## A survey of industrial model predictive control technology (2003)

Citations: | 201 - 5 self |

### BibTeX

@MISC{Qin03asurvey,

author = {S. Joe Qin and Thomas A. Badgwell},

title = {A survey of industrial model predictive control technology},

year = {2003}

}

### Years of Citing Articles

### OpenURL

### Abstract

This paper provides an overview of commercially available model predictive control (MPC) technology, both linear and nonlinear, based primarily on data provided by MPC vendors. A brief history of industrial MPC technology is presented first, followed by results of our vendor survey of MPC control and identification technology. A general MPC control algorithm is presented, and approaches taken by each vendor for the different aspects of the calculation are described. Identification technology is reviewed to determine similarities and differences between the various approaches. MPC applications performed by each vendor are summarized by application area. The final section presents a vision of the next generation of MPC technology, with an emphasis on potential business and research opportunities.

### Citations

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Citation Context ... PREDICTIVE CONTROL The development of modern control concepts can be traced to the work of Kalman in the early 1960's, who sought to determine when a linear control system can be said to be optimal (=-=Kalman, 1960-=-a; Kalman, 1960b). Kalman studied a Linear Quadratic Regulator (LQR) designed to minimize an quadratic objective function. The process to be controlled can be described by a discrete-time, determinist... |

1182 |
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Citation Context ... y (q \Gamma1 )] \Gamma1 [\Phi u (q \Gamma1 )uk + \Phi v (q \Gamma1 )v k + \Phi w (q \Gamma1 )w k ] + �� k (11) where q \Gamma1 is a backward shift operator. The output error identification approa=-=ch (Ljung, 1987) mi-=-nimizes the measurement error �� k , which results in nonlinear parameter estimation. Multiplying [I \Gamma \Phi y (q \Gamma1 )] on both sides of the above equation results in an autoregressive mo... |

358 | Predictive control with constraints - Maciejowski - 2002 |

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215 |
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Citation Context ...r plant, it had little impact on control technology development in the process industries. The most significant of the reasons cited for this failure include (Richalet, Rault, Testud and Papon, 1978; =-=Garc'ia et al., 1989-=-) : ffl constraints ffl process nonlinearities ffl model uncertainty (robustness) ffl unique performance criteria ffl cultural reasons (people, education, etc.) It is well known that the economic oper... |

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Citation Context ...e-time LTI model form is the linear state space model: x k+1 = Ax k + Buu k +B v v k +Bww k (9) y k = Cx k + �� k (10) An equivalent transfer function model in the form of matrix fraction descript=-=ion(Kailath, 1980) ca-=-n be written as: y k = [I \Gamma \Phi y (q \Gamma1 )] \Gamma1 [\Phi u (q \Gamma1 )uk + \Phi v (q \Gamma1 )v k + \Phi w (q \Gamma1 )w k ] + �� k (11) where q \Gamma1 is a backward shift operator. T... |

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Citation Context ...f controlling a system by solving a sequence of open-loop dynamic optimization problems was not new. Propoi, for example, described a moving horizon controller in 1963 (Propoi, 1963). Lee and Markus (=-=Lee and Markus, 1967-=-) anticipated current MPC practice in their 1967 optimal control text: One technique for obtaining a feedback controller synthesis from knowledge of openloop controllers is to measure the current cont... |

90 | A quasi-infinite horizon nonlinear model predictive control scheme with guaranteed stability - Chen, Allgöwer - 1998 |

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Citation Context ...shows a conventional control structure on the left for Unit 1 and a model predictive control structure on the right for Unit 2. Similar hierarchical structures have been described by Richalet et al. (=-=Richalet et al., 1978-=-) and Prett and Garc'ia (Prett and Garc`ia, 1988). At the top of the structure a plant-wide optimizer determines optimal steady-state settings for each unit in the plant. These may be sent to local op... |

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Citation Context ... PREDICTIVE CONTROL The development of modern control concepts can be traced to the work of Kalman in the early 1960's, who sought to determine when a linear control system can be said to be optimal (=-=Kalman, 1960-=-a; Kalman, 1960b). Kalman studied a Linear Quadratic Regulator (LQR) designed to minimize an quadratic objective function. The process to be controlled can be described by a discrete-time, determinist... |

