Design of Model Predictive Control based Direct Neural Controller for Surge Tank Application
... Model predictive control based direct neural controllers represent another class of computer application in the field of non-linear ...parameterized nonlinear controller to approximate an ...
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Learning Based Approximate Model Predictive Control for Nonlinear Systems
... the control law repre- sented in Algorithm 1, we apply a Gaussian process (GP) to approximate the general optimal control ...based neural network, is chosen for this task, because it has a simple, ...
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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 ...in predictive control of the ...while control ...
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Robust predictive tracking control for a class of nonlinear systems
... robust predictive tracking control (RPTC) approach is developed in this paper to deal with a class of nonlinear SISO ...the control performance, the RPTC architecture mainly consists of a ...
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Neural Network Predictive Control of a SOFC Fuelled with Ammonia
... Model Predictive Control (MPC) methods are available in the literature [5-7; 23; 26-28; ...process control methodology. Wu et al. [25] used a predictive controller based on a T–S fuzzy model ...
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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 ...
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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 ...
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Nonlinear System Identification in Frequent and Infrequent Operating Points for Nonlinear Model Predictive Control
... low nonlinear process up to 1000 for high nonlinear ...general nonlinear dynamic model has also been used [8] in some ...a neural network ARX (NARX) model for the ...a nonlinear model ...
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Single Phase Induction Motor Drive with Restrained Speed and Torque Ripples Using Neural Network Predictive Controller
... plants control, to maximize the production rate and to meet sharper specification of product quality ...and control of Industrial Drives (ID) for set point tracking as well as for distur- bance rejection ...
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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 ...temperature control of a semi-batch ...
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Nonlinear Autonomous Altitude Control of a Miniature Helicopter UAV Based on Sliding Mode Methodology
... highly nonlinear, inherently unstable and uncertain mathematical model of a helicopter calls for high degree of autonomy for flight regulations and desired operations in a full flight ...Several control ...
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Nonlinear Multiple Model Predictive Control of Solution Polymerization of Methyl Methacrylate
... Model predictive control (MPC), on the other hand, is a model based advanced control technique that have been proved to be very sussefull in controlling highly complex dynamic ...
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Linear and nonlinear predictive control algorithms applied to a heated tank system
... In this work a number of model based predictive controllers have been designed in order to regulate a (nonlinear) heated tank system. First, two controllers according to the EPSAC algorithm were designed, ...
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Variable neural networks for adaptive control of nonlinear systems
... variable neural network, is proposed in this ...variable neural network is that the number of basis functions in the network can be either increased or decreased over time according to a design strategy in ...
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Nonlinear predictive generalized minimum variance LPV control of wind turbines
... Industrial Control Centre at the University of Strathclyde on Nonlinear Generalised Minimum Variance controllers (supported by the EPSRC) has led to a family of controllers, including predictive ...
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Maximum Wind Energy Extraction by Using Neural Network Estimation and Predictive Control of Boost Converter
... artificial neural network (ANN) is combined with particle swarm optimization (PSO) to use the max- imum power point tracking (MPPT) by controlling the rotor speed of the wind ...
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Research of adaptive control algorithm research based on rough set and implementation
... adaptive control is that the uncertainty of the system, so this control should be the first to run in the process control system, by continuously measured system input, state, or output parameters, ...
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State-space approach to nonlinear predictive generalized minimum variance control
... PGMV Optimal Controller Consider the linear components of the plant, disturbance and output weighting models in state space form 2, 3 with input from the nonlinear finite gain stable pla[r] ...
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