Sharif Digital Repository

In this paper, a new approach is presented for optimal control of large-scale chemical processes. In this approach, the chemical process is decomposed into smaller sub-systems at the first level, and a coordinator at the second level, for which a two-level hierarchical control strategy is designed. For this purpose, each sub-system in the first level can be solved separately, by using any conventional optimization algorithm. In the second level, the solutions obtained from the first level are coordinated using a new gradient-type strategy, which is updated by the error of the coordination vector. The proposed algorithm is used to solve the optimal control problem of a complex nonlinear... 

This paper presents a two-level optimal control for the binary distillation column. From the control point of view, the binary distillation column is a high-order system consisting of several interconnected subsystems (trays) that aim to maximize output purity. Controlling the system in a hierarchical manner not only decreases complexity and solution time but also can improve the control structure's reliability. In this study, the distillation column is decomposed into NT second-order subsystems, each representing one stage (one tray). Accordingly, the cost function is decomposed, and thus, the overall problem is converted into NT lower-order subproblems where each tray has its own... 

In this paper, a new decomposition-coordination framework is presented for two-level optimal control of large-scale nonlinear systems. In the proposed approach, decomposition is performed by defining an interaction vector, while coordination is based on a new interaction prediction approach. In the first level, sub-problems are solved for nonlinear dynamics using a gradient method, while in the second level, the coordination is done using the gradient of coordination errors. This is in contrast to the conventional gradient-type coordination schemes, where they use the gradient of Lagrangian function. It is shown that the proposed decomposition-coordination framework considerably reduces the... 

This paper presents a fuzzy-based interaction prediction approach (F-IPA) for two-level optimal control of large-scale systems. The design procedure uses a decomposition/coordination framework of hierarchical structures. At the first level, the system is decomposed into subsystems for which subproblems are formed. At the second level, a fuzzy coordinator is used to predict the coordination parameters needed to coordinate the solutions of the first level subproblems. The fuzzy coordinator uses a critic vector to evaluate its performance and learn its parameters by minimizing an energy function. The proposed control scheme is implemented on a two-degrees-of-freedom (2DOF) model of robot...