59 | Robust process Control - Morari, Zafiriou - 1989 |

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Citation Context ...xcellent reviews of MPC theoretical issues, including the papers of Garc'ia et al. (Garc'ia, Prett and Morari, 1989), Ricker (Ricker, 1991), Morari and Lee (Morari and Lee, 1991), Muske and Rawlings (=-=Muske and Rawlings, 1993-=-) and Rawlings et al. (Rawlings, Meadows and Muske, 1994). The other papers in the present session by Mayne (Mayne, 1996) and Lee (Lee, 1996) summarize the very latest technical developments in MPC co... |

40 |
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Citation Context ...osed loop stable when the prediction horizon was set long enough to include the steady-state effect of all computed input moves. This is supported by a rigorous proof presented by Garc'ia and Morari (=-=Garc'ia and Morari, 1982-=-) which shows that the DMC algorithm is nominally stabilizing for a sufficiently large prediction horizon. Garc'ia and Morshedi then show how the DMC objective function can be re-written in the form o... |

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31 |
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Citation Context ...+j ) + b k (19) This form of feedback is equivalent to assuming an output disturbance that remains constant for all future time (Morari and Lee, 1991; Lee, Morari and Garc'ia, 1994). Rawlings et al. (=-=Rawlings et al., 1994-=-) show that this method of feedback removes steady-state offset, which provides theoretical support for its use. Variations of this basic feedback approach are used for the case of integrating dynamic... |

31 | An overview of nonlinear model predictive control applications, In: Allgöwer F., Zheng A. (Eds.), Nonlinear model predictive control, Birkhauser - Qin, Badgwell - 2000 |

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Citation Context ...imization. This prevents problems which may occur due to enforcing output constraints early in the prediction horizon of the dynamic optimization (see the discussion in Zafiriou's paper, for example (=-=Zafiriou, 1990-=-)). Only the HIECON and PFC algorithms consider hard output constraints in the dynamic optimization. Hard output constraints are ranked in order of priority so that low priority constraints can be dro... |

27 |
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(Show Context)
Citation Context ...eral researchers, including Ricker et al. (Ricker, Subrahmanian and Sim, 1988), Zafiriou and Chiou (Zafiriou and Chiou, 1993), and Genceli and Nikolaou (Genceli and Nikolaou, 1993). Zheng and Morari (=-=Zheng and Morari, 1995-=-) recently analyzed an infinite horizon MPC algorithm with soft output constraints implemented in this way. They show that global asymptotic stability can be guaranteed provided that the plant is not ... |

23 |
Nonlinear model predictive control: An assessment
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(Show Context)
Citation Context ... 1991), Morari and Lee (Morari and Lee, 1991), Muske and Rawlings (Muske and Rawlings, 1993) and Rawlings et al. (Rawlings, Meadows and Muske, 1994). The other papers in the present session by Mayne (=-=Mayne, 1996-=-) and Lee (Lee, 1996) summarize the very latest technical developments in MPC control theory. Froisy provides a vendor's perspective on industrial MPC technology and summarizes likely future developme... |

22 |
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Citation Context ...antee, for example, that the global optimum can be found. Bequette describes several approaches to solving the general nonlinear MPC problem in his review of nonlinear control for chemical processes (=-=Bequette, 1991-=-). Although solving the nonlinear MPC problem at each time step is much more difficult, Rawlings et al. (Rawlings et al., 1994) have shown that the nominal Lyapunov stability argument presented for li... |

22 |
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Citation Context ...er et al. first described the QDMC algorithm in a 1983 AIChE conference paper (Cutler, Morshedi and Haydel, 1983). Garc'ia and Morshedi published a more comprehensive description several years later (=-=Garc'ia and Morshedi, 1986-=-). Key features of the QDMC algorithm include: ffl linear step response model for the plant 6 MODEL PREDICTIVE CONTROL ffl quadratic performance objective over a finite prediction horizon ffl future p... |

