Modeling and control of discrete stochastic systems with poorly known dynamics

• Grant number: 16/13508-0
• Support Opportunities: Scholarships in Brazil - Master
• Start date: October 01, 2016
• End date: May 31, 2018
• Field of knowledge: Engineering - Electrical Engineering - Industrial Electronics, Electronic Systems and Controls
• Principal Investigator: João Bosco Ribeiro do Val
• Grantee: Filipe de Carvalho Pedrosa
• Host Institution: Faculdade de Engenharia Elétrica e de Computação (FEEC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

This research proposal concerns with the class of systems coined as Control Variation Increase Uncertainty (CVIU). There is a vast range of systems for which, due to their intrinsic nature, the application of identification techniques is infeasible. Hence, only an uncertain and simplified model for the dynamics is attainable for control design purposes. Illustrations of CVIU systems permeate scientific publications in extensive areas of Economics, Biology and Medicine. That said, an alternative method is proposed by characterizing such systