A phosphoric acid production plant and its controls have been studied. New controls and monitoring systems which are partly realized with fuzzy logic, have been installed. Sulphuric acid concentrations in two reactors...
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A phosphoric acid production plant and its controls have been studied. New controls and monitoring systems which are partly realized with fuzzy logic, have been installed. Sulphuric acid concentrations in two reactors are controlled with fuzzy logic modules. The fuzzy logic concentration control is compared with traditional PID-control and Internal Model control. Some modelling work that has been necessary in order to be able to design the IMC-system is presented. A performance index for phosphoric acid filtration unit has been introduced and it is one of the variables that are used to control the amount of raw material feed. Two fuzzy logic modules are used for this purpose. The first one develops the performance index and the other one the proposals for the new raw material feed.
A direct model reference adaptive control (MRAC) algorithm is used to compute the infusion of two drugs in order to control blood pressure and cardiac output in a realistic physiological nonlinear multiple-input multi...
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ISBN:
(纸本)0080417175
A direct model reference adaptive control (MRAC) algorithm is used to compute the infusion of two drugs in order to control blood pressure and cardiac output in a realistic physiological nonlinear multiple-input multiple-output representation. Consideration is given to the effects of digitization, unequal output sampling rates, and to a modification to alleviate the nonsatisfaction of a positive real condition.
It is shown that the network representation (as obtained through the generalized bond graph formalism) of non-resistive physical systems in interaction with their environment leads to a well-defined class of (nonlinea...
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ISBN:
(纸本)0080419011
It is shown that the network representation (as obtained through the generalized bond graph formalism) of non-resistive physical systems in interaction with their environment leads to a well-defined class of (nonlinear) controlsystems, called port-controlled Hamiltonian systems. A first basic feature of these systems is that their internal dynamics is Hamiltonian with respect to a Poisson structure determined by the topology of the network and to a Hamiltonian given by the stored energy. Secondly the network representation provides automatically (intrinsically to the notation) to every port-control variable (input) a port-conjugated variable as output. This definition of port-conjugated input and output variables, based on energy considerations, is shown to have important consequences for the observability and controllability properties, as well as the external characterization of port-controlled Hamiltonian systems.
This paper presents a set of real time experiments conducted to demonstrate the performances of a partial state reference model adaptive controller on a flexible transmission system. The partial state reference model ...
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ISBN:
(纸本)0080417175
This paper presents a set of real time experiments conducted to demonstrate the performances of a partial state reference model adaptive controller on a flexible transmission system. The partial state reference model control design is particularly derived using the generalized predictive control approach. Particular emphasis is put on those engineering design features of the adaptive controller, namely the tracking capability, the adaptation alertness and the robustness with respect to state disturbances and reduced order modelling.
A multivariable implicit self-tuning algorithm is presented together with the robustness analysis. The algorithm can be applied to non-minimum phase systems and does not require the explicit solution of the algebraic ...
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ISBN:
(纸本)0080417175
A multivariable implicit self-tuning algorithm is presented together with the robustness analysis. The algorithm can be applied to non-minimum phase systems and does not require the explicit solution of the algebraic matrix polynomial equation. The controller parameters are directly estimated from two implicit prediction models which contain the plant and controller parameters in bilinear form. The stability analysis is performed by applying the sector theory to a new error equation which is decomposed into two operators, namely, the modelling uncertainty and the parameter estimator. The robustness improvement is achieved in the sense that the frequency weighted estimator can choose a suitable nominal plant from the model set, which satisfies the Strictly Positive Real (SPR) Condition. Simulation results are presented to demonstrate the performance of the proposed adaptive controller.
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