Bridging the gap between planning and control: A cascaded MPC approach
Abstract: A new 1-to-n MPC cascade strategy is proposed for bridging the gap between planning and control and for improving operating profitability. Industrial facilities, such as oil refineries, LNG plants and alumina plants, are typically comprised of multiple processing units and have thousands of control measurements and PID loops in aggregate. From a plantwide perspective, control and planning are almost always coupled: Planning relies on control to establish the feasible region for optimization, while control relies on planning to run the plant at the most profitable operating point. Ideally, control and plantwide optimization should be designed jointly. A primary unsolved issue in the joint-design approach is how to provide simultaneously decentralized controls at the unit level and centralized optimization at the plant level. Decentralized MPC solutions are more desirable because of their better operability and flexibility in dealing with unit upsets, equipment failures, and maintenance, whereas centralized plantwide optimization is more desirable because the bird’s eye view in the planning model distills out unessential or even obscuring details. Currently, this complex problem is decomposed into several layers – with a plantwide planning solution layer at the top, an MPC solution layer at the unit level, and possibly one or two intermediate layers in between (scheduling and/or RTO layers, for example). A considerable drawback of this decomposition lies in a lack of guaranteed solution consistency across multiple layers. In practice the planning optimization layer is rarely, if at all, implemented as a part of the closed-loop control system. As a result, a significant amount of optimization benefits still remain unreachable, and a recent benefit study confirms that there is an estimated amount of 20-30 million US dollars of un-captured benefits per year for a mid-sized North America refinery. The proposed 1-to-n MPC cascade strategfill the void of gate-to-gate (i.e., plantwide) optimization as part of an automatic control system. The master MPC uses an existing single-period planning model (or other suitable reduced models) as a seed model and performs the plantwide economic optimization inside its embedded optimizer. It cascades on top of multiple slave MPC controllers at the unit level, and the slave MPC controllers provide the master with the unit’s operating states and constraints. Therefore, the plantwide optimal solution from the master will always honor all the unit-level operating constraints in the slave MPCs. Jointly, the cascaded MPC provides simultaneously decentralized controls at the unit level and centralized gate-to-gate optimization at the plant level in a single, consistent control system. Biography: Joseph Lu received his Ph.D. degree in Chemical Engineering from University of Washington in 1990. He joined Honeywell in 1990, held various research and development roles and currently is Senior Fellow and Chief Scientist of Advanced Solutions. His research interest has primarily been in the areas of advanced control, robust control and multi-unit or plantwide optimization for process industries. Joseph is the recipient of the 2010 Control Engineering Practice Award from American Automatic Control Council and is a member of IEEE. |