21 |
Recent advances in model predictive control and other related areas
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(Show Context)
Citation Context ... (Morari and Lee, 1991), Muske and Rawlings (Muske and Rawlings, 1993) and Rawlings et al. (Rawlings, Meadows and Muske, 1994). The other papers in the present session by Mayne (Mayne, 1996) and Lee (=-=Lee, 1996-=-) summarize the very latest technical developments in MPC control theory. Froisy provides a vendor's perspective on industrial MPC technology and summarizes likely future developments (Froisy, 1994). ... |

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15 |
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Citation Context ...initial application in 1973. Cutler and Ramaker presented details of an unconstrained multivariable control algorithm which they named Dynamic Matrix Control (DMC) at the 1979 National AIChE meeting (=-=Cutler and Ramaker, 1979-=-) and at the 1980 Joint Automatic Control Conference (Cutler and Ramaker, 1980). In a companion paper at the 1980 meeting Prett and Gillette (Prett and Gillette, 1980) described an application of DMC ... |

15 | Nonlinear Predictive Control: Theory and Practice. Institution of Electrical Engineers - Kouvaritakis, Cannon - 2001 |

13 | Algoritmic Control of Industrial Processes - Richalet, Rault, et al. - 1976 |

11 | Control Systems Design - Goodwin, Graebe - 2001 |

10 |
Optimization and constrained multivariable control of a catalytic cracker unit
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(Show Context)
Citation Context ... unique performance criteria ffl cultural reasons (people, education, etc.) It is well known that the economic operating point of a typical process unit often lies at the intersection of constraints (=-=Prett and Gillette, 1980-=-). A successful industrial controller must therefore maintain the system as close as possible to constraints without violating them. In addition, process units are typically complex, nonlinear, constr... |

10 | An extension of Newton-type algorithms for nonlinear process control - Oliveira, Biegler - 1995 |

10 | Nonlinear model predictive control using neural networks - Piche, Sayyar-Rodsari, et al. - 2000 |

9 | GRG2 User’s Guide - Lasdon, Waren - 1984 |

9 | Evolution of an industrial nonlinear model predictive controller - Young, Bartusiak, et al. - 2001 |

8 |
Use of linear programming methods for synthesizing sampled-data automatic systems
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(Show Context)
Citation Context ...should be noted that the idea of controlling a system by solving a sequence of open-loop dynamic optimization problems was not new. Propoi, for example, described a moving horizon controller in 1963 (=-=Propoi, 1963-=-). Lee and Markus (Lee and Markus, 1967) anticipated current MPC practice in their 1967 optimal control text: One technique for obtaining a feedback controller synthesis from knowledge of openloop con... |

8 | Case studies of model predictive control in pulp and paper production - Subrahmanian, Sim - 1989 |

8 | Constraint handling and stability properties of model-predictive control - Oliveira, Biegler - 1994 |

8 | Feedback Controllers for the Process Industries - Shinskey - 1994 |

7 |
Design of robust constrained modelpredictive controllers with Volterra series
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(Show Context)
Citation Context ...g in the presence of constraints if the initial optimization problem is feasible. Additional work is needed to extend this result to the case of an imperfect plant model. Vuthandam et al. (Vuthandam, =-=Genceli and Nikolaou, 1995-=-) have done this already for a modified QDMC algorithm; their results should be useful to many industrial practitioners. Identification Test Protocol Test signals are required to excite both steady-st... |

7 |
Model predictive control: The good, the bad, and the ugly
- Morari, Lee
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(Show Context)
Citation Context ...and paper. Several authors have published excellent reviews of MPC theoretical issues, including the papers of Garc'ia et al. (Garc'ia, Prett and Morari, 1989), Ricker (Ricker, 1991), Morari and Lee (=-=Morari and Lee, 1991-=-), Muske and Rawlings (Muske and Rawlings, 1993) and Rawlings et al. (Rawlings, Meadows and Muske, 1994). The other papers in the present session by Mayne (Mayne, 1996) and Lee (Lee, 1996) summarize t... |

7 | W.(1998) A field study of the industrial modelling process - Foss, Lohmann, et al. |

6 | Steady states and constraints in model predictive control - Rao, Rawlings - 1999 |