This paper presents some properties regarding the Multivariable Generalized predictivecontroller (MGPC) designed in state space. The authors proposed the design of such a controller under the condition that it gives ...
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This paper presents some properties regarding the Multivariable Generalized predictivecontroller (MGPC) designed in state space. The authors proposed the design of such a controller under the condition that it gives ...
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This paper presents some properties regarding the Multivariable Generalized predictivecontroller (MGPC) designed in state space. The authors proposed the design of such a controller under the condition that it gives the same results as the input/output (I/O) formulation of the GPC proposed originally by Clarke. The main reason for redesigning the controller in state space is the power of the analysis tools available. These tools allow some properties to be treated more easily than under (I/O) formulation. These properties include: stability, robustness, closed loop representation, specifications, etc. This paper presents results related to: observability and controllability of the CARIMA model used, closed loop representation, uniqueness and the existence of control law without constraints and closed loop stability without constraints.
This work presents a powerful and flexible alternative for tuning PID controllers using Genetic Algorithms. The potential of this technique is shown using non-linear process models and a reference trajectory. Flexibil...
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This work presents a powerful and flexible alternative for tuning PID controllers using Genetic Algorithms. The potential of this technique is shown using non-linear process models and a reference trajectory. Flexibility is demonstrated by showing how to tune an optimal PID in various situations: model errors, noisy input, IAE minimization, and following a reference models, etc. These problems are solved by changing the minimization index.
The purpose of this paper is to describe the implementation of a hierarchical distributed control system for a chemical pilot plant using industrial standard components. The control system consists of three components...
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The purpose of this paper is to describe the implementation of a hierarchical distributed control system for a chemical pilot plant using industrial standard components. The control system consists of three components: regulatory control (mainly PID controllers), multivariable control (Dynamic Matrix controlcontroller) and the optimization and economic layer (Linear Programming). This work also includes details of the implementation tools: PROFIBUS, LabVIEW and data acquisition modules. The paper concludes with two possible solutions that deal with plants with integral behaviour.
This paper presents a modification to the generalized predictivecontrol algorithm which guarantees closed-loop stability. The GPC controller is designed using a terminal equality constraint. The available degrees of ...
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This paper presents a modification to the generalized predictivecontrol algorithm which guarantees closed-loop stability. The GPC controller is designed using a terminal equality constraint. The available degrees of freedom are presented to the designer as parameters called principal components. This components can be left or removed from the solution to get different performances. Two methods to select the degrees of freedom are presented based on percentage of index minimized and control effort applied to the process respectively. This methods can be an alternative to the empirical selection of the weighting control factor λ.
One of the first steps taken in any technological area is building a mathematical model. In fact, in the case of process control, modelling is a crucial aspect that influences quality control. Building a nonlinear mod...
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Solving multivariables and non-linear problems with constrains is usual when dealing with control problems. The classical way to solve this was through the decomposition into less complex problems: Sub-problems with l...
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