scholarly journals Model Predictive Control Based on Kalman Filter for Constrained Hammerstein-Wiener Systems

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Man Hong ◽  
Shao Cheng
Keyword(s):  
Kalman Filter ◽  
Predictive Control ◽  
Output Feedback Control ◽  
Continuous Stirred Tank Reactor ◽  
Reaction Heat ◽  
State Observation ◽  
Wiener Systems ◽  
Linear Subsystem ◽  
Continuous Stirred Tank ◽  
Actual Control

To precisely track the reactor temperature in the entire working condition, the constrained Hammerstein-Wiener model describing nonlinear chemical processes such as in the continuous stirred tank reactor (CSTR) is proposed. A predictive control algorithm based on the Kalman filter for constrained Hammerstein-Wiener systems is designed. An output feedback control law regarding the linear subsystem is derived by state observation. The size of reaction heat produced and its influence on the output are evaluated by the Kalman filter. The observation and evaluation results are calculated by the multistep predictive approach. Actual control variables are computed while considering the constraints of the optimal control problem in a finite horizon through the receding horizon. The simulation example of the CSTR tester shows the effectiveness and feasibility of the proposed algorithm.

Model predictive control of a CSTR: A hybrid modeling approach

2010 ◽  
Vol 64 (3) ◽  
Author(s):  
Michal Kvasnica ◽  
Martin Herceg ◽  
Ľuboš Čirka ◽  
Miroslav Fikar
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Linear Models ◽  
Nonlinear Behavior ◽  
Continuous Stirred Tank Reactor ◽  
Modeling Framework ◽  
Future Evolution ◽  
Continuous Stirred Tank ◽  
Traditional Approaches

AbstractThis paper presents a case study of model predictive control (MPC) applied to a continuous stirred tank reactor (CSTR). It is proposed to approximate nonlinear behavior of a plant by several local linear models, enabling a piecewise affine (PWA) description of the model used to predict and optimize future evolution of the reactor behavior. Main advantage of the PWA model over traditional approaches based on single linearization is a significant increase of model accuracy which leads to a better control quality. It is also illustrated that, by adopting the PWA modeling framework, MPC strategy can be implemented using significantly less computational power compared to nonlinear MPC setups.

Applying GP-EKF and GP-SCKF for non-linear state estimation and fault detection in a continuous stirred-tank reactor system

2016 ◽  
Vol 39 (10) ◽  
pp. 1486-1496 ◽  
Author(s):  
Elham Kowsari ◽  
Behrooz Safarinejadian
Keyword(s):  
Kalman Filter ◽  
Fault Detection ◽  
Gaussian Process ◽  
Stirred Tank ◽  
Square Root ◽  
Continuous Stirred Tank Reactor ◽  
Tank Reactor ◽  
Cubature Kalman Filter ◽  
Non Linear ◽  
Continuous Stirred Tank

This paper proposes two novel methods for fault detection in non-linear processes. These methods apply a Gaussian process (GP) to model the underlying process, and then the extended Kalman filter (EKF) and square root cubature Kalman filter (SCKF) are used to detect faults. Accordingly, two approaches called the Gaussian process–extended Kalman filter (GP-EKF) and Gaussian process–square root cubature Kalman filter (GP-SCKF) are proposed. The most important characteristic of these proposed methods is that there is no need for an accurate model of the system. Therefore, these methods are considered non-parametric approaches of fault detection in non-linear systems. To illustrate the performance of these algorithms in fault detection, they have been used in a continuous stirred-tank reactor system (CSTR). Both proposed methods are able to detect sensor faults at an early stage.

Sliding-mode Observer for Uncertainty Estimation in a Class of Chemical Reactor: A Differential-Algebraic Approach

2007 ◽  
Vol 2 (3) ◽  
Author(s):  
Ricardo Aguilar-López
Keyword(s):  
Sliding Mode ◽  
Algebraic Approach ◽  
Chemical Reactor ◽  
Uncertainty Estimation ◽  
Temperature Measurements ◽  
Continuous Stirred Tank Reactor ◽  
Reaction Heat ◽  
On Line ◽  
Continuous Stirred Tank ◽  
Noisy Measurements

The problem of the on-line estimation of the reaction heat in a continuous stirred tank reactor from temperature measurements is addressed in this paper. The proposed uncertainty observer is based on differential algebraic techniques, such that the algebraic observability condition of the uncertainty from noisy temperature measurements is easily verified and the observer structure is very simple, which lead to feasible implementation. The observer proposed is robust against noisy measurements and sustained disturbances. The good performance of the observer is shown by means of numerical simulations and is compared with a nonlinear Luenberger-type observer.

scholarly journals Pole Placement-Based NMPC of Hammerstein Systems and Its Application to Grade Transition Control of Polypropylene

2012 ◽  
Vol 2012 ◽  
pp. 1-6
Author(s):  
He De-Feng ◽  
Yu Li
Keyword(s):  
Predictive Control ◽  
Pole Placement ◽  
Hammerstein Systems ◽  
Transition Control ◽  
Intermediate Variable ◽  
Grade Transition ◽  
Linear Controller ◽  
Control Actions ◽  
Linear Subsystem ◽  
Actual Control

This paper presents a new nonlinear model predictive control (MPC) algorithm for Hammerstein systems subject to constraints on the state, input, and intermediate variable. Taking no account of constraints, a desired linear controller of the intermediate variable is obtained by applying pole placement to the linear subsystem. Then, actual control actions are determined in consideration of constraints by online solving a finite horizon optimal control problem, where only the first control is calculated and others are approximated to reduce the computational demand. Moreover, the asymptotic stability can be guaranteed in certain condition. Finally, the simulation example of the grade transition control of industrial polypropylene plants is used to demonstrate the effectiveness of the results proposed here.

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