DEVELOPMENT OF CONTROLLER AND OBSERVER FOR CONTINUOUS STIRRED TANK REACTOR VIA STATE SPACE APPROACH

iii ABSTRACT This paper describes the designing, simulation and analysis of controller and observer for a continuous stirred tank reactor via state space approach. Many industries uses the conventional control system approach, as opposed to the modern control approach commonly used in aerospace industries. Conventional controls possess several drawbacks, for example PID controllers are not adaptive and not robust. Thus, qualities such as robustness, optimality and adaptivity could have been overlooked. This project is looking at modern control approach for plant control which is expected to be better in terms of the system’s controllability and stability. The entire project involves understanding the process control and state space, grasping the concept of system identification as well as mastering the function of MATLAB and Simulink for controller and observer design and simulation. Extensive utilization of MATLAB and Simulink were involved in several experiments and simulations. Results from the project indicate the practicality of modern control in plant process control system. This project successfully achieved the theoretical implementation of modern control engineering in plant process control systems, paving way for a possible design of a new controller and observer strategy that are robust, optimal and adaptive via modern control approach

Comparison of two identification models used in adaptive control of continuous-stirred tank reactor

The goal of this paper is to compare two identification methods continuous-time and discrete-time. The continuous-time identification model is more accurate but not very suitable for on-line identification. This disadvantage was overcome with the use of differential filters. On the other hand, discrete-time identification model has is more suitable for identification but less accurate. Compromise can be found in the delta model as a special type of the discrete-time model parameters of which are related to the sampling period. The adaptive approach is based on the choice of the External Linear Model, parameters of which are identified recursively which satisfies the adaptivity of this system. Proposed control strategy was applied on the mathematical model of the Continuous Stirred-Tank reactor as a typical nonlinear lumped-parameters system used in the industry

Robust control of continuous stirred tank reactor with jacket cooling

Continuous Stirred-Tank Reactors (CSTR) belong to basic technological equipment frequently used in the the production of various types of chemicals. These systems are quite complex with many nonlinearities. So, the conventional linear control with fixed parameters can be questionable or unacceptable. The solution should be found in so-called “non-traditional” control approaches like Adaptive, Robust, Fuzzy or Artificial Intelligent methods. One way is the utilization of selftuning adaptive schemes but computations are quite difficult, clumsy and time-consuming. This paper brings an alternative principle called robust approach. This approach considers a linear system with parametric uncertainty which covers a family of all feasible plants. Then a controller with fix parameters is designed so that for all possible plants the acceptable control behavior is obtained. The two degree of freedom (2DOF) structure for the control law was chosen. All calculation and simulations of mathematical models and control responses was performed in the Matlab and Simulink environment. Copyright © 2019, AIDIC Servizi S.r.l

Two degrees-of-freedom hybrid adaptive approach with pole-placement method used for control of isothermal chemical reactor

Continuous Stirred-Tank Reactors (CSTR) are technological plants often used in the chemical or biochemical industry for the production of various types of chemicals. These systems are very complex from the control point-of-view - mainly because of their nonlinearity. Controlling such processes by means of conventional methods that use controllers with fixed parameters; often produces bad - or even, unacceptable results. This is the right field for so-called "modern" control methods like Robust, Predictive, and Adaptive Control. The control method used in this work is a hybrid adaptive control where the originally nonlinear system is represented by the external linear model whose parameters are recursively identified during the control phase. The pole-placement method with a spectral factorization and two degrees-of-freedom (2DOF) control configuration used in the control synthesis in order satisfy the basic control requirements, for instance: stability, reference signal tracking and disturbance attenuation. Moreover, the resulting controller obtained from the polynomial synthesis is easily programmable and be implemented in control computers. All of the proposed methods were tested by simulations on a mathematical model of an isothermal CSTR, with a complex reaction inside. The results so obtained, demonstrate the applicability of this control method for these kinds of processes. The team used the MATLAB simulation program in this research. Copyright © 2017, AIDIC Servizi S.r.l.CZ.1.05/2.1.00/03.0089, ERDF, European Regional Development Fund; MOE, Ministry of Educatio

Terminal sliding mode control for continuous stirred tank reactor

© 2014 The Institution of Chemical Engineers. A continuous stirred tank reactor (CSTR) is a typical example of chemical industrial equipment, whose dynamics represent an extensive class of second order nonlinear systems. It has been witnessed that designing a good control algorithm for the CSTR is very challenging due to the high complexity. The two difficult issues in CSTR control are state estimation and external disturbance attenuation. In general, in industrial process control a fast and robust response is essential. Driven by these challenging issues and desired performance, this paper proposes an output feedback terminal sliding mode control (TSMC) framework which is developed for CSTR, and can estimate the system states and stabilize the system output tracking error to zero in a finite time. The corresponding stability analysis is presented in terms of the Lyapunov method. Illustrative examples are demonstrated by using Matlab simulations to validate the effectiveness of the proposed approach

Control of a non-isothermal continuous stirred tank reactor by a feedback–feedforward structure using type-2 fuzzy logic controllers

