Multiple Model Based Adaptive Control for Shell and Tube Heat Exchanger Process
|
|
- Polly Andrews
- 6 years ago
- Views:
Transcription
1 Multiple Model Based Adaptive Control for Shell and Tube Heat Exchanger Process R. Manikandan Assistant Professor, Department of Electronics and Instrumentation Engineering, Annamalai University, Annamalai Nagar, Chidambaram, Tamil Nadu, India. R. Vinodha Associate Professor, Department of Electronics and Instrumentation Engineering, Annamalai University, Annamalai Nagar, Chidambaram, Tamil Nadu, India. Abstract Shell and Tube heat exchanger system (STHX) is widely used in food processing and chemical industries because it can sustain wide range of temperature and pressure. The main purpose is to exchange heat between hot and cool fluid. The designed controllers will regulate the temperature of outlet fluid to a desired set point in the shortest possible time irrespective of load and process disturbances, equipment saturation and nonlinearity. Due to nonlinear nature, shell and tube heat exchanger system is hard to model and control using conventional methods. Conventional controllers may not give efficient control over process as heat exchange influenced by operating point shifts and disturbances. To accommodate linear controllers with such drawbacks, multiple model strategy has been used. This paper proposes multiple model based PID and multiple model based MRAC control for a nonlinear STHX process. Closed loop control is implemented on the chosen process in simulation using Matlab. The controllers are subjected to both reference tracking and disturbance rejection. Keywords: Shell and Tube heat exchanger, conventional Proptional Integral Derivative controller (PID), Model Reference Adaptive Controller (MRAC), multiple models. Introduction Heat Exchanger works in the principle of three methods conduction, convection, and radiation. Heat exchanger is widely used in areas like chemical, food perseverating, energy production, etc. STHX process has its own nonlinearity and component added non-linearity, hence a challenge is faced in the control aspect. Controlling the outlet hot-water temperature by manipulating cold water inflow is difficult because heating and cooling a material will cause change in its gain and time constant. It is observed in literature that STHX hot water outlet temperature is controlled widely by intelligent and adaptive controllers [6]. In the process industries, model predictive control and Internal Model Control (IMC) have been widely accepted for set-point tracking and overcoming plant model mismatch. Many literatures have reported for system design of STHX. [2] However, only few literature have addressed about mathematical modelling developed from first principle method and control point of view. Simulation studies are presented with conventional fuzzy logic controller for STHX process for a linear range [1]. The detailed study and implementation of hybrid fuzzy logic controller for shell and tube heat exchanger is presented literature [1]. Also the above shell and tube heat exchanger has been addressed in optimization of membership functions and fuzzy rules based on genetic algorithm, Ant colony algorithm and PSO method [2]. All the above literature survey deals, control of STHX process only for a linear range and hence there is a motivation to extend the operating range of the STHX process by multiple model approach [3]. Linear control strategy is simple to design, but it fails as shift in operating point or disturbance effect is severe To utilize the advantages of linear controllers multiple model based techniques have been proposed. The multiple model schemes in the literature pave the way to use local controllers efficiently. In the work of Prakash et. al, [3] multiple model concept has been utilized for single input single output CSTR process. The same concept is utilized for the proposed work via PID control and MRAC. Shell and Tube Heat Exchanger A STHX [4], [13] consists of a bundle of tubes enclosed within a cylindrical shell. One fluid flows through the tubes and second fluid flows within the space between the tubes and the shell. Heat is thus transferred from one fluid to the other through the tube walls, either from tube side to shell side or vice versa shown in Figure 1. In this proposed work, water is taken as the medium for both shell and tube. The water is raised to a certain temperature in the process tank using thyristor drivers and this hot water is allowed to flow through the tubes where as shell carries the water in room temperature. The hot and cold water inflow to the shell and tubes are manipulated using pneumatic control valves. RTD is used as temperature sensors at places of hot and cold water inlet and outlet. The hot water outlet temperature of tubes is the variable to be controlled, by manipulating the cold water flow to the shell. Differential Pressure Transmitter (DPT) is used for sensing the flow. 3175
2 Figure 3: Exchange of heat in co-current and counter current mode. Figure 1: Piping and Instrumentation diagram of Shell and Tube Heat Exchanger (STHX). The direction of flow of hot and cold water decides the operation of STHX process to lie in co-current or counter current mode. If flow in shell and tubes are in same direction the mode is said to be co-current mode and counter current for opposite direction of flow as stated in Figure 2. The exchange of heat between shell and tube [13] are shown in Figure 3 for co-current and counter current mode. Energy Balance Equation The energy balance for shell and tube [4] are given in equation (1) and (2) respectively with specification listed in Table 1. Shell Side: ρ s c s v s dt h s A * co m T s s c s (T ci co ) (T ho T co ) N dt N TUBE SIDE ρ c v dt t t t ho h tat * m c (T T ) (T T ) N dt t t hi ho co (2) ho N (1) Table 1: Parameter specifications of the STHX process at nominal operating point. Inputs Value Units Density of water ( s ρ t ) 1000 Kg/m 3 Specific Heat Capacity of water (cs,ct ) 4230 J/kg C Shell Heat Transfer Area ( As ) m 2 Tube Heat Transfer Area ( At ) m 2 Shell side volume ( vs ) X 10 m 3 Tube side volume ( v t ) X 10 m 3 Heat transfer coefficient of Shell ( hs ) 2162 W/m 2 o C Heat transfer coefficient of Tube ( h t ) 2162 W/m 2 o C Mass flow rate of cold water m ) Kg/s ( s Mass flow rate of hot water m ) Kg/s ( t Cold water inlet temp ( Tci ) 33 o C Hot water inlet temp ( Thi ) 55 o C Number of control volume (N) 10 NA Figure 2: Co-current and Counter current modes of STHX. White Box Modelling The experiment has been carried out in co-current mode. To observe the model of the process, the hot water of tubes is maintained at a nominal temperature. Then a small step change in cold water inflow rate is given, both in positive and 3176
