Receding Horizon Control : Model Predictive Control for State Models

by Kwon, W. H.; Han, S.

• ISBN13: 9781846280245
• ISBN10: 1846280249
• Format: Paperback
• Copyright: 2005-09-30
• Publisher: Springer Verlag

Summary

Receding Horizon Control introduces the essentials of a successful feedback strategy that has emerged in many industrial fields: the process industries in particular. Receding horizon control (RHC) has a number of advantages over other types of control: easier computation than steady-state optimal control; greater adaptability to parametric changes than infinite horizon control; better tracking than PID and good constraint handling among others.The text builds understanding starting with optimal controls for simple linear systems and working through constrained systems to nonlinear cases. RHC is applied to discrete-time systems for better understanding and easier computer application. Its diverse techniques are unified using the state-space framework. Worked examples and exercises throughout the book allow you to practise as you go and MATLAB(r) files for the solution of selected examples can be downloaded from springeronline.com.Graduate students following masters and doctoral courses in control theory and engineering will find Receding Horizon Control to be an excellent companion to tuition and research. Tutors and academics researching model predictive control can use this not only as a scholarly textbook but as a co-ordinated reference for its wide range of receding horizon schemes.

Author Biography

Professor Kwon is President-elect of IFAC and will take over the presidency for three years beginning January 2006.Professor Kwon has an excellent reputation as a leading control engineer and an important member of IFAC. He has specialised in model predictive control for many years.Professor Kwon was a research associate at Brown University in 1975 and from 1976 to 1977 he was an adjunct assistant professor at the University of Iowa. Since 1977, which includes a period from 1981 to 1982 when he was a visiting assistant professor at Stanford University, he has been with Seoul National University.During his career Professor Kwon has published more than 60 international journal papers and approximately 120 international conference papers. In recognition of his academic and industrial achievements in Korea he was endowed with a POSCO professorship from Pohang Steel Company in 1995, and in 1997 received the National Academy of Sciences Award. He is a Fellow of the Korean Academy of Science and Technology and is also a member of the National Academy of Engineering. Since 1991 he has been the Director of the Engineering Research Center for Advanced Control and Instrumentation established at SNU by the Korean Science and Engineering Foundation. This Center won the prestigious University LEAD Award of the Society of Manufacturing Engineers (SME) in the US under his guidance in 1996. He was a key founder of the Korea Automatic Control Conference, now in its fourteenth year, in which about 650 people participate every year. He was a key founder and is now President of the Institute of Control Automation and Systems Engineers which is the Korean National Member Organisation of IFAC. He became the Vice-President of IFAC in July 1999. He will be President elect of the Korean Institute of Electrical Engineers next year. He was the founding Vice-Chairman of the Asian Control Professors Association in 1996 and is now the Chairman. He was also a founding member of the Steering Committee of the Asian Control Conference.

