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Biotechnology industry is expanded rapidly due to the progress in the understanding of bio-systems and the increased demand for products. Since bioprocess dynamics are almost always affected by physical parameter variations and external disturbances, the need for robust control techniques is of major importance in order to ensure the desired behavior of the process. The overall process equilibrium...
The present paper deals with the production of Saccharomyces cerevisiae, described by a sixth order nonlinear state space model. The control objective is to ensure the process stability and desirable specifications in the presence of disturbances and lack of reliable state measurements. First, the model of the process and its properties are presented. Next the ability of multi-layer Neural Networks...
The present paper considers the problem of designing guaranteed cost controllers minimizing multiple quadratic performance objectives, for linear systems with parametric uncertainties. The design procedure uses the LMI optimization technique. By setting the multi-objective control problem in an LMI form, one may find the suitable uncertainty decomposition which allows to compute a positive definite...
Robust control of dynamic linear systems with parametric uncertainties in the LQG context often leads to the so-called guaranteed cost control approaches. In such cases it is based on the solution of generalized Riccati equations. This paper presents an overview of robust control problems related to the guaranteed cost control approach and the corresponding solutions. It is shown that different uncertainty...
This paper focuses on the problem of fuzzy guaranteed cost control and stabilization of discrete-time nonlinear systems with polytopic uncertainties. Takagi-Sugeno fuzzy models with uncertainties are used in order to model the uncertain nonlinear systems and the Parallel Distributed Compensation (PDC) scheme is utilized for the construction of the fuzzy controller. A quadratic cost function is considered...
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