Application of Feedback Linearization to the Controller of CSTR

2014 ◽  
Vol 1049-1050 ◽  
pp. 850-854
Author(s):  
Lan Xiang Zhu ◽  
Zhen Wang ◽  
Ding Li Yu ◽  
Wei Wei Yang ◽  
Lei Gu ◽  
...  
Keyword(s):  
Feedback Linearization ◽  
Dynamic Performance ◽  
Linear Control ◽  
Control Input ◽  
Time Varying ◽  
Continuous Stirred Tank Reactor ◽  
Linear Control Theory ◽  
Control Scheme ◽  
Variable Substitution ◽  
Continuous Stirred Tank

Based on input-output feedback linearization scheme using the theories of differential geometry, this paper designed a controller for the continuous stirred tank reactor system which is a typical nonlinear, multi-variables, time-varying system. First, continuously different the chosen system outputs until control input appear in the expression. Then, overall linearization can be realized by input variable-substitution if some conditions are satisfied. At last, mature linear control theory is used to control the sub linear system stable. Simulation results show that the proposed control scheme is efficient and the system contains good static, dynamic performance.

Signal Synthesis Model Reference Adaptive Controller with Artificial Intelligent Technique for a Control of Continuous Stirred Tank Reactor

2018 ◽  
Vol 17 (2) ◽  
Author(s):  
Harsh Goud ◽  
Pankaj Swarnkar
Keyword(s):  
Steady State ◽  
Stirred Tank ◽  
Continuous Stirred Tank Reactor ◽  
Stirred Tank Reactor ◽  
Tank Reactor ◽  
Design And Implementation ◽  
Control Scheme ◽  
Signal Synthesis ◽  
Continuous Stirred Tank ◽  
The Given

AbstractModelling and controlling of Continuous stirred tank reactor (CSTR) is one of the major problems in the process industry. The nonlinear characteristic of CSTR may change the variation of temperature in either direction from the given set value. Chemical reactions within the CSTR depends on the given reference temperature. Such variation from reference values may result in degrading the variety of biomass. Design and implementation of the precise control device in such system are difficult for researchers. This paper proposes the MIT based control scheme as a solution to control problem of CSTR. An improvement of signal synthesis MIT system has been proposed in this study to enhance the steady-state and transient performance of CSTR. Artificial Bee Colony (ABC) based controller parameter tuning technique is applied to get the optimal performance of the controller. This paper shows the design and implementation of conventional PID tuned with the Z-N method, adaptive PID tune with ABC, MIT and ABC-MIT for CSTR. Detailed comparison based on simulation studies is presented which shows that ABC-MIT based control scheme improves the transient and steady state response.

Design of Gain Scheduled Multivariable Controllers for a Nonlinear Process

2011 ◽  
Vol 403-408 ◽  
pp. 4821-4827 ◽  
Author(s):  
N. Kamala ◽  
T. Thyagarajan ◽  
S. Renganathan
Keyword(s):  
Pid Controller ◽  
Absolute Error ◽  
Nonlinear Process ◽  
Simulation Studies ◽  
Continuous Stirred Tank Reactor ◽  
Control Scheme ◽  
Continuous Stirred Tank ◽  
Dynamic Nonlinearity ◽  
Gain Scheduled ◽  
Operating Points

In this paper, Genetic Algorithm is utilized to optimize the coefficients of a decentralized PID controller for a nonlinear Multi-Input Multi-output process by minimizing the Integral Absolute Error (IAE).The controller is tuned at chosen operating points, which are selected to cover the nonlinear range of the process. The optimal PID controller parameters are gain scheduled using a Fuzzy Gain scheduler. The effectiveness of the proposed control scheme has been demonstrated by conducting simulation studies on a Continuous Stirred Tank Reactor (CSTR) process which exhibits dynamic nonlinearity

scholarly journals Adaptive Neural Control and Modeling for Continuous Stirred Tank Reactor with Delays and Full State Constraints

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Dongjuan Li ◽  
Dongxing Wang ◽  
Ying Gao
Keyword(s):  
Time Delay ◽  
State Constraints ◽  
Stirred Tank ◽  
Time Varying ◽  
Continuous Stirred Tank Reactor ◽  
Stirred Tank Reactor ◽  
Tank Reactor ◽  
Full State ◽  
Continuous Stirred Tank ◽  
Full State Constraints

In this paper, an adaptive neural network control method is described to stabilize a continuous stirred tank reactor (CSTR) subject to unknown time-varying delays and full state constraints. The unknown time delay and state constraints problem of the concentration in the reactor seriously affect the input-output ratio and stability of the entire system. Therefore, the design difficulty of this control scheme is how to debar the effect of time delay in CSTR systems. To deal with time-varying delays, Lyapunov–Krasovskii functionals (LKFs) are utilized in the adaptive controller design. The convergence of the tracking error to a small compact set without violating the constraints can be identified by the time-varying logarithm barrier Lyapunov function (LBLF). Finally, the simulation results on CSTR are shown to reveal the validity of the developed control strategy.

scholarly journals Comparative study of Time Optimal Controller with PID Controller for a Continuous Stirred Tank Reactor

