Robust Industrial Control Systems Optimal Design Approach for Polynomial Systems

by Grimble, Michael J.

• ISBN13: 9780470020739
• ISBN10: 0470020733
• eBook ISBN(s): 9780470020746
• Edition: 1st
• Format: Hardcover
• Copyright: 2006-05-25
• Publisher: WILEY
• More Book Details
• Purchase Benefits

Summary

Robust Industrial Control Systems: Optimal Design Approach for Polynomial Systems presents a comprehensive introduction to the use of frequency domain and polynomial system design techniques for a range of industrial control and signal processing applications. The solution of stochastic and robust optimal control problems is considered, building up from single-input problems and gradually developing the results for multivariable design of the later chapters. In addition to cataloguing many of the results in polynomial systems needed to calculate industrial controllers and filters, basic design procedures are also introduced which enable cost functions and system descriptions to be specified in order to satisfy industrial requirements.Providing a range of solutions to control and signal processing problems, this book: Presents a comprehensive introduction to the polynomial systems approach for the solution of H 2 and H infin; optimal control problems. Develops robust control design procedures using frequency domain methods. Demonstrates design examples for gas turbines, marine systems, metal processing, flight control, wind turbines, process control and manufacturing systems. Includes the analysis of multi-degrees of freedom controllers and the computation of restricted structure controllers that are simple to implement. Considers time-varying control and signal processing problems. Addresses the control of non-linear processes using both multiple model concepts and new optimal control solutions. Robust Industrial Control Systems: Optimal Design Approach for Polynomial Systems is essential reading for professional engineers requiring an introduction to optimal control theory and insights into its use in the design of real industrial processes. Students and researchers in the field will also find it an excellent reference tool.

Author Biography

Professor <b>Michael Grimble</b>, Director of the Industrial Control Centre and Past Chairman of the Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, UK

Table of Contents

CHAPTER 1. INTRODUCTION TO OPTIMAL AND ROBUST CONTROL.

1.1 INTRODUCTION.

1.2 The H2 and H∞ SPACES and NORMS.

1.3 INTRODUCTION TO H∞ CONTROL DESIGN .

1.4 STATE-SPACE MODELLING AND SYNTHESIS THEORY.

1.5 INTRODUCTION TO H2 OR LQG POLYNOMIAL SYNTHESIS .

1.6 BENCHMARKING.

1.7 CONDITION MONITORING.

1.8 COMBINING H2, H∞ DESIGN AND OPTIMAL CONTROL.

1.9 LINEAR MATRIX INEQUALITIES.

1.10 CONCLUDING REMARKS.

1.11 PROBLEMS.

1.12 REFERENCES.

CHAPTER 2. SCALAR LQG OPTIMAL CONTROL.

2.1 INTRODUCTION.

2.2 STOCHASTIC SYSTEM DESCRIPTION.

2.3 DUAL-CRITERION COST-MINIMISATION PROBLEM.

2.4 LQG CONTROLLER WITH ROBUST WEIGHTING FUNCTION.

2.5 INTRODUCTION TO THE STANDARD SYSTEM MODEL.

2.6. THE STANDARD SYSTEM MODEL STRUCTURE.

2.7 GENERALISED H2 OPTIMAL CONTROL: STANDARD SYSTEM MODEL.

2.8 CONCLUDING REMARKS.

2.9 PROBLEMS.

2.10 REFERENCES.

CHAPTER 3. SCALAR H∞ OPTIMAL CONTROL.

3.1 INTRODUCTION.

3.2 SYSTEM DESCRIPTION.

3.3 LEMMA LINKING H∞ AND LQG CONTROL PROBLEMS.

3.4 CALCULATION OF THE H∞ OPTIMAL CONTROLLER.

3.5 THE GH∞ CONTROL PROBLEM.

3.6 STABILITY ROBUSTNESS OF GH∞ DESIGNS.

3.7 STANDARD SYSTEM AND COST FUNCTION DESCRIPTION.

3.8 CALCULATION OF THE H∞ CONTROLLER FOR THE STANDARD SYSTEM.

3.9 PROBABILISTIC SYSTEM DESCRIPTIONS AND H∞ CONTROL.

3.10 CONCLUDING REMARKS.

3.11 PROBLEMS.

3.12 REFERENCES.

CHAPTER 4. MULTIVARIABLE H2/LQG OPTIMAL CONTROL.

4.1 INTRODUCTION.

4.2 MULTIVARIABLE SYSTEM DESCRIPTION.

4.3. LQG OPTIMAL CONTROL PROBLEM AND SOLUTION.

4.4 YOULA PARAMETERISATION AND AUXILIARY LQG DESIGN PROBLEM.

4.5 H2/LQG OPTIMAL CONTROL PROBLEM: MEASUREMENT NOISE CASE.

4.6 GLQG OPTIMAL CONTROL PROBLEM AND SIMPLIFIED SOLUTION.

4.7 DESIGN OF AUTOMATIC VOLTAGE REGULATORS .

4.8 PSEUDO-STATE MODELLING AND SEPARATION PRINCIPLE.

4.9 CONCLUDING REMARKS.

4.10 PROBLEMS.

4.11 REFERENCES.

CHAPTER 5.MULTIVARIABLE H∞ OPTIMAL CONTROL.