A control system that uses type-2 fuzzy logic controllers (FLC) is proposed for the control of a non-isothermal continuous stirred tank reactor (CSTR), where a first order irreversible reaction occurs and that is characterized by the presence of bifurcations. Bifurcations due to parameter variations can bring the reactor to instability or create new working conditions which although stable are unacceptable. An extensive analysis of the uncontrolled CSTR dynamics was carried out and used for the choice of the control configuration and the development of controllers. In addition to a feedback controller, the introduction of a feedforward control loop was required to maintain effective control in the presence of disturbances. Simulation results confirmed the effectiveness and the robustness of the type-2 FLC which outperforms its type-1 counterpart particularly when system uncertainties are present

Data-driven Soft Sensors in the Process Industry

In the last two decades Soft Sensors established themselves as a valuable alternative to the traditional means for the acquisition of critical process variables, process monitoring and other tasks which are related to process control. This paper discusses characteristics of the process industry data which are critical for the development of data-driven Soft Sensors. These characteristics are common to a large number of process industry fields, like the chemical industry, bioprocess industry, steel industry, etc. The focus of this work is put on the data-driven Soft Sensors because of their growing popularity, already demonstrated usefulness and huge, though yet not completely realised, potential. A comprehensive selection of case studies covering the three most important Soft Sensor application fields, a general introduction to the most popular Soft Sensor modelling techniques as well as a discussion of some open issues in the Soft Sensor development and maintenance and their possible solutions are the main contributions of this work

Practical modelling and control implementation studies on a pH neutralization process pilot plant

In recent years the industrial application of advanced control techniques for the process industries has become more demanding, mainly due to the increasing complexity of the processes themselves as well as to enhanced requirements in terms of product quality and environmental factors. Therefore the process industries require more reliable, accurate, robust, efficient and flexible control systems for the operation of process plant. In order to fulfil the above requirements there is a continuing need for research on improved forms of control. There is also a need, for a variety of purposes including control system design, for improved process models to represent the types of plant commonly used in industry. Advanced technology has had a significant impact on industrial control engineering. The new trend in terms of advanced control technology is increasingly towards the use of a control approach known as an “intelligent” control strategy. Intelligent control can be described as a control approach or solution that tries to imitate important characteristics of the human way of thinking, especially in terms of decision making processes and uncertainty. It is also a term that is commonly used to describe most forms of control systems that are based on artificial neural networks or fuzzy logic. The first aspect of the research described in the thesis concerns the development of a mathematical model of a specific chemical process, a pH neutralization process. It was intended that this model would then provide an opportunity for the development, implementation, testing and evaluation of an advanced form of controller. It was also intended that this controller should be consistent in form with the generally accepted definition of an “intelligent” controller. The research has been based entirely around a specific pH neutralization process pilot plant installed at the University Teknologi Petronas, in Malaysia. The main feature of interest in this pilot plant is that it was built using instrumentation and actuators that are currently used in the process industries. The dynamic model of the pilot plant has been compared in detail with the results of experiments on the plant itself and the model has been assessed in terms of its suitability for the intended control system design application. The second stage of this research concerns the implementation and testing of advanced forms of controller on the pH neutralization pilot plant. The research was also concerned with the feasibility of using a feedback/feedforward control structure for the pH neutralization process application. Thus the study has utilised this control scheme as a backbone of the overall control structure. The main advantage of this structure is that it provides two important control actions, with the feedback control scheme reacting to unmeasured disturbances and the feedforward control scheme reacting immediately to any measured disturbance and set-point changes. A non-model-based form of controller algorithm involving fuzzy logic has been developed within the context of this combined feedforward and feedback control structure. The fuzzy logic controller with the feedback/feedforward control approach was implemented and a wide range of tests and experiments were carried out successfully on the pilot plant with this type of controller installed. Results from this feedback/feedforward control structure are extremely encouraging and the controlled responses of the plant with the fuzzy logic controller show interesting characteristics. Results obtained from tests of these closed-loop system configurations involving the real pilot plant are broadly similar to results found using computer-based simulation. Due to limitations in terms of access to the pilot plant the investigation of the feedback/feedforward control scheme with other type of controllers such as Proportional plus Integral (PI) controller could not be implemented. However, extensive computer-based simulation work was carried out using the same control scheme with PI controller and the control performances are also encouraging. The emphasis on implementation of advanced forms of control with a feedback/feedforward control scheme and the use of the pilot plant in these investigations are important aspects of the work and it is hoped that the favourable outcome of this research activity may contribute in some way to reducing the gap between theory and practice in the process control field

DEVELOPMENT OF CONTROLLER AND OBSERVER FOR CONTINUOUS STIRRED TANK REACTOR VIA STATE SPACE APPROACH

iii ABSTRACT This paper describes the designing, simulation and analysis of controller and observer for a continuous stirred tank reactor via state space approach. Many industries uses the conventional control system approach, as opposed to the modern control approach commonly used in aerospace industries. Conventional controls possess several drawbacks, for example PID controllers are not adaptive and not robust. Thus, qualities such as robustness, optimality and adaptivity could have been overlooked. This project is looking at modern control approach for plant control which is expected to be better in terms of the system’s controllability and stability. The entire project involves understanding the process control and state space, grasping the concept of system identification as well as mastering the function of MATLAB and Simulink for controller and observer design and simulation. Extensive utilization of MATLAB and Simulink were involved in several experiments and simulations. Results from the project indicate the practicality of modern control in plant process control system. This project successfully achieved the theoretical implementation of modern control engineering in plant process control systems, paving way for a possible design of a new controller and observer strategy that are robust, optimal and adaptive via modern control approach