Piecewise-linear controller synthesis with applications to inventory control of switched production systems☆
Introduction
Nowadays, with the globalization of business, we are living in a world where the increasing competition between companies is dictating the business rules. Therefore, to survive, the companies are forced to focus seriously on how to produce high-quality products at low cost and on how to respond quickly to rapid changes in the demand. The key competitive factors are the new technological advances and the ability to use them to quickly respond to rapid changes in the market. Production planning is one of the key ingredients that has a direct effect on the ability to quickly respond to rapid changes in the market. It is concerned with the optimal allocation of the production capacity of the system to meet the demand efficiently. In general, this problem is not easy and requires significant attention.
Inventory control and production planning are classical, yet complex, subjects. Inventory, broadly defined as “quantity of commodity”, serves basically as a buffer between two processes: supply and demand. It is necessary because there are obvious differences in rates and timing between supply and demand. Policies for inventory control and production planning involving forecasting are therefore extremely important in the management of companies. The problem of production planning has been tackled by many authors and many research results have been reported in the literature. Among them we quote the developments from (Axsater, 1985, Boukas and Liu, 2001, Disney et al., 2000, Gavish and Graves, 1980, Grubbstrom and Wikner, 1996, Hennet, 2003, Ridalls and Bennett, 2002, Sethi and Zhang, 1994, Sethi et al., 2005, Towill et al., 1997, Wiendahl and Breithaupt, 2000) and the references therein. In these references, both stochastic and deterministic models have been proposed to handle the production planning and/or maintenance. Different approaches have been used to tackle production planning, such as, dynamic programming, linear programming, queuing theory, and Petri nets. Recently, a new concept of manufacturing and production planning control has emerged based on the availability of radio frequency identifiers (RFID) called auto-id-based control (McFarlane, 2002).
This paper models deterministic production systems with switching. The switching corresponds to changes in the stock between two fundamentally different situations: having stocked products and running out of stocked products. In that sense, this work falls under the area of inventory control. It is proposed that the control policy (or decision-making) should also include switching to cope with the switched nature of the system dynamics. Previous research on control theoretic methods applied to production systems has not addressed the case of switched production systems. Moreover, it has been mostly focused on the use of optimal control techniques leading to the solution of the Hamilton–Jacobi–Bellman equation. However, this equation is very hard to solve and numerical solutions can only be obtained for very simplified cases of very low state order. It is also very difficult to include state and control constraints. The solution method presented in this paper will depart considerably from previous research by showing how PWA control theory can be used to handle production planning of constrained switched production systems. The method developed in the paper can easily incorporate state and control constraints and is based on LMIs, which are convex constraints. Therefore, they can be solved very efficiently, scaling very well with the size of the system. To the best of our knowledge the methodology we are using in this paper to formulate and solve the problem has never been used in production planning before. The main contribution of the paper is therefore that production systems are modeled as constrained switched systems and the inventory control problem is formulated as a switched problem with a PWA control law.
The rest of the paper is organized as follows. In Section 2, the production planning problem is described for the case of production of a single part type and the problem assumptions are stated. The main contribution of the paper is presented in Section 3. The inventory control problem is formulated as a switched control problem posed as an optimization program subject to LMI constraints, which can be solved efficiently using currently available software packages. Section 4 presents two numerical examples to show the effectiveness of the proposed methodology to handle the inventory control problem. The paper then finishes by presenting possible extensions and the conclusions.
Section snippets
Problem statement
As a preliminary step, let us consider the case of a production system producing one part type and formulate the inventory control problem. Let denote the stock level, the production rate and the demand rate at time t, respectively. It is assumed that the demand rate is composed of a known constant component (maybe obtained by forecasting) plus an unknown time-varying (possibly fluctuating) component with finite energy, i.e.,so that a
Problem formulation and solution
This section formulates mathematically the piecewise-linear control problem from Definition 1 as an optimization program subject to LMI constraints. For system (11)–(12) we will use a PWA control lawwhere, in this case, . Using (16) in (11)–(12) yields Remark 5 The method that will be developed in this section is not restricted to the system from Definition 1. Rather, it is applicable to any system whose model is described by (11) and that verifies constraint (17)
Numerical examples
To illustrate the effectiveness of the developed results, we consider in this section two manufacturing production systems. Example 1 Consider a manufacturing system producing one item. The problem data for this example can be found in Table 1. For this problem, , and . The corresponding matrices are Notice that this system fits the general model (11) with constraint (17). Solving the optimization problem 1 using Yalmip (
Conclusions
This paper dealt with the inventory control problem for a deterministic production system with given deterministic demand rate plus an unknown fluctuating demand rate with finite energy whose bound is known. This problem has been modeled as a control problem of a switched (PWA) system and it has been solved using new results on piecewise-linear control theory developed in the paper.
The proposed approach has shown that switched control theory can be applied to inventory control problems. This
Acknowledgments
The authors would like to acknowledge the Natural Sciences and Engineering Research Council of Canada (NSERC) for partially funding this research.
Luis Rodrigues was born in Portugal. He earned his “licenciatura” and his M.Sc. degrees in Electrical Engineering and Computers from IST, Technical University of Lisbon. He obtained his Ph.D. in Aeronautics and Astronautics from Stanford University in 2002. He worked as a consultant in speech modeling and recognition for Eliza Corporation in USA and as a project manager for Ydreams in Portugal before joining Concordia as an Assistant Professor in 2003. His research interests lie in the areas of
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Luis Rodrigues was born in Portugal. He earned his “licenciatura” and his M.Sc. degrees in Electrical Engineering and Computers from IST, Technical University of Lisbon. He obtained his Ph.D. in Aeronautics and Astronautics from Stanford University in 2002. He worked as a consultant in speech modeling and recognition for Eliza Corporation in USA and as a project manager for Ydreams in Portugal before joining Concordia as an Assistant Professor in 2003. His research interests lie in the areas of switched, hybrid and optimal control with applications to manufacturing, aerospace, automotive, and biological systems (such as the vocal tract).
El-Kebir Boukas was born in Morocco. He received the engineer degree in Electrical engineering in 1979 from Ecole Mohammadia d’Ingenieurs, Rabat, Morocco, and the M.Sc. and Ph.D. degrees in Electrical engineering both from Ecole Polytechnique de Montreal, Canada in 1984 and 1987, respectively. He worked as an Engineer in R.A.I.D. Tangier, Morocco, from 1979 to 1980, and as a Lecturer at the University Caddy Ayyad, Marrakech, Morocco from 1980 to 1982. In 1987, he joined the Mechanical Engineering Department at Ecole Polytechnique de Montreal where he is now a full professor. His research interests include stochastic control, robust control, optimal control, modeling and control of flexible manufacturing systems and mechatronics. He is the author of three books in control and more than 25 invited chapters in edited books. He is the author of more than 200 technical publications, most of them in control theory and manufacturing systems.
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This paper was not presented at any IFAC meeting. This paper was recommended for publication in revised form by Associate Editor Qing Zang under the direction of Editor Suresh Sethi.