2015 ◽  
Vol 8 (1) ◽  
pp. 27-33 ◽  
Author(s):  
Ayush Sharma ◽  
Miroslav Fikar ◽  
Monika Bakošová
Keyword(s):  
Stirred Tank ◽  
Control Input ◽  
Continuous Stirred Tank Reactor ◽  
Process Industries ◽  
Stirred Tank Reactor ◽  
Tank Reactor ◽  
Time Optimal ◽  
Continuous Stirred Tank ◽  
Non Linear System ◽  
Cstr System

Abstract Continuous Stirred Tank Reactor (CSTR) is the productive part in different chemical and process industries, and hence there is a need to control this process at desired optimum conditions of temperature and concentration. This paper deals with modelling and constrained control of a CSTR that minimises the processing time. Modelling consisted in performing the mass and heat balances of the CSTR system. Different controllers (time optimal, PID) were then applied to this non-linear system and compared within the boundaries of the control input and states. A theoretical case study was solved numerically using the orthogonal collocations method and simulations, resulting in a comparison of different controllers.

Disturbance observer-based formation tracking control of multiple quadrotors in the presence of disturbances

2019 ◽  
Vol 41 (14) ◽  
pp. 4129-4141 ◽  
Author(s):  
Izzuddin M Lazim ◽  
Abdul Rashid Husain ◽  
Zaharuddin Mohamed ◽  
Mohd Ariffanan Mohd Basri ◽  
Nurul Adilla Mohd Subha ◽  
...  
Keyword(s):  
Adverse Effects ◽  
Tracking Control ◽  
Feedback Linearization ◽  
Disturbance Observer ◽  
Formation Flight ◽  
Test Cases ◽  
Control Input ◽  
Simulation Experiments ◽  
Formation Tracking ◽  
Control Scheme

The presence of disturbances may bring adverse effects to the formation flight of multiple quadrotors. This paper proposes a robust disturbance observer-based feedback linearization that enhances the formation tracking control of quadrotors to achieve the desired formation shapes under the effect of disturbances. The method not only retains the simplicity of the control scheme using feedback linearized quadrotor model, but also has the capability to reject the disturbances. This is achieved by introducing a disturbance observer to estimate and attenuate the lumped disturbance that causes inexact inversion in the feedback linearization of the quadrotor. Then, a distributed formation tracking algorithm is adopted to ensure the quadrotors are able to form up and maintain the desired formation shape and heading via local communication between neighbours with respect to a leader that has nonzero control input. To evaluate the effectiveness of the proposed method, simulation experiments of multiple quadrotor formations using the proposed approach are conducted under several test cases. Results obtained demonstrate the superiority of the proposed control scheme for a more robust formation tracking as compared with the formation without the disturbance observer.

Sampled data output regulation of n-link robotic manipulator using a realizable reconstruction filter

Robotica ◽  
2014 ◽  
Vol 34 (4) ◽  
pp. 900-912 ◽  
Author(s):  
Muwahida Liaquat ◽  
Mohammad Bilal Malik
Keyword(s):  
Stability Analysis ◽  
Discrete Time ◽  
Feedback Linearization ◽  
Impulsive System ◽  
Observer Design ◽  
Control Input ◽  
Sampled Data ◽  
Control Scheme ◽  
Reconstruction Filter ◽  
The Stability

SUMMARYThis paper proposes a solution to the sampled-data regulation problem for feedback linearizable n-link robotic manipulators. The prime focus is on the development and stability analysis of the proposed control scheme in the presence of model uncertainties and external disturbances. A major constraint is the availability of sampled measurements of output signal. This leads to designing an impulsive observer for feedback linearization. The discrete-time control input is mapped into its continuous-time counterpart using a realizable reconstruction filter (RRF). The underlying control scheme relies on the sampled-data regulator theory based on the discrete-time equivalence of the plant and RRF modeled as impulsive system. This method leads to controller/observer design in discrete time. The working of the entire scheme is dependent on the stability of impulsive observer; hence a Lyapunov-based stability analysis is also included to ensure the stability of a closed-loop system. The working of the proposed scheme along with a comparison with conventional solution is presented, when applied to the control of a 3-degree-of-freedom PUMA 560 robot.

scholarly journals Fault Detection Approach Based on Weighted Principal Component Analysis Applied to Continuous Stirred Tank Reactor

2015 ◽  
Vol 9 (1) ◽  
pp. 966-972 ◽  
Author(s):  
Shanmao Gu ◽  
Yunlong Liu ◽  
Ni Zhang ◽  
De Du
Keyword(s):  
Principal Component Analysis ◽  
Fault Detection ◽  
Principal Component ◽  
Stirred Tank ◽  
Time Varying ◽  
Continuous Stirred Tank Reactor ◽  
Stirred Tank Reactor ◽  
Tank Reactor ◽  
Detection Approach ◽  
Continuous Stirred Tank

Fault detection approach based on principal component analysis (PCA) may perform not well when the process is time-varying, because it can cause unfavorable influence on feature extraction. To solve this problem, a modified PCA which considering variance maximization is proposed, referred to as weighted PCA (WPCA). WPCA can obtain the slow features information of observed data in time-varying system. The monitoring statistical indices are based on WPCA model and their confidence limits are computed by kernel density estimation (KDE). A simulation example on continuous stirred tank reactor (CSTR) show that the proposed method achieves better performance from the perspective of both fault detection rate and fault detection time than conventional PCA model.

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