Constrained robust model predicted control of discrete-time Markov jump linear systems

• Autor(a) principal: Rosileide de Oliveira Lopes
• Data de Publicação: 2019
• Outros Autores: Eduardo Mazoni Andrade Marçal Mendes, Leonardo Antonio Borges Torres, Reinaldo Martinez Palhares
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Repositório Institucional da UFMG
• Texto Completo: https://doi.org/10.1049/iet-cta.2018.5543; http://hdl.handle.net/1843/57001; https://orcid.org/0000-0003-2805-7140; https://orcid.org/0000-0002-3267-3862; https://orcid.org/0000-0003-3039-6547; https://orcid.org/0000-0003-2470-4240
• topic: Controle; Controle de Processos; Controle Preditivo Baseado em Modelo (MPC); Sistemas com saltos Markovianos; Controle Robusto; LMIs; Engenharia Mecânica; Matemática

This study is concerned with the problem of designing a robust model predictive control (MPC) for a class of uncertain discrete-time Markov jump linear systems. The main contribution is a set of linear matrix inequality (LMI) conditions obtained under new control policies for the unconstrained as well as the constrained MPC when uncertainties are present both in the system's matrices and in the transition probabilities of the modes. For the constrained MPC, hard constraints are considered over the input control and the states and results are extended to the so-called multi-step mode-dependent state-feedback control design. To illustrate the improvements obtained with the new set of LMI conditions, numerical simulations are carried out and compared with a recent reference in the literature.