Sharif Digital Repository

A Real-Time Optimization (RTO) strategy incorporating the fuzzy sets theory is developed, where the problem constraints obtained from process considerations are treated in fuzzy environment. Furthermore, the objective function is penalized by a fuzzified form of the key process constraints. To enable using conventional optimization techniques, the resulting fuzzy optimization problem is then reformulated into a crisp programming problem. The crisp programming problem is solved using both Sequential Quadratic Programming (SQP) and Heuristic Random Optimization (HRO) techniques for comparison purposes. The proposed fuzzy RTO strategy is demonstrated via the Tennessee Eastman benchmark process,... 

A stochastic real time optimization (SRTO) which has an efficient result has been implemented on the Tennessee Eastman (TE) challenging problem. In this article a novel stochastic optimization method, the so-called heuristic random optimization (HRO) proposed by Li & Rhinehart is used which attempts to rationally combine features of both deterministic and random (stochastic) methods. Further, an on-line nonlinear identifier via extended Kalman filter (EKF) is used to supply the plant model for model-based optimization algorithm. Using the information obtained from EKF an on-line HRO is accomplished by a random search method whose search directions and steps are considerably reduced by some...