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This allows easy design of each controller and good control performance for both set-point and disturbance responses.
The simulations compared the performance of each controller in their abilities to effectively control the infusion and concentration rates for atracurium and isoflurane to regulate set points for muscle relaxation and BP in the face of noisy signals.
The logical functions of each controller can be recovered from the obtained feedback control matrix.
Given a control architecture and the functional specification of each controller module, formal proofs are established and discharged to demonstrate the logical equivalence between the functional specification and the code implementation of logic controllers.
Finally, the experimental results are analysed in various tests using both control algorithms to show the benefits and disadvantages of each controller.
Experimental results illustrate the performance of each controller.
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Stability proofs of the overall strategy require estimates of the Region of Attraction (ROA) for each controller, that are discussed in the paper.
Essentially, a control rule is of concern and each controller needs to follow this rule.
The control design of each local controller is achieved using internal model control structure.
Resulting control effort is computed as a sum of weighted control efforts of each vertex controller.
This can be viewed as distributed control of inventory, in which each controller is making autonomous decisions based on local objectives.
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