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However, hybrid MPC is based on hybrid model that captures both logical and continuous dynamics in one unified framework.
Both logical and continuous frameworks have advantages and disadvantages above-mentioned.
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Logical and continuous control systems are usually designed separately.
This may result in unforeseen interactions between logical and continuous control and in the deterioration of the control performance.
Control results obtained with hybrid MPC are indeed fairly good and they show clear improvement over the results achieved with separate design of logical and continuous control.
These approaches can be further organized into two larger categories: logical and continuous models.
These approaches can generally be grouped into two larger categories: logical and continuous models.
The combination of logical and continuous modelling enables a thorough analysis of different determinants of bistable regulation, i.e. network topology and biochemical kinetics, and allows for an incorporation of experimental data from heterogeneous sources.
Combining the advantages of the logical and continuous modelling approaches may allow to overcome their individual limitations and thus significantly increase the computational feasibility of the analysis, while keeping a high level of detail.
ChemChains combines the advantages of logical and continuous modeling and provides a way for laboratory biologists to perform in silico experiments on mathematical models easily, a necessary component of laboratory research in the systems biology era.
Programming structures become complex, as the possibilities of error proneness (both logical and syntax errors) increase due to the continuous increment of variabilities in the pre-processed source code.
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