5.1 INTRODUCTION.

5.2 H∞ MULTIVARIABLE CONTROLLERS.

5.3 ONE BLOCK AND GH∞ OPTIMAL CONTROL PROBLEMS.

5.4 SUBOPTIMAL H∞ MULTIVARIABLE CONTROLLERS.

5.5 POLYNOMIAL SYSTEM FOR SUBOPTIMAL H∞ CONTROL PROBLEM.

5.6 SOLUTION OF SUBOPTIMAL H∞ STATE FEEDBACK PROBLEM.

5.7 SUBOPTIMAL H∞ STATE FEEDBACK CONTROL PROBLEM RESULTS.

5.8 RELATIONSHIP BETWEEN POLYNOMIAL AND STATE-SPACE RESULTS.

5.9 SOLUTION OF SUBOPTIMAL OUTPUT FEEDBACK CONTROL PROBLEM.

5.10 PROBLEMS.

5.11 REFERENCES.

CHAPTER 6. ROBUST CONTROL SYSTEMS DESIGN AND IMPLEMENTATION.

6.1 INTRODUCTION.

6.2 AVOIDING IMPRACTICAL H∞ DESIGNS.

6.3 POLE-ZERO CANCELLATION PROPERTIES OF LQG AND H∞ DESIGNS.

6.4 SYSTEM POLE AND ZERO PROPERTIES.

6.5 INFLUENCE OF COST WEIGHTING FUNCTIONS ON FREQUENCY RESPONSES.

6.6 LOOP SHAPING DESIGN FOR MULTIVARIABLE SYSTEMS.

6.7 FORMALISED DESIGN PROCEDURES.

6.8 THE MULTIVARIABLE ROBUST CONTROL DESIGN PROBLEM.

6.9 H∞ MULTIVARIABLE DESIGN OF SUBMARINE DEPTH AND PITCH CONTROL.

6.10 RESTRICTED STRUCTURE AND MULTIPLE MODEL OPTIMAL CONTROL.

6.11 CONCLUDING REMARKS.

6.12 PROBLEMS.

6.13 REFERENCES.

CHAPTER 7. H2 FILTERING, SMOOTHING AND PREDICTION .

7.1 INTRODUCTION.

7.2 SIGNAL PROCESSING SYSTEM DESCRIPTION.

7.3 THE STANDARD H∞ OPTIMAL ESTIMATION PROBLEM.

7.4 SOLUTION OF FILTERING, SMOOTHING AND PREDICTION PROBLEMS.

7.5 STRIP THICKNESS ESTIMATION FROM ROLL FORCE MEASUREMENTS.

7.6 RESULTS FOR STRIP THICKNESS ESTIMATION : FORCE MEASUREMENTS.

7.7 STRIP THICKNESS ESTIMATION FROM X-RAY GAUGE MEASUREMENTS.

7.8 RESULTS FOR STRIP THICKNESS ESTIMATION: GAUGE MEASUREMENT.

7.9 TIME VARYING AND NON-STATIONARY FILTERING.

7.10 CONCLUSIONS.

7.11 PROBLEMS .

7.12 REFERENCES.

CHAPTER 8. H∞ FILTERING, SMOOTHING AND PREDICTION.

8.1 INTRODUCTION.

8.2 SOLUTION OF H∞ OPTIMAL ESTIMATION PROBLEM.

8.3 H∞ DECONVOLUTION FILTERING PROBLEM.

8.4 SUBOPTIMAL H∞ MULTI-CHANNEL FILTERS.

8.5 RELEVANCE OF H∞ METHODS TO SIGNAL PROCESSING APPLICATIONS.

8.6 FINAL REMARKS ON THE SUBOPTIMAL H∞ FILTERING PROBLEM.

8.7 PROBLEMS.

8.8 REFERENCE.

CHAPTER 9. INDUSTRIAL APPLICATIONS OF H2/LQG OPTIMAL CONTROL.

9.1 INTRODUCTION.

9.2 WIND TURBINE POWER CONTROL SYSTEMS.

9.3 DESIGN OF AN H2 FLIGHT CONTROL SYSTEM .

9.4 THICKNESS CONTROL SYSTEMS DESIGN USING FORCE FEEDBACK.

9.5 THICKNESS CONTROL USING GAUGE MEASUREMENT.

9.6 SHIP ROLL STABILISATION.

9.7 CONCLUDING REMARKS.

9.8 PROBLEMS.

9.9 REFERENCES.

CHAPTER 10. INDUSTRIAL APPLICATIONS OF H∞ OPTIMAL CONTROL.

10.1 INTRODUCTION.

10.2 H∞ FLIGHT CONTROL SYSTEMS DESIGN.

10.3 H∞ GAUGE CONTROL SYSTEM DESIGN USING FORCE FEEDBACK.

10.4 SUBMARINE DEPTH AND COURSE KEEPING H∞ DESIGN.

10.5 H∞ CONTROL OF REMOTELY OPERATED UNDERWATER VEHICLES.

10.6 H∞ CONTROL OF SURFACE SHIPS.

10.7 CONCLUDING REMARKS.

10.8 PROBLEMS.

10.9 REFERENCES .

CHAPTER 11. TIME-VARYING AND NONLINEAR CONTROL .

11.1 INTRODUCTION.

11.2 OPTIMAL CONTROL OF TIME-VARYING LINEAR SYSTEMS.

11.3 MODELLING AND CONTROL OF NONLINEAR SYSTEMS.

11.4 NLQG COMPENSATION AND CONTROL.

11.5 NLQG EXAMPLE WITH INPUT AND OUTPUT NONLINEARITIES.

11.6 NONLINEAR GENERALISED MINIMUM VARIANCE CONTROL.

11.7 NONLINEAR GENERALISED MINIMUM VARIANCE PROBLEM.

11.8 NONLINEAR GMV CONTROL PROBLEM.

11.9 NONLINEAR SMITH PREDICTOR.

11.10 CONCLUDING REMARKS.

11.11 REFERENCES.