The efficient real-time plant-wide coordination of petrochemical production sites is a challenging and yet not fully resolved problem and its solution can substantially improve the productivity and the efficiency of such complex petrochemical plants. While a site-wide integrated optimization might be feasible in principle, the size of the problem, the unavailability of data and the management structures of the plants favour a distributed solution, where the global coordination has to be achieved by suitable mechanisms. In this paper we propose price based coordination in a moving horizon setting to achieve plant-wide real-time coordination of the utilization of shared resources without communication of detailed knowledge of the structure of the subsystems. The shared resources are considered as market commodities that are traded between the units and global coordination is achieved by real-time adjustment of their market prices. We provide results of different price coordination methods for a model of an integrated petrochemical site. The results clearly show that market mechanisms can be applied for the coordination of large sites in the petrochemical industry.

Model Predictive Controller Employing Genetic Algorithm Optimization of Thermal Processes with Non-Convex Constraints | InTechOpen, Published on: 2012-03-21. Authors: Goran Stojanovski and Mile Stankovski

A novel robust tracking control technique for time-delay systems with uncertain time-delays based on fuzzy T-S is presented. Fuzzy T-S model with parametric uncertainties is employed to represent the uncertain time-delay plant. This control synthesis design is shown reduce the tracking error considerably for all bounded reference inputs while guaranteeing the H ∞ performance. The proposed solution has advantage of employing only a simple fuzzy controller and no complicated adaptive scheme. The fuzzy tracking control synthesis is parameterized in terms of a linear matrix inequality, which are solved efficiently by using convex optimization techniques. This method has been applied to trailer-truck example and respective numerical and simulation results demonstrate its valid applicability and efficiency.

We describe several predictive control approaches for high consumption industrial furnace control. These furnaces are major consumers in production industries, and reducing their fuel consumption and optimizing the quality of the products is one of the most important engineer tasks. In order to demonstrate the benefits from implementation of the advanced predictive control algorithms, we have compared several major criteria for furnace control. On the basis of the analysis, some important conclusions have been drawn.