3 negative directions to obtain respective reaction curves, as shown in Figure 4. The open loop parameters like process gain Kp, time constant τ and time delay td are obtained from the reaction curves[15], [16]. The closed loop parameters are calculated from the open loop parameters using ZN tuning method. To design multiple model based controller [5], [6], [8], the above procedure is repeated at four different operating points and parameters are listed in Table 2. The Z-N tuning parameters are given in equation (3), (4) and (5). Controller gain 1.2τ K (3) c td *Kp Integral time Ti 2* t d (4) Derivative time Td 0.5 * t d (5) controller PID parameters. Figure 7 shows the closed loop response of STHX process with MM-PID controller. Figure 5: Block diagram of Multiple Model (MM)-PID Controller for STHX within all operating region. Table 3 gives the performance indices of MM-PID for STHX process. It has been observed that setting time is very high and hence there is need for model based approach like Model Reference Adaptive Control (MRAC) [12], [17]. Figure 4: Open loop responses of STHX at different operating regions. Table 2: Open loop and close loop controller parameters at different operating regions. Operating Hot water Zone outlet Temperature o C Process parameters PID Controller Parameters Kp τ td Kc TI TD to to to to to to to to Multiple Model PID Controller (MM-PID) In this work, multiple model based control scheme MM-PID has been proposed for the STHX process. The multiple model based control system consists of a family local linear PID controllers and a scheduler [9], [14], [15], is shown in Figure 6. At each sampling instant the scheduler will assign weights to each local controller and the weighted sum of the outputs will be applied as input to the plant. Table 2 provides the local Figure 6: Servo response of MM-PID controller. Table 3: Performance indices of MM-PID controller Sampling Instants to to to to Ts ISE IAE Multiple Model Adaptive Controller The Model Reference Adaptive Control strategy [12], [17] is used to design the adaptive controller that works on the principle of adjusting the controller parameters θ 1 and θ 2. This adjustment is done by adaptation of gain-γ and γ, so that the output of the plant tracks the output of a reference model having to minimize the error. E=T ho (t) T ho m (t). Hence the cost function J, can be minimized [9], [10], [17]. In the proposed work, Multiple Model MRAC (MM-MRAC) for STHX process, the reference model is tend to be selected 3177
4 based on operating point changes. The block diagram of Multi Model MRAC is shown in Figure 7, where Lyapunov type bypasses the filter that MIT rule has. The equations related with MRAC are given from equations (6) to (10). The servo response of MM-MRAC (with Lyapunov and MIT rule) is shown in Figure 8 with respective manipulated cold water flow. Table 4, gives the performance measure of STHX process for set point change in hot water outlet of tubes. MM- MRAC (with MIT rule) performs better than MM-MRAC (Lyapunov) since it has better setting time with minimum ISE and IAE values. Plant equation: T ho (t) = STHX equ (m S(t)) (6) W n 2 Model equation: T m ho (t) S 2 +2δW n +W 2 (m n S(t)) (7) Controller: (m S(t)) = θ 1 sp(t) θ 2 T ho (t) (8) E= T ho (t) T ho m (t) (9) The control law to minimize error between plant and model is, d ( γ dt m S(t) = { sp(t) [T ho (t) T ho m (t)]sp(t) ) d ( γ T dt ho (t) [T ho (t) T ho m (t)]t ho (t) ) } (10) Where θ 1, θ 2 are updating parameters and γ is the adaptation gain Figure 7: Block diagram representation of MM-MRAC [Lyapunov & MIT] Controller for STHX process. A clear enlarged vision for large range of hot water outlet temperature servo response of 3. 5 O C tracking is shown in figure 9. Figure 9: Servo response of MM-MRAC [Lyapunov & MIT] Controller showing clear vision between 230 to 300 samples. Table 4: Performance indices for servo response of STHX process (MM-MRAC Lyapunov & MIT). Sampling Instants 75 to to to to 349 MM-MRAC %Mp LYAPUNOV Ts ISE IAE MM-MRAC %Mp MIT Ts ISE IAE Regulatory Responses The hot water outlet temperature can be disturbed by changing the flow rate and temperature of tubes hot water [refer Figure 10 and 11]. The servo regulatory response [refer Figure 12] has been obtained for STHX process by increasing the flow rate to Kg/sec from its nominal of Kg/sec (at 300 th sec) and decreasing the temperature to 54 O C from its nominal of 55 O C (at 400 th sec). The clear vision of above said servo regulatory response is made in Figure 13. Similarly Figure 14 gives the vision of decrease in flow rate (at 600 th sec) by Kg/sec to its nominal value of Kg/sec and increase in temperature by 3. 5 O C from its nominal of 54 O C (at 700 th sec). Figure 8: Servo responses of sampling instants MM-MRAC [Lyapunov & MIT] Controller. Figure 10: Block diagram representation for disturbed by changing the flow rate and temperature of tubes hot water inlet. 3178
