Anderson Luiz de Oliveira Cavalcanti

GENERALIZED PREDICTIVE CONTROL BASED IN MULTIVARIABLE BILINEAR MULTI- MODEL

Abstract 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 controller in other operation point. Application results are showed in a case study.

Integrating mobile devices and industrial automation through web services

The increasing need of integration among the many kinds of automation systems inside the companies is causing process engineers and IT managers to provide solutions which can facilitate the data transmission from production level to higher levels of the industrial automation pyramid. Static architectures with high degree of engagement, platform dependency and low level of interoperability, make the service oriented paradigm get space in industrial automation scenario. Allied to all these needs, some new requirements such as mobility already shows that are indispensable today. For example, receiving a programmed alarm of an industrial plant or accessing production data through a cell phone is not just one more superfluous feature, but a necessity for the business dynamics of the company. In this context, this article presents an architecture for the integration of mobile devices in an industrial automation scenario, using Web Service.

Hybrid fuzzy and robust controller applied to a DC-DC boost converter

This paper purposes a hybrid control method applied to a DC-DC Boost converter in order to maintain a constant output voltage and ensure the supply of good power quality to the load. The hybrid controller consists of a fuzzy supervisor which mixes control signals of two types of controllers: robust and fuzzy. Each one of these controllers has good performance in certain operational conditions. The supervisor determines the ideal proportion of the action provided by the controllers in each operational condition. The simulations show that fuzzy and robust control signals can be mixed to provide a good power quality to the load ensuring fast transient response and zero steady-state error due to input voltage and load variations.

A phase margin metric for multi-model multivariable MPC

This paper deals of a new metric for multi-model approach, based in phase margin. A quasilinear generalized predictive controller (QGPC) is designed for each chosen operating regime and the metric calculates a weighting factor for each controller. A case study with a simulated debutanizer distillation column is showed.

Identification of Two-Time Scaled Systems Using Prefilters

This paper deals with the identification of two-time scale linear dynamic systems, which are an important class of multiscale systems. Classical identification processes may fail to yield accurate parameters for systems of this class and, for this reason, the authors propose two different techniques to estimate the system parameters. The first technique utilizes two prefilters that are iteratively tuned. The second one considers wavelet filters that are tuned based on the results of the first iterative algorithm. Identification and analysis results for a dynamical aircraft model are shown to demonstrate the algorithm’s performance.

Visual Language for Use Case Description

Use cases have been widely adopted by software engineers to model user–system interaction. However, its fragmented and textual description of functionalities has been inadequate for user‐centered design concerns. This has led human–computer interaction professionals to create their own methods and techniques, which has often had the opposite philosophy from that used by software engineers when modeling user–system interactions. Therefore, the present paper proposes the Visual Language for Use Case Description aiming to improve the support of use cases for user‐centered design by projecting a common artifact for the communication between both the human–computer interaction and the software engineering communities. To obtain the perceptions of potential users about Visual Language for Use Cases Description, an experimental study involving software development students and professionals was conducted. Copyright

A Proposal based on Frequency Response for Multi-Model Controllers

This paper presents an alternative approach to control nonlinear plants. The nonlinear system to be controlled is decomposed into a number of operating points and a GPC controller is properly designed, based on local linear model for each point. A metric based on frequency response of each local linear model is proposed in order to consider the contribution of each local controller in the signal sent to the plant. Two applications are presented. The first application in a simulated plant consists of a continuous stirred tank reactor (CSTR) and the second consists of a coupled tanks system level control.

Robust control applied in Buck Boost converter in a photovoltaic system: A new proposal

The utilization of renewable energies like wind energy and solar energy, have been grown in the last decades. In the solar energy, photovoltaic modules are connected with a power stage for electric energy production. Normally, when the converter works for some time, yours inductive and capacitive components suffer heating, causing an increase on the converters output resistance. This problem changes the systems operating point, contributing directly in output power loss. The main objective of this work is synthetize a robust control that minimizes the effects of the converter inductor parasite resistance and possible modifications of solar radiation. The main objective of the controller is maintaining a constant voltage in the output load considering uncertainty at the duty cycle in the operating point. The results showed that the robust control techniques H2 and H∞ minimized the effects of the uncertainties and the disturbances approximating the system output response to its operating point.

Multi-Model Approaches for Bilinear Predictive Control

It is well known that linear controllers can exhibit serious performance limitations when applied to nonlinear systems since nominal linear models used during design cannot represent the nonlinear plant in its whole operating range (Arslan et al., 2004). For this reason, several researches has been proposed new techniques in order to supply a solution for this problem. The main alternative technique, proposed by academy, to resolve the referred problem is known as multi-model approach. The basic idea of multi-model approach consists in decompose the system’s operating range into a number of operating regimes that completely cover the chosen trajectory as showed in (Foss et al., 1995). There are, basically, two approaches for multi-model. The first one consists of to design a set of suitable controllers (one for each operating regime) and to calculate weighting factors to them as showed in (Arslan et al., 2004) and (Cavalcanti et al., 2007a). The global control signal is a weighting sum of the contributions of each controller. The second one consists of to build a global model as a weighting sum of each local model as showed in (Foss et al., 1995) and (Cavalcanti et al., 2007b). In both cases, a way to measure distances between models is defined. Multivariable Model Predictive Control (MMPC) has been presented in this chapter. MPC is the an of the most important control technique used in industry. Multivariable Bilinear Generalized Predictive Control (MBGPC) is formulated and, its alternative solution, Multivariable Bilinear Generalized Predictive Control with Iterative Compensation (MBGPCIC) is presented. This chapter shows either proposed metrics in order to build multi-model based controllers (based in MBGPC and MBGPCIC) and presents simulation results applied in distillation columns.