25 research outputs found
Interval Predictor Models for Data with Measurement Uncertainty
An interval predictor model (IPM) is a computational model that predicts the range of an output variable given input-output data. This paper proposes strategies for constructing IPMs based on semidefinite programming and sum of squares (SOS). The models are optimal in the sense that they yield an interval valued function of minimal spread containing all the observations. Two different scenarios are considered. The first one is applicable to situations where the data is measured precisely whereas the second one is applicable to data subject to known biases and measurement error. In the latter case, the IPMs are designed to fully contain regions in the input-output space where the data is expected to fall. Moreover, we propose a strategy for reducing the computational cost associated with generating IPMs as well as means to simulate them. Numerical examples illustrate the usage and performance of the proposed formulations
Engineering and technology applications of control co-design: a survey
Control-inspired design, as the name suggests, involves drawing inspiration from control theory to design other engineering systems. Engineers may use the principles of feedback control to design systems that can adapt and self-correct in response to changing conditions. This technique is known as Control Co-design (CCD), and it focuses on the redesign of dynamics and subsystem interactions. CCD offers several benefits, such as improved performance, reduced design time and cost, and increased reliability, and has been applied to a variety of areas. In this paper, we present a review of 197 articles related to CCD and highlight the main topics of its applications, such as renewable energy, vehicular and aircraft control systems and communication systems in control. We delimit the applications of CCD in the field of engineering, providing an introductory understanding of this topic and presenting the main works developed in this field in recent years, as well as discussing the tendencies and benefits of CCD. The paper offers an in-depth conceptualisation of CCD. A theoretical example is provided to illustrate CCD’s application in a Hybrid Wind-Wave Platform (HWWP), detailing the interaction between aerodynamic and hydrodynamic design domains and their control challenges, along with discussions on simultaneous and nested CCD formulations
Variabilidade genética de populações de fava d'anta (Dimorphandra mollis) da região norte do Estado de Minas Gerais
A aplicação do método do arco da problematização na coleta de dados em pesquisa de enfermagem: relato de experiência
Acúmulo de matéria seca e óleo nas sementes de pinhão-manso e qualidade do óleo extraído
Phytosociology of the herbaceous-subshrub layer of a rupestrian complex in Serra do Espinhaço, Brazil
Robust periodic observer-based control for periodic discrete-time LTV systems
New conditions for the design of robust periodic observer-based controllers for periodic discrete-time linear time-varying (LTV) systems are proposed in this paper. The control system is designed to be robust to external noises, and such robustness is achieved by minimizing the H-infinity norm from the input noise to the error output in the observer design, and the H-infinity norm from the error and disturbance signal to the output in the control design. Concerning the observer, two LMI (Linear Matrix Inequality) conditions are proposed. As part of the main contribution, an LMI condition, based on a dual representation of the LTV system, is also proposed for the synthesis of a robust state-feedback controller that makes use of the observed states rather than the actual states. A numerical example illustrates the validity of the proposed technique29422947CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPsem informaçãosem informação2014/03669-1; 2015/00269-5American Control Conference (ACC)2016-07-06Boston, MA, Estados Unido
Control of Hysteretic Systems Through an Analytical Inverse Compensation Based on a NARX Model
It has been widely accepted that a hysteretic system can be controlled by combining inverse compensation with feedback. Among the strategies to identify hysteretic systems, data-driven models have been received great attention due to its flexibility and ability to online and adaptive estimation. Nevertheless, less attention has been paid to determine its inversion, which is essential to use such models in control applications. The novelty of this paper is twofold. First, we propose a method to obtain analytically the inverse compensation of a hysteretic system modeled by a Nonlinear Auto-Regressive Model with eXougenous input (NARX) representation with a bounding structure. Second, this paper presents an adapted nonautonomous electronic circuit with rate-independent hysteresis and linear dynamics, which is used as a benchmark to test the proposed methodology. The experimental results have shown the efficiency of the proposed technique