Table of Contents

1 Introduction	1	(16)
1.1 Control Systems	1	(2)
1.2 Concept of Receding Horizon Controls	3	(4)
1.3 Receding Horizon Filters and Output Feedback Receding Horizon Controls	7	(1)
1.4 Predictive Controls	8	(1)
1.5 Advantages of Receding Horizon Controls	9	(2)
1.6 About This Book	11	(4)
1.7 References	15	(2)
2 Optimal Controls on Finite and Infinite Horizons: A Review	17	(66)
2.1 Introduction	17	(1)
2.2 Optimal Control for General Systems	18	(8)
2.2.1 Optimal Control Based on Minimum Criterion	18	(6)
2.2.2 Optimal Control Based on Minimax Criterion	24	(2)
2.3 Linear Optimal Control with State Feedback	26	(23)
2.3.1 Linear Quadratic Controls Based on Minimum Criterion	26	(16)
2.3.2 Hinfinity Control Based on Minimax Criterion	42	(7)
2.4 Optimal Filters	49	(8)
2.4.1 Kalman Filter on Minimum Criterion	49	(3)
2.4.2 Hinfinity Filter on Minimax Criterion	52	(4)
2.4.3 Kalman Filters on Minimax Criterion	56	(1)
2.5 Output Feedback Optimal Control	57	(9)
2.5.1 Linear Quadratic Gaussian Control on Minimum Criterion	58	(3)
2.5.2 Output Feedback Hinfinity Control on Minimax Criterion	61	(5)
2.6 Linear Optimal Controls via Linear Matrix Inequality	66	(4)
2.6.1 Infinite Horizon Linear Quadratic Control via Linear Matrix Inequality	66	(2)
2.6.2 Infinite Horizon Hinfinity Control via Linear Matrix Inequality	68	(2)
2.7 H2 Controls	70	(4)
2.8 References	74	(2)
2.9 Problems	76	(7)
3 State Feedback Receding Horizon Controls	83	(76)
3.1 Introduction	83	(1)
3.2 Receding Horizon Controls in Predictive Forms	84	(3)
3.2.1 Predictive Forms	84	(1)
3.2.2 Performance Criteria in Predictive Forms	85	(2)
3.3 Receding Horizon Control Based on Minimum Criteria	87	(38)
3.3.1 Receding Horizon Linear Quadratic Control	87	(4)
3.3.2 Simple Notation for Time-invariant Systems	91	(4)
3.3.3 Monotonicity of the Optimal Cost	95	(9)
3.3.4 Stability of Receding Horizon Linear Quadratic Control	104	(11)
3.3.5 Additional Properties of Receding Horizon Linear Quadratic Control	115	(7)
3.3.6 A Special Case of Input–Output Systems	122	(3)
3.4 Receding Horizon Control Based on Minimax Criteria	125	(14)
3.4.1 Receding Horizon Hinfinity Control	125	(3)
3.4.2 Monotonicity of the Saddle-point Optimal Cost	128	(5)
3.4.3 Stability of Receding Horizon Hinfinity Control	133	(5)
3.4.4 Additional Properties	138	(1)
3.5 Receding Horizon Control via Linear Matrix Inequality Forms	139	(11)
3.5.1 Computation of Cost Monotonicity Condition	139	(4)
3.5.2 Receding Horizon Linear Quadratic. Control via, Batch and Linear Matrix Inequality Forms	143	(5)
3.5.3 Receding Horizon Hinfinity Control via Batch and Linear Matrix Inequality Forms	148	(2)
3.6 References	150	(1)
3.7 Problems	151	(8)
4 Receding Horizon Filters	159	(58)
4.1 Introduction	159	(2)
4.2 Dual Infinite Impulse Response Filter Based on Minimum Criterion	161	(4)
4.3 Optimal Finite Impulse Response Filters Based on Minimum Criterion	165	(25)
4.3.1 Linear Unbiased Finite Impulse Response Filters	165	(2)
4.3.2 Minimum Variance Finite Impulse Response Filters with Nonsingular A	167	(10)
4.3.3 Minimum Variance Finite Impulse Response Filters with General A	177	(11)
4.3.4 Numerical Examples for Minimum Variance Finite Impulse Response Filters	188	(2)
4.4 Dual Infinite Impulse Response Filters Based on Minimax Criterion	190	(5)
4.5 Finite Impulse Response Filters Based on Minimax Criterion	195	(12)
4.5.1 Linear Unbiased Finite Impulse Response Filters	195	(2)
4.5.2 L2-E Finite Impulse Response Filters	197	(5)
4.5.3 Hinfinity Finite Impulse Response Filter	202	(2)
4.5.4 H2/Hinfinity Finite Impulse Response Filters	204	(3)
4.6 References	207	(2)
4.7 Problems	209	(8)
5 Output Feedback Receding Horizon Controls	217	(44)
5.1 Introduction	217	(1)
5.2 State-observer-based Output Feedback Controls	218	(2)
5.3 Predictor-based Output Feedback Controls	220	(2)
5.4 A Special Case of Input—Output Systems of General Predictive Control	222	(5)
5.5 Finite Memory Control Based on Minimum Criterion	227	(17)
5.5.1 Finite Memory Control and Unbiased Condition	227	(3)
5.5.2 Linear Quadratic Finite Memory Control	230	(5)
5.5.3 Linear Quadratic Finite Memory Control with General A	235	(4)
5.5.4 Properties of Linear Quadratic Finite Memory Control	239	(5)
5.6 Finite Memory Control Based on Minimax Criterion	244	(12)
5.6.1 Finite Memory Control and Unbiased Condition	244	(1)
5.6.2 L2-E Finite Memory Controls	245	(5)
5.6.3 Hinfinity Finite Memory Controls	250	(4)
5.6.4 H2/Hinfinity Finite Memory Controls	254	(2)
5.7 References	256	(1)
5.8 Problems	256	(5)
6 Constrained Receding Horizon Controls	261	(36)
6.1 Introduction	261	(1)
6.2 Reachable and Maximal Output Admissible Sets	262	(7)
6.3 Constrained Receding Horizon Control with Terminal Equality Constraint	269	(3)
6.4 Constrained Receding Horizon Control with Terminal Set Constraint	272	(5)
6.5 Constrained Receding Horizon Control with Free Terminal Cost	277	(7)
6.6 Constrained Receding Horizon Control with Mixed Constraints	284	(2)
6.7 Constrained Output Feedback Receding Horizon Control	286	(3)
6.8 References	289	(1)
6.9 Problems	290	(7)
7 Nonlinear Receding Horizon Controls	297	(26)
7.1 Introduction	297	(1)
7.2 Nonlinear Receding Horizon Control with Terminal Equality Constraint	298	(2)
7.3 Nonlinear Receding Horizon Control with Terminal Set Constraints	300	(4)
7.4 Nonlinear Receding Horizon Control with Free Terminal Cost	304	(7)
7.5 Nonlinear Receding Horizon Control with Infinite Cost Horizon	311	(2)
7.6 Nonlinear Receding Horizon Minimax Control with Free Terminal Cost	313	(3)
7.7 References	316	(1)
7.8 Problems	316	(7)
A Matrix Equality and Matrix Calculus	323	(4)
A.1 Useful Inversion Formulae	323	(2)
A.2 Matrix Calculus	325	(2)
B System Theory	327	(8)
B.1 Controllability and Observability	327	(3)
B.2 Stability Theory	330	(1)
B.3 Lyapunov and Riccati Matrix Equations	331	(4)
C Random Variables	335	(6)
C.1 Random Variables	335	(1)
C.2 Gaussian Random Variable	336	(3)
C.3 Random Process	339	(2)
D Linear Matrix Inequalities and Semidefinite Programming	341	(6)
D.1 Linear Matrix Inequalities	341	(2)
D.2 Semidefinite Programming	343	(4)
E Survey on Applications	347	(2)
F MATLAB® Programs	349	(18)
References	367	(8)
Index	375