André Laurindo Maitelli

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In this paper a new approach of bilinear predictive control is presented. The approach is based in the Bilinear Generalized Predictive Control (BGPC), strategy that uses a time-step quasi-linearised NARIMAX model. In that approach, due to the used model, a prediction error exist, which increases with the prediction horizon, degrading the performance of that(More)
This paper shows a new approach of Model Predictive Control (MPC). A multivariable bilinear multi-model is presented. A set of local bilinear models is identified and the proposed algorithm implements the timestep quasilinearization in trajectory. A metric based in norms is presented to measure the distance from the current operation point to a designed(More)
The quick progress in technology has brought new paradigms to the computing area, bringing with them many benefits to society. The paradigm of ubiquitous computing brings innovations applying computing in people's daily life without being noticed. For this, it has used the combination of several existing technologies like wireless communications and(More)
-Arterial pressure control is an important task, mostly in postsurgical patients. This work proposes an adaptive system to patient’s arterial blood pressure control using sodium nitroprusside. The proposed system uses Proportional-Integral (PI), Fuzzy-PI, rule-based and predictive controllers. To introduce an adaptive characteristic to PI controller, it was(More)
In this paper is presented a contribution for development and implementation of nonlinear predictive control based on Hammerstein models as well as to make properties evaluation. In this work, nonlinear predictive control development has been used the time-step linearity method and a compensation term is used with an objective to make better the controller(More)
Models of real systems are of fundamental importance for its analysis, making it possible to simulate or predict its behavior. Additionally, advanced techniques for controller design, optimization, monitoring, fault detection and diagnosis components are also based on process models. One of the most used techniques to model a system is by identification.(More)
Some diseases, such as hypertension, require a close control of the patient's blood pressure. This is even more critical when that patient is going through--or has just underwent--a surgical procedure In such situations, reducing blood pressure to normal levels is of paramount importance. Usually, this demanding and time consuming monitoring is done(More)