5 Figure 11: Response for representation of disturbance by changing the temperature and the flow rate of tubes hot water inlet. Figure 14: Regulatory responses of Inflow 600) and temperature 700) for MM-MRAC [Lyapunov & MIT] Controller for STHX. Table 5 gives the performance measure of servo-regulatory response of STHX process. The values from Table 5 infer that MM-MRAC (MIT) performs better in both possibilities of disturbance namely increasing the flow rate and decreasing the temperature of inlet hot water tubes and vice-versa. Table 5: Performance indices for regulatory response of STHX process (MM-MRAC Lyapunov & MIT). Figure 12: Servo & Regulatory responses for all operating region of MM-MRAC [Lyapunov & MIT] Controller for STHX. Time in sec and 299 to to To To 799 Regulatory In Flow disturbance temperature dist O C 3. 5 O C Lit/Sec Lit/Sec MM-MRAC %Mp LYAPUNOV ts ISE IAE MM-MRAC %Mp MIT ts ISE IAE Conclusion In this paper, an attempt has been made to control the STHX process over a wide operating temperature with multiple model approach the simulation utilizing differential equation model of STHX process reveals that MM-MRAC [Lyapunov & MIT] gives better performance with good setpoint tracking and disturbance rejection. Reference Figure 13: Regulatory responses of Inflow (@ 300) and temperature (@ 400) for MM-MRAC [Lyapunov & MIT] Controller for STHX. [1] Venkatesan, N. Sivakumaran, N and Sivashanmuguham, P, Experimental Study of Temperature Control using Soft Computing, International Journal of Computer Applications ( ) Volume 52-No. 9, August 2012, pp. 1-6,
6 [2] Sivakumar, P, Prabhakaran, D and Kannadasan, T, Temperature Control of Shell and Tube Heat Exchanger by Using Intelligent Controllers-Case Study, International Journal Of Computational Engineering Research, vol. 2, pp , [3] Vinodha, R, Lincoln, S, A and Prakash, J, Multiple Model and Neural based Adaptive Multi-loop PID Controller for a CSTR Process, International Journal of Electrical and Electronics Engineering, [4] Manikandan, R, Sivaraman, E, Arulselvi, S, Md. Shabuilla, Neuro modeling of shell and tube heat exchanger, International conference on challenges in Biotechnology and food technology, pp , Annamalai University., Chidambaram, Jan 9-10, [5] Tan, W., Marquez, H. J., Chen, T., & Liu, J. Multimodel analysis and controller design for nonlinear processes, Computers and Chemical Engineering, Vol 28, pp , [6] Manikandan. R;Vinodha. R; Lincoln. S, A; Prakash. J; Design and Simulation of Model based Controller for 2X2 CSTR Process,, IEEE Xplore Digital Library, doi /ICGCEE , pp. 1-7, 2014 [7] Dougherty, D and Cooper, D, A practical multiple model adaptive strategy for single-loop MPC, Control Eng. Pract., vol. 11, no. 2, pp , [8] Dhanalakshmi, R and Vinodha, R, Design of control schemes to adapt PI controller for conical tank process, International Journal Advance Soft Computing its Application., vol. 5, no. 3, pp. 1-20, [9] Wang, R and Safonov, M. G, Stability of unfalsified adaptive control using multiple controllers, Proc. 2005, American Control Conference., pp , 8-10 june [10] Sukumar Kamalasan, Adel. a. Ghandakly, Khail. Al. olimat, A fuzzy logic based multiple reference model adaptive control, Journal Control and Intelligent Systems, Volume 36, Issue 2, [11] Ahmad, M. A., Ishak, A. A, Ismail, N. K., New hybrid model reference adaptive supervisory fuzzy logic controller for shell and tube heat exchanger temperature system, in Control and System Graduate Research colloquium (ICSGRC), IEEE, doi /ICSGRC , pp , July [12] Roffel, B and Betlem, B. H, Process dynamics and control: modeling for control and prediction Wiley [13] John. H. Lienhard. IV/ John. H. Lienhard V, A heat transfer text book, third edition, Phlogiston Press., vol., 10. no., 1., [14] Astolfi. A, Karagiannis. D, and Ortega. R, Nonlinear and adaptive control with applications. London: Springer-Verlag, [15] Padmasree, R. and Chidambaram. M, Control of unstable System Narosa Publications, ISBN, , [16] Wayne Bequette. B. Process Control, Modeling Design and Simulation. Prentice Hall of India, First Edition [17] Karl J. Astrom, Adaptive Control, Pearson education, Second Edition,
PROPORTIONAL-Integral-Derivative (PID) controllers
Multiple Model and Neural based Adaptive Multi-loop PID Controller for a CSTR Process R.Vinodha S. Abraham Lincoln and J. Prakash Abstract Multi-loop (De-centralized) Proportional-Integral- Derivative
More informationControl Of Heat Exchanger Using Internal Model Controller
IOSR Journal of Engineering (IOSRJEN) e-issn: 2250-3021, p-issn: 2278-8719 Vol. 3, Issue 7 (July. 2013), V1 PP 09-15 Control Of Heat Exchanger Using Internal Model Controller K.Rajalakshmi $1, Ms.V.Mangaiyarkarasi
More informationDesign and Comparative Analysis of Controller for Non Linear Tank System
Design and Comparative Analysis of for Non Linear Tank System Janaki.M 1, Soniya.V 2, Arunkumar.E 3 12 Assistant professor, Department of EIE, Karpagam College of Engineering, Coimbatore, India 3 Associate
More informationSensors & Transducers 2015 by IFSA Publishing, S. L.
Sensors & Transducers 2015 by IFSA Publishing, S. L. http://www.sensorsportal.com Multi-Model Adaptive Fuzzy Controller for a CSTR Process * Shubham Gogoria, Tanvir Parhar, Jaganatha Pandian B. Electronics
More informationCHAPTER 7 MODELING AND CONTROL OF SPHERICAL TANK LEVEL PROCESS 7.1 INTRODUCTION
141 CHAPTER 7 MODELING AND CONTROL OF SPHERICAL TANK LEVEL PROCESS 7.1 INTRODUCTION In most of the industrial processes like a water treatment plant, paper making industries, petrochemical industries,
More informationEnhanced Fuzzy Model Reference Learning Control for Conical tank process
Enhanced Fuzzy Model Reference Learning Control for Conical tank process S.Ramesh 1 Assistant Professor, Dept. of Electronics and Instrumentation Engineering, Annamalai University, Annamalainagar, Tamilnadu.
More informationCHAPTER 3 TUNING METHODS OF CONTROLLER
57 CHAPTER 3 TUNING METHODS OF CONTROLLER 3.1 INTRODUCTION This chapter deals with a simple method of designing PI and PID controllers for first order plus time delay with integrator systems (FOPTDI).
