Nonlinear Model Based Predictive Controller Using a Fuzzy-neural Wiener-hammerstein Model
نویسندگان
چکیده
It is presented in this paper a method for designing a nonlinear model predictive controller. The controller is based on a hybrid Wiener-Hammerstein fuzzy-neural predictive model and а simplified gradient optimization algorithm. The proposed approach is used to control the product temperature in a Lyophlization plant. The controller efficiency is tested and proved by simulation experiments in Matlab & Simulink.
منابع مشابه
Nonlinear System Identification Using Hammerstein-Wiener Neural Network and subspace algorithms
Neural networks are applicable in identification systems from input-output data. In this report, we analyze theHammerstein-Wiener models and identify them. TheHammerstein-Wiener systems are the simplest type of block orientednonlinear systems where the linear dynamic block issandwiched in between two static nonlinear blocks, whichappear in many engineering applications; the aim of nonlinearsyst...
متن کاملHammerstein-Wiener Model: A New Approach to the Estimation of Formal Neural Information
A new approach is introduced to estimate the formal information of neurons. Formal Information, mainly discusses about the aspects of the response that is related to the stimulus. Estimation is based on introducing a mathematical nonlinear model with Hammerstein-Wiener system estimator. This method of system identification consists of three blocks to completely describe the nonlinearity of inp...
متن کاملRejection of the Feed-Flow Disturbances in a Multi-Component Distillation Column Using a Multiple Neural Network Model-Predictive Controller
This article deals with the issues associated with developing a new design methodology for the nonlinear model-predictive control (MPC) of a chemical plant. A combination of multiple neural networks is selected and used to model a nonlinear multi-input multi-output (MIMO) process with time delays. An optimization procedure for a neural MPC algorithm based on this model is then developed. T...
متن کاملFPGA Implementation of a Hammerstein Based Digital Predistorter for Linearizing RF Power Amplifiers with Memory Effects
Power amplifiers (PAs) are inherently nonlinear elements and digital predistortion is a highly cost-effective approach to linearize them. Although most existing architectures assume that the PA has a memoryless nonlinearity, memory effects of the PAs in many applications ,such as wideband code-division multiple access (WCDMA) or orthogonal frequency-division multiplexing (OFDM), can no longer b...
متن کاملIdentification and Control of Nonlinear Systems Using Fuzzy Hammerstein Models
This paper addresses the identification and control of nonlinear systems by means of Fuzzy Hammerstein (FH) models, which consist of a static fuzzy model connected in series with a linear dynamic model. For the identification of nonlinear dynamic systems with the proposed FH models, two methods are proposed. The first one is an alternating optimization algorithm that iteratively refines the est...
متن کامل