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In fluidized-bed gas-phase polymerization reactors, several grades of polyethylene are produced in the same equipment by changing the operating conditions. Transitions between the different grades are rather slow and result in the production of a considera ...
For the optimization of dynamic systems, it is customary to use measurements to combat the effect of uncertainty. In this context, an approach that consists of tracking the necessary conditions of optimality is gaining in popularity. The approach relies st ...
A benchmark problem for restricted complexity controller design is introduced. The objective is to design the lowest-order controller which meets the control specifications for an active suspension system. The input-output data of the plant are provided on ...
J. V. Kadam, W. Marquardt Lehrstuhl für Prozesstechnik, RWTH Aachen University, Turmstr. 46, 52064 Aachen, Germany B. Srinivasan, D. Bonvin Laboratoire d’Automatique, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland Optimization of T ...
This paper presents an optimal control scheme for a real-time feedback control rate-monotonic scheduling (FC-RMS) system. We consider two-version tasks composed of a mandatory and an optional part to be scheduled according to the FC-RMS. In FC-RMS, the con ...
The performance of predictive controller is typically poor when the true plant evolution deviates significantly from that predicted by the model. A robust approach that considers model uncertainty explicitly is then needed. However, it is often difficult t ...
Improving the productivity of fed-batch filamentous fungal fermentations can be formulated as a dynamic optimization problem. However, numerical optimization based on a nominal process model is typically insufficient when uncertainty in the form of model m ...
Optimal (re)scheduling of production in industrial processes increases economic efficiency through timely and optimal use of limited resources. In this article an approach to scheduling based on the use of hybrid systems and model predictive control is pre ...
Closed-form Model Predictive Control (MPC) results in a polytopic subdivision of the set of feasible states, where each region is associated with an affine control law. Solving the MPC problem on-line then requires determining which region contains the cur ...
In this paper, it is shown that dynamic optimization problems of first-order systems can be transformed into a static paramertic programming problem, where the state plays the role of the parameter. Thus, an optimal feedback law is obtained. This concept i ...