More informationDesign of Model based controller for Two Conical Tank Interacting Level systems
International OPEN ACCESS Journal Of Modern Engineering Research (IJMER) Design of Model based controller for Two Conical Tank Interacting Level systems S. Vadivazhagi 1, Dr. N. Jaya 1 (Department of Electronics
More informationInternational Journal of ChemTech Research CODEN (USA): IJCRGG ISSN: Vol.7, No.4, pp ,
International Journal of ChemTech Research CODEN (USA): IJCRGG ISSN: 0974-4290 Vol.7, No.4, pp 1843-1848, 2014-2015 Nonlinear Block-Box Modelling And Control A Shell And Tube Heat Exchanger Using Generalized
More informationExperimental Investigations on Fractional Order PI λ Controller in ph Neutralization System
IJCTA, 8(3), 2015, pp. 867-875 International Science Press Experimental Investigations on Fractional Order PI λ Controller in ph Neutralization System B. Meenakshipriya, M. Prakash and C. Maheswari Abstract:
More informationInternational Journal of ChemTech Research CODEN (USA): IJCRGG ISSN: Vol.8, No.4, pp , 2015
International Journal of ChemTech Research CODEN (USA): IJCRGG ISSN: 0974-4290 Vol.8, No.4, pp 1742-1748, 2015 Block-Box Modelling and Control a Temperature of the Shell and Tube Heatexchanger using Dynamic
More informationECE Introduction to Artificial Neural Network and Fuzzy Systems
ECE 39 - Introduction to Artificial Neural Network and Fuzzy Systems Wavelet Neural Network control of two Continuous Stirred Tank Reactors in Series using MATLAB Tariq Ahamed Abstract. With the rapid
More informationProcess Control Hardware Fundamentals
Unit-1: Process Control Process Control Hardware Fundamentals In order to analyse a control system, the individual components that make up the system must be understood. Only with this understanding can
More informationSimulation based Modeling and Implementation of Adaptive Control Technique for Non Linear Process Tank
Simulation based Modeling and Implementation of Adaptive Control Technique for Non Linear Process Tank P.Aravind PG Scholar, Department of Control and Instrumentation Engineering, JJ College of Engineering
More informationIntroduction to Heat and Mass Transfer
Introduction to Heat and Mass Transfer Week 16 Merry X mas! Happy New Year 2019! Final Exam When? Thursday, January 10th What time? 3:10-5 pm Where? 91203 What? Lecture materials from Week 1 to 16 (before
More informationDesign of Decentralised PI Controller using Model Reference Adaptive Control for Quadruple Tank Process
Design of Decentralised PI Controller using Model Reference Adaptive Control for Quadruple Tank Process D.Angeline Vijula #, Dr.N.Devarajan * # Electronics and Instrumentation Engineering Sri Ramakrishna
More informationH-Infinity Controller Design for a Continuous Stirred Tank Reactor
International Journal of Electronic and Electrical Engineering. ISSN 974-2174 Volume 7, Number 8 (214), pp. 767-772 International Research Publication House http://www.irphouse.com H-Infinity Controller
More informationPerformance Analysis of ph Neutralization Process for Conventional PI Controller and IMC Based PI Controller
IJIRST International Journal for Innovative Research in Science & Technology Volume 3 Issue 01 June 2016 ISSN (online): 2349-6010 Performance Analysis of ph Neutralization Process for Conventional PI Controller
More informationEEE 550 ADVANCED CONTROL SYSTEMS
UNIVERSITI SAINS MALAYSIA Semester I Examination Academic Session 2007/2008 October/November 2007 EEE 550 ADVANCED CONTROL SYSTEMS Time : 3 hours INSTRUCTION TO CANDIDATE: Please ensure that this examination
More informationDynamics and Control of Double-Pipe Heat Exchanger
Nahrain University, College of Engineering Journal (NUCEJ) Vol.13 No.2, 21 pp.129-14 Dynamics and Control of Double-Pipe Heat Exchanger Dr.Khalid.M.Mousa Chemical engineering Department Nahrain University
More informationFeedback Control of Linear SISO systems. Process Dynamics and Control
Feedback Control of Linear SISO systems Process Dynamics and Control 1 Open-Loop Process The study of dynamics was limited to open-loop systems Observe process behavior as a result of specific input signals
More informationMODELLING AND REAL TIME CONTROL OF TWO CONICAL TANK SYSTEMS OF NON-INTERACTING AND INTERACTING TYPE
MODELLING AND REAL TIME CONTROL OF TWO CONICAL TANK SYSTEMS OF NON-INTERACTING AND INTERACTING TYPE D. Hariharan, S.Vijayachitra P.G. Scholar, M.E Control and Instrumentation Engineering, Kongu Engineering
More informationControl of Neutralization Process in Continuous Stirred Tank Reactor (CSTR)
Control of Neutralization Process in Continuous Stirred Tank Reactor (CSTR) Dr. Magan P. Ghatule Department of Computer Science, Sinhgad College of Science, Ambegaon (Bk), Pune-41. gmagan@rediffmail.com
More informationT718. c Dr. Md. Zahurul Haq (BUET) HX: Energy Balance and LMTD ME 307 (2018) 2/ 21 T793
HX: Energy Balance and LMTD Dr. Md. Zahurul Haq Professor Department of Mechanical Engineering Bangladesh University of Engineering & Technology (BUET) Dhaka-000, Bangladesh http://zahurul.buet.ac.bd/
More informationNonlinearControlofpHSystemforChangeOverTitrationCurve
D. SWATI et al., Nonlinear Control of ph System for Change Over Titration Curve, Chem. Biochem. Eng. Q. 19 (4) 341 349 (2005) 341 NonlinearControlofpHSystemforChangeOverTitrationCurve D. Swati, V. S. R.
More informationModelling and Simulation of Interacting Conical Tank Systems
ISSN: 39-8753 (An ISO 397: 007 Certified Organization) Vol. 3, Issue 6, June 04 Modelling and Simulation of Interacting Conical Tank Systems S.Vadivazhagi, Dr.N.Jaya Assistant Professor, Department of
More informationClass 27: Block Diagrams
Class 7: Block Diagrams Dynamic Behavior and Stability of Closed-Loop Control Systems We no ant to consider the dynamic behavior of processes that are operated using feedback control. The combination of
More informationCHBE320 LECTURE XI CONTROLLER DESIGN AND PID CONTOLLER TUNING. Professor Dae Ryook Yang
CHBE320 LECTURE XI CONTROLLER DESIGN AND PID CONTOLLER TUNING Professor Dae Ryook Yang Spring 2018 Dept. of Chemical and Biological Engineering 11-1 Road Map of the Lecture XI Controller Design and PID
More informationImproved Identification and Control of 2-by-2 MIMO System using Relay Feedback
CEAI, Vol.17, No.4 pp. 23-32, 2015 Printed in Romania Improved Identification and Control of 2-by-2 MIMO System using Relay Feedback D.Kalpana, T.Thyagarajan, R.Thenral Department of Instrumentation Engineering,
More informationANFIS Gain Scheduled Johnson s Algorithm based State Feedback Control of CSTR
International Journal of Computer Applications (975 8887) ANFIS Gain Scheduled Johnsons Algorithm based State Feedback Control of CSTR U. Sabura Banu Professor, EIE Department BS Abdur Rahman University,
More informationDesign of Controller using Variable Transformations for a Two Tank Conical Interacting Level Systems
Design of Controller using Variable Transformations for a Two Tank Conical Interacting Level Systems S. Vadivazhagi Department of Instrumentation Engineering Annamalai University Annamalai nagar, India
More informationKeywords - Integral control State feedback controller, Ackermann s formula, Coupled two tank liquid level system, Pole Placement technique.
ISSN: 39-5967 ISO 9:8 Certified Volume 3, Issue, January 4 Design and Analysis of State Feedback Using Pole Placement Technique S.JANANI, C.YASOTHA Abstract - This paper presents the design of State Feedback
More informationModeling and Control of Chemical Reactor Using Model Reference Adaptive Control
Modeling and Control of Chemical Reactor Using Model Reference Adaptive Control Padmayoga.R, Shanthi.M 2, Yuvapriya.T 3 PG student, Dept. of Electronics and Instrumentation, Valliammai Engineering College,
More informationFault Detection and Diagnosis for a Three-tank system using Structured Residual Approach
Fault Detection and Diagnosis for a Three-tank system using Structured Residual Approach A.Asokan and D.Sivakumar Department of Instrumentation Engineering, Faculty of Engineering & Technology Annamalai
More informationA Tuning of the Nonlinear PI Controller and Its Experimental Application
Korean J. Chem. Eng., 18(4), 451-455 (2001) A Tuning of the Nonlinear PI Controller and Its Experimental Application Doe Gyoon Koo*, Jietae Lee*, Dong Kwon Lee**, Chonghun Han**, Lyu Sung Gyu, Jae Hak
More informationDESIGN OF FUZZY ESTIMATOR TO ASSIST FAULT RECOVERY IN A NON LINEAR SYSTEM K.
DESIGN OF FUZZY ESTIMATOR TO ASSIST FAULT RECOVERY IN A NON LINEAR SYSTEM K. Suresh and K. Balu* Lecturer, Dept. of E&I, St. Peters Engg. College, affiliated to Anna University, T.N, India *Professor,
More informationModeling of Hydraulic Control Valves
Modeling of Hydraulic Control Valves PETR CHALUPA, JAKUB NOVAK, VLADIMIR BOBAL Department of Process Control, Faculty of Applied Informatics Tomas Bata University in Zlin nam. T.G. Masaryka 5555, 76 1
More informationDesign and Implementation of Controllers for a CSTR Process
Design and Implementation of Controllers for a CSTR Process Eng. Muyizere Darius, Dr. S. Sivagamasundari Dept. of M.Sc (EI), Annamalai University, Cuddalore. Abstract Continuous Stirred Tank Reactor (CSTR)
More informationDesign of Decentralized Fuzzy Controllers for Quadruple tank Process
IJCSNS International Journal of Computer Science and Network Security, VOL.8 No.11, November 2008 163 Design of Fuzzy Controllers for Quadruple tank Process R.Suja Mani Malar1 and T.Thyagarajan2, 1 Assistant
More informationSoft Computing Technique and Conventional Controller for Conical Tank Level Control
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol. 4, No. 1, March 016, pp. 65~73 ISSN: 089-37, DOI: 10.11591/ijeei.v4i1.196 65 Soft Computing Technique and Conventional Controller
More informationCHAPTER 13: FEEDBACK PERFORMANCE
When I complete this chapter, I want to be able to do the following. Apply two methods for evaluating control performance: simulation and frequency response Apply general guidelines for the effect of -
More informationModel Predictive Control For Interactive Thermal Process
Model Predictive Control For Interactive Thermal Process M.Saravana Balaji #1, D.Arun Nehru #2, E.Muthuramalingam #3 #1 Assistant professor, Department of Electronics and instrumentation Engineering, Kumaraguru
More informationDesign and Implementation of Two-Degree-of-Freedom Nonlinear PID Controller for a Nonlinear Process
IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE) e-issn: 2278-1676,p-ISSN: 23-3331, Volume 9, Issue 3 Ver. III (May Jun. 14), PP 59-64 Design and Implementation of Two-Degree-of-Freedom
More informationEXAMINATION INFORMATION PAGE Written examination
EXAMINATION INFORMATION PAGE Written examination Course code: Course name: PEF3006 Process Control Examination date: 30 November 2018 Examination time from/to: 09:00-13:00 Total hours: 4 Responsible course
More informationProcess Control, 3P4 Assignment 5
Process Control, 3P4 Assignment 5 Kevin Dunn, kevin.dunn@mcmaster.ca Due date: 12 March 2014 This assignment is due on Wednesday, 12 March 2014. Late hand-ins are not allowed. Since it is posted mainly
More informationPERFORMANCE ANALYSIS OF TWO-DEGREE-OF-FREEDOM CONTROLLER AND MODEL PREDICTIVE CONTROLLER FOR THREE TANK INTERACTING SYSTEM
PERFORMANCE ANALYSIS OF TWO-DEGREE-OF-FREEDOM CONTROLLER AND MODEL PREDICTIVE CONTROLLER FOR THREE TANK INTERACTING SYSTEM K.Senthilkumar 1, Dr. D.Angeline Vijula 2, P.Venkadesan 3 1 PG Scholar, Department
More informationEXPERIMENTAL AND THEORETICAL ANALYSIS OF TRIPLE CONCENTRIC TUBE HEAT EXCHANGER
EXPERIMENTAL AND THEORETICAL ANALYSIS OF TRIPLE CONCENTRIC TUBE HEAT EXCHANGER 1 Pravin M. Shinde, 2 Ganesh S. Yeole, 3 Abhijeet B. Mohite, 4 Bhagyashree H. Mahajan. 5 Prof. D. K. Sharma. 6 Prof. A. K.
More informationPrototype of Heat Exchanger Cooler Type Shell And Tube Counter Flow Model as ATrainer for Temperature using Neuro-Fuzzy Control (ANFIS)
Prototype of Heat Exchanger Cooler Type Shell And Tube Counter Flow Model as ATrainer for erature using Neuro-Fuzzy Control (ANFIS) ( First Project ) Hairil Budiarto Mechatronic Departement of Trunojoyo
More informationSubject: Introduction to Process Control. Week 01, Lectures 01 02, Spring Content
v CHEG 461 : Process Dynamics and Control Subject: Introduction to Process Control Week 01, Lectures 01 02, Spring 2014 Dr. Costas Kiparissides Content 1. Introduction to Process Dynamics and Control 2.
More informationDESIGN AND EXPERIMENTAL ANALYSIS OF SHELL AND TUBE HEAT EXCHANGER (U-TUBE)
DESIGN AND EXPERIMENTAL ANALYSIS OF SHELL AND TUBE HEAT EXCHANGER (U-TUBE) Divyesh B. Patel 1, Jayesh R. Parekh 2 Assistant professor, Mechanical Department, SNPIT&RC, Umrakh, Gujarat, India 1 Assistant
More informationExperimental Analysis of Double Pipe Heat Exchanger
206 IJEDR Volume 4, Issue 2 ISSN: 232-9939 Experimental Analysis of Double Pipe Heat Exchanger Urvin R. Patel, 2 Manish S. Maisuria, 3 Dhaval R. Patel, 4 Krunal P. Parmar,2,3,4 Assistant Professor,2,3,4
More informationFAULT-TOLERANT CONTROL OF CHEMICAL PROCESS SYSTEMS USING COMMUNICATION NETWORKS. Nael H. El-Farra, Adiwinata Gani & Panagiotis D.
FAULT-TOLERANT CONTROL OF CHEMICAL PROCESS SYSTEMS USING COMMUNICATION NETWORKS Nael H. El-Farra, Adiwinata Gani & Panagiotis D. Christofides Department of Chemical Engineering University of California,
More informationMemorial University of Newfoundland Faculty of Engineering and Applied Science
Memorial University of Newfoundl Faculty of Engineering Applied Science ENGI-7903, Mechanical Equipment, Spring 20 Assignment 2 Vad Talimi Attempt all questions. The assignment may be done individually
More informationDesigning Steps for a Heat Exchanger ABSTRACT
Designing Steps for a Heat Exchanger Reetika Saxena M.Tech. Student in I.F.T.M. University, Moradabad Sanjay Yadav 2 Asst. Prof. in I.F.T.M. University, Moradabad ABSTRACT Distillation is a common method
More informationDesign and Implementation of Sliding Mode Controller using Coefficient Diagram Method for a nonlinear process
IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE) e-issn: 2278-1676,p-ISSN: 2320-3331, Volume 7, Issue 5 (Sep. - Oct. 2013), PP 19-24 Design and Implementation of Sliding Mode Controller
More informationCompensatorTuning for Didturbance Rejection Associated with Delayed Double Integrating Processes, Part II: Feedback Lag-lead First-order Compensator
CompensatorTuning for Didturbance Rejection Associated with Delayed Double Integrating Processes, Part II: Feedback Lag-lead First-order Compensator Galal Ali Hassaan Department of Mechanical Design &
More informationPROCESS CONTROL (IT62) SEMESTER: VI BRANCH: INSTRUMENTATION TECHNOLOGY
PROCESS CONTROL (IT62) SEMESTER: VI BRANCH: INSTRUMENTATION TECHNOLOGY by, Dr. Mallikarjun S. Holi Professor & Head Department of Biomedical Engineering Bapuji Institute of Engineering & Technology Davangere-577004
More informationEnhanced Single-Loop Control Strategies Chapter 16
Enhanced Single-Loop Control Strategies Chapter 16 1. Cascade control 2. Time-delay compensation 3. Inferential control 4. Selective and override control 5. Nonlinear control 6. Adaptive control 1 Chapter
More informationEvaluation Performance of PID, LQR, Pole Placement Controllers for Heat Exchanger
Evaluation Performance of PID, LQR, Pole Placement Controllers for Heat Exchanger Mohamed Essahafi, Mustapha Ait Lafkih Abstract In industrial environments, the heat exchanger is a necessary component
More informationFUZZY LOGIC CONTROL Vs. CONVENTIONAL PID CONTROL OF AN INVERTED PENDULUM ROBOT
http:// FUZZY LOGIC CONTROL Vs. CONVENTIONAL PID CONTROL OF AN INVERTED PENDULUM ROBOT 1 Ms.Mukesh Beniwal, 2 Mr. Davender Kumar 1 M.Tech Student, 2 Asst.Prof, Department of Electronics and Communication
More informationModel Based Fault Detection and Diagnosis Using Structured Residual Approach in a Multi-Input Multi-Output System
SERBIAN JOURNAL OF ELECTRICAL ENGINEERING Vol. 4, No. 2, November 2007, 133-145 Model Based Fault Detection and Diagnosis Using Structured Residual Approach in a Multi-Input Multi-Output System A. Asokan
More informationModel Predictive Control Design for Nonlinear Process Control Reactor Case Study: CSTR (Continuous Stirred Tank Reactor)
IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE) e-issn: 2278-1676,p-ISSN: 2320-3331, Volume 7, Issue 1 (Jul. - Aug. 2013), PP 88-94 Model Predictive Control Design for Nonlinear Process
More informationA Boiler-Turbine System Control Using A Fuzzy Auto-Regressive Moving Average (FARMA) Model
142 IEEE TRANSACTIONS ON ENERGY CONVERSION, VOL. 18, NO. 1, MARCH 2003 A Boiler-Turbine System Control Using A Fuzzy Auto-Regressive Moving Average (FARMA) Model Un-Chul Moon and Kwang Y. Lee, Fellow,
More informationCM 3310 Process Control, Spring Lecture 21
CM 331 Process Control, Spring 217 Instructor: Dr. om Co Lecture 21 (Back to Process Control opics ) General Control Configurations and Schemes. a) Basic Single-Input/Single-Output (SISO) Feedback Figure
More informationSIMULATION SUITE CHEMCAD SOFTWARE PROCESS CONTROL SYSTEMS PROCESS CONTROL SYSTEMS COURSE WITH CHEMCAD MODELS. Application > Design > Adjustment
COURSE WITH CHEMCAD MODELS PROCESS CONTROL SYSTEMS Application > Design > Adjustment Based on F.G. Shinskey s 1967 Edition Presenter John Edwards P & I Design Ltd, UK Contact: jee@pidesign.co.uk COURSE
More informationProposal of a Fuzzy Control System for Heat Transfer Using PLC
Proposal of a Fuzzy Control System for Heat Transfer Using PLC Martin Nesticky (B), Tomas Skulavik, and Jaroslav Znamenak Faculty of Materials Science and Technology in Trnava, Slovak University of Technology
More informationThe Effect of Mass Flow Rate on the Effectiveness of Plate Heat Exchanger
The Effect of Mass Flow Rate on the of Plate Heat Exchanger Wasi ur rahman Department of Chemical Engineering, Zakir Husain College of Engineering and Technology, Aligarh Muslim University, Aligarh 222,
More informationCascade Control of a Continuous Stirred Tank Reactor (CSTR)
Journal of Applied and Industrial Sciences, 213, 1 (4): 16-23, ISSN: 2328-4595 (PRINT), ISSN: 2328-469 (ONLINE) Research Article Cascade Control of a Continuous Stirred Tank Reactor (CSTR) 16 A. O. Ahmed
More informationWorld Journal of Engineering Research and Technology WJERT
wjert, 218, Vol. 4, Issue 1, 165-175. Original Article ISSN 2454-695X Pandimadevi et al. WJERT www.wjert.org SJIF Impact Factor: 4.326 DESIGN OF PI CONTROLLER FOR A CONICAL TANK SYSTEM *G. Pandimadevi
More informationDesign of Multivariable Neural Controllers Using a Classical Approach
Design of Multivariable Neural Controllers Using a Classical Approach Seshu K. Damarla & Madhusree Kundu Abstract In the present study, the neural network (NN) based multivariable controllers were designed
More informationResearch Article. World Journal of Engineering Research and Technology WJERT.
wjert, 2015, Vol. 1, Issue 1, 27-36 Research Article ISSN 2454-695X WJERT www.wjert.org COMPENSATOR TUNING FOR DISTURBANCE REJECTION ASSOCIATED WITH DELAYED DOUBLE INTEGRATING PROCESSES, PART I: FEEDBACK
More informationMultiple pass and cross flow heat exchangers
Multiple pass and cross flow heat exchangers Parag Chaware Department of Mechanical Engineering of Engineering, Pune Multiple pass and cross flow heat exchangers Parag Chaware 1 / 13 Introduction In order
More informationModeling and Model Predictive Control of Nonlinear Hydraulic System
Modeling and Model Predictive Control of Nonlinear Hydraulic System Petr Chalupa, Jakub Novák Department of Process Control, Faculty of Applied Informatics, Tomas Bata University in Zlin, nám. T. G. Masaryka
More informationJUSTIFICATION OF INPUT AND OUTPUT CONSTRAINTS INCORPORATION INTO PREDICTIVE CONTROL DESIGN
JUSTIFICATION OF INPUT AND OUTPUT CONSTRAINTS INCORPORATION INTO PREDICTIVE CONTROL DESIGN J. Škultéty, E. Miklovičová, M. Mrosko Slovak University of Technology, Faculty of Electrical Engineering and
More informationInvestigations of hot water temperature changes at the pipe outflow
Investigations of hot water temperature changes at the pipe outflow Janusz Wojtkowiak 1,*, and Czesław Oleśkowicz-Popiel 1 1 Poznan University of Technology, Faculty of Civil and Environmental Engineering,
More informationEXPERIMENTAL IMPLEMENTATION OF CDM BASED TWO MODE CONTROLLER FOR AN INTERACTING 2*2 DISTILLATION PROCESS
Volume 118 No. 18 2018, 2241-2251 ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version) url: http://www.ijpam.eu ijpam.eu EXPERIMENTAL IMPLEMENTATION OF CDM BASED TWO MODE CONTROLLER FOR
More informationarxiv: v1 [cs.sy] 30 Nov 2017
Disturbance Observer based Control of Integrating Processes with Dead-Time using PD controller Sujay D. Kadam SysIDEA Lab, IIT Gandhinagar, India. arxiv:1711.11250v1 [cs.sy] 30 Nov 2017 Abstract The work
More informationControl of an Ambiguous Real Time System Using Interval Type 2 Fuzzy Logic Control
International Journal of Applied Engineering Research ISSN 973-462 Volume 12, Number 21 (17) pp.11383-11391 Control of an Ambiguous Real Time System Using Interval Type 2 Fuzzy Logic Control Deepa Thangavelusamy
More informationAn Improved Relay Auto Tuning of PID Controllers for SOPTD Systems
Proceedings of the World Congress on Engineering and Computer Science 7 WCECS 7, October 4-6, 7, San Francisco, USA An Improved Relay Auto Tuning of PID Controllers for SOPTD Systems Sathe Vivek and M.
More informationAn improved auto-tuning scheme for PI controllers
ISA Transactions 47 (2008) 45 52 www.elsevier.com/locate/isatrans An improved auto-tuning scheme for PI controllers Rajani K. Mudi a,, Chanchal Dey b, Tsu-Tian Lee c a Department of Instrumentation and
More informationEnhanced Single-Loop Control Strategies (Advanced Control) Cascade Control Time-Delay Compensation Inferential Control Selective and Override Control
Enhanced Single-Loop Control Strategies (Advanced Control) Cascade Control Time-Delay Compensation Inferential Control Selective and Override Control 1 Cascade Control A disadvantage of conventional feedback
More informationType-2 Fuzzy Logic Control of Continuous Stirred Tank Reactor
dvance in Electronic and Electric Engineering. ISSN 2231-1297, Volume 3, Number 2 (2013), pp. 169-178 Research India Publications http://www.ripublication.com/aeee.htm Type-2 Fuzzy Logic Control of Continuous
More informationChapter 8. Feedback Controllers. Figure 8.1 Schematic diagram for a stirred-tank blending system.
Feedback Controllers Figure 8.1 Schematic diagram for a stirred-tank blending system. 1 Basic Control Modes Next we consider the three basic control modes starting with the simplest mode, proportional
More informationOUTPUT REGULATION OF RÖSSLER PROTOTYPE-4 CHAOTIC SYSTEM BY STATE FEEDBACK CONTROL
International Journal in Foundations of Computer Science & Technology (IJFCST),Vol., No., March 01 OUTPUT REGULATION OF RÖSSLER PROTOTYPE-4 CHAOTIC SYSTEM BY STATE FEEDBACK CONTROL Sundarapandian Vaidyanathan
More informationTemperature Control of CSTR Using Fuzzy Logic Control and IMC Control
Vo1ume 1, No. 04, December 2014 936 Temperature Control of CSTR Using Fuzzy Logic Control and Control Aravind R Varma and Dr.V.O. Rejini Abstract--- Fuzzy logic controllers are useful in chemical processes
More informationDesign and Implementation of PI and PIFL Controllers for Continuous Stirred Tank Reactor System
International Journal of omputer Science and Electronics Engineering (IJSEE olume, Issue (4 ISSN 3 48 (Online Design and Implementation of PI and PIFL ontrollers for ontinuous Stirred Tank Reactor System
More informationNUMERICAL ANALYSIS ON THERMAL ENERGY STORAGE TANK FILLED WITH PHASE CHANGE MATERIAL
NUMERICAL ANALYSIS ON THERMAL ENERGY STORAGE TANK FILLED WITH PHASE CHANGE MATERIAL Uday Maruti Jad PG Student, Department of Mechanical Engineering Rajarambapu Institute of Technology Rajaramnagar, India.
More informationOUTPUT REGULATION OF THE SIMPLIFIED LORENZ CHAOTIC SYSTEM
OUTPUT REGULATION OF THE SIMPLIFIED LORENZ CHAOTIC SYSTEM Sundarapandian Vaidyanathan Research and Development Centre, Vel Tech Dr. RR & Dr. SR Technical University Avadi, Chennai-600 06, Tamil Nadu, INDIA
More informationH-infinity Model Reference Controller Design for Magnetic Levitation System
H.I. Ali Control and Systems Engineering Department, University of Technology Baghdad, Iraq 6043@uotechnology.edu.iq H-infinity Model Reference Controller Design for Magnetic Levitation System Abstract-
More informationc Dr. Md. Zahurul Haq (BUET) Heat Exchangers: Rating & Sizing - I ME 307 (2017) 2 / 32 T666
Heat Exchanger: Rating & Sizing Heat Exchangers: Rating & Sizing - I Dr. Md. Zahurul Haq Professor Department of Mechanical Engineering Bangladesh University of Engineering & Technology (BUET) Dhaka-000,
More informationCOMPARISON OF FUZZY LOGIC CONTROLLERS FOR A MULTIVARIABLE PROCESS
COMPARISON OF FUZZY LOGIC CONTROLLERS FOR A MULTIVARIABLE PROCESS KARTHICK S, LAKSHMI P, DEEPA T 3 PG Student, DEEE, College of Engineering, Guindy, Anna University, Cennai Associate Professor, DEEE, College
More informationHEAT EXCHANGER. Objectives
HEAT EXCHANGER Heat exchange is an important unit operation that contributes to efficiency and safety of many processes. In this project you will evaluate performance of three different types of heat exchangers
More informationS.E. (Chemical) (Second Semester) EXAMINATION, 2011 HEAT TRANSFER (2008 PATTERN) Time : Three Hours Maximum Marks : 100
Total No. of Questions 12] [Total No. of Printed Pages 7 [4062]-186 S.E. (Chemical) (Second Semester) EXAMINATION, 2011 HEAT TRANSFER (2008 PATTERN) Time : Three Hours Maximum Marks : 100 N.B. : (i) Answers
More informationSolutions for Tutorial 10 Stability Analysis
Solutions for Tutorial 1 Stability Analysis 1.1 In this question, you will analyze the series of three isothermal CSTR s show in Figure 1.1. The model for each reactor is the same at presented in Textbook
More informationCSTR CONTROL USING MULTIPLE MODELS
CSTR CONTROL USING MULTIPLE MODELS J. Novák, V. Bobál Univerzita Tomáše Bati, Fakulta aplikované informatiky Mostní 39, Zlín INTRODUCTION Almost every real process exhibits nonlinear behavior in a full
More informationAn Adaptive LQG Combined With the MRAS Based LFFC for Motion Control Systems
Journal of Automation Control Engineering Vol 3 No 2 April 2015 An Adaptive LQG Combined With the MRAS Based LFFC for Motion Control Systems Nguyen Duy Cuong Nguyen Van Lanh Gia Thi Dinh Electronics Faculty
More informationOptimization and composition control of Distillation column using MPC
Optimization and composition control of Distillation column using M.Manimaran 1,A.Arumugam 2,G.Balasubramanian 3,K.Ramkumar 4 1,3,4 School of Electrical and Electronics Engineering, SASTRA University,
More informationFuzzy Approximate Model for Distributed Thermal Solar Collectors Control
Fuzzy Approimate Model for Distributed Thermal Solar Collectors Control Item Type Conference Paper Authors Elmetennani, Shahrazed; Laleg-Kirati, Taous-Meriem Eprint version Pre-print Download date 3/3/219
More informationHow can we use Fundamental Heat Transfer to understand real devices like heat exchangers?
Lectures 7+8 04 CM30 /30/05 CM30 Transport I Part II: Heat Transfer Applied Heat Transfer: Heat Exchanger Modeling, Sizing, and Design Professor Faith Morrison Department of Chemical Engineering Michigan
More informationProcess Control J.P. CORRIOU. Reaction and Process Engineering Laboratory University of Lorraine-CNRS, Nancy (France) Zhejiang University 2016
Process Control J.P. CORRIOU Reaction and Process Engineering Laboratory University of Lorraine-CNRS, Nancy (France) Zhejiang University 206 J.P. Corriou (LRGP) Process Control Zhejiang University 206
More information