l£>/vOt\ / * ]6 /OS PROPOSED AUTOMATION OF TEA WITHERING PROCESS USING FUZZY LOGIC CONTROLLER A dissertation submitted to the Department of Electrical Engineering, University of Moratuwa in partial fulfilment of the requirements for the degree of Master of Science by JAYASUNDARA MUDIYANSELAGE INDIKA JAYASUNDARA -jmAKY uiwc«rn <* tDMUM^ irj ianw " MUWfl Supervised by: Dr. Lanka Udawatta, Mr. K.Raveendran. j n \ 3 8 Department of Electrical Engineering University of Moratuwa, Sri Lanka February 2008 University of Moratuwa 91250 9 1 2 5 0 DECLARATION The work submitted in this dissertation is the result of my own investigation, except where otherwise stated. It has not already been accepted for any degree, and is also not being concurrently submitted for any other degree. J.M.I Jayasundara Date endorse the declaration by the candidate. Dr. Lanka Udawatta - / r a ^ K.Raveendran 3 CONTENTS Declaration 3 Contents 4 Abstract 6 Dedication 7 Acknowledgement 8 List of Figures 9 List of Tables 10 1. Introduction 11 1.1 Background 11 1.2 Motivation 14 1.3 Objective 14 2. Tea Processing 15 2.1 Withering 15 2.2 Rolling 16 2.3 Fermentation 17 2.4 Drying 17 2.5 Grading and Packaging 17 3. Fuzzy Controller 18 3.1 Fuzzy logic History and Applications 18 3.2 Fuzzy logic in Industrial Automation 18 3.3 Multivariable Control 19 3.4 Structure of a Fuzzy Controller 20 3.4.1 Pre-processing 20 3.4.2 Fuzzyfication 20 3.4.3 Rule Base 21 3.4.4 Inference Engine 21 3.4.5 Defuzzyfication 22 3.4.6 Post Processing 22 4 4. Statement of the Problem 23 4.1 Preliminaries 23 4.2 Behaviour of Process Inputs 24 5. Proposed Solution 28 5.1 Methods and Techniques 28 5.2 Development of the Control Algorithm 36 5.3 The Fuzzy Inference System 38 5.4 Rule Base 40 6. Results and Analysis 45 6.1 Evaluation of the Proposed Control Strategy 45 6.2 Energy Saving Approximations 49 7. Application of the Proposed Method 53 7.1 Implementation 53 7.2 Configuring Fine Tuning and Commissioning 54 7.3 Practical Issues 54 8. Conclusions 55 8.1 Conclusions, Remarks and Discussion 55 8.2 Considerations for Future Research 56 References 57 Appendix 59 ABSTRACT Tea processing is one of the major energy intensive food processing industries in Sri Lanka and the process "withering", which is the first stage of the complete process, accounts for about half of the total electrical energy consumption in the tea industry. This process consumes electrical energy mainly to run the withering fans. The traditional methods of controlling withering process have proven to be very inefficient in energy point of view. This study proposes a fuzzy logic based withering control methodology which will optimize the electrical energy consumption of the process while maintaining the quality of the processed tea. Present process analysis was done with field experimental data and the performance of the proposed system was evaluated on Matlab® platform. This proposed control structure can be implemented, modified and field tuned for optimization depending on the practical installation characteristics and expected to save a considerable amount of electrical energy in tea processing industry. ACKNOWLEDGEMENT I would like to express thanks to my supervisors Dr. Lanka Udawatta and Mr. K.Raveendran for their continuing guidance, encouragement, and support throughout the course of my study. My sincere thanks go to the officers at Tea Research institute of Sri Lanka, Thalawakelle, Faculty of Engineering, University of Moratuwa, for helping in various ways to clarify the things related to my work in time with excellent cooperation and guidance. Also I must thank the management and staff of Rotax Limited, for support and encouragement extended to me in making this study a success. Finally, I should thank many individuals, friends and colleagues who have not been mentioned here personally in making this educational process a success. May be I could not have made it without your support. 8 LIST OF FIGURES Figure 3.1: Standard Fuzzy Logic Controller. Figure 4.1: Withering Trough Arrangement. Figure 4.2: Variation of Air Flow with Process Time. Figure 4.3: Variation of Chamber Pressure with Process Time. Figure 5.1: Fuzzyfication of Input Air Flow Figure 5.2: Fuzzyfication of Input Chamber Pressure Figure 5.3: Fuzzyfication of Input Relative Humidity Figure 5.4: Fuzzyfication of Input Chamber Temperature Figure 5.5: Fuzzyfication of Output Motor Frequency Figure 5.6: Fuzzyfication of Output Damper Angle Figure 5.7: Layout of the Withering Trough Figure 5.8: Fuzzy Withering Control System Figure 6.1: Comparison of Normal Process and Fuzzy Withering Controller Outputs Figure 6.2: Graphical View of Motor Frequency Pattern With Respect To Chamber Pressure and Air Flow Readings. Figure 6.3: Graphical View of Damper Angle Variation Pattern With Relation To Humidity and Chamber Pressure Readings Figure 7.1: Structure of the Proposed Control System Figure A.l: Motor Power Consumption with Time (At Constant Frequency) Figure A.2: Air Flow Vs Chamber Pressure LIST OF TABLES Table 5.1: Fuzzyfication of Input Air Flow Table 5.2: Fuzzyfication of Input Chamber Pressure Table 5.3: Fuzzyfication of Input Relative Humidity Table 5.4: Fuzzyfication of Input Chamber Temperature Table 5.5: Fuzzyfication of Output Motor Frequency Table 5.6: Fuzzyfication of Output Damper Angle Table 6.1: Matlab Fuzzy Inference Evaluation Results Table 6.2: Electrical Energy Consumption of the Present and Proposed systems Table A. 1: Field Experiment Data Table A.2: Air Velocity through Withering Bed. Table A3: Withering Chamber Pressure Variation during the Process Table A.4: Motor Power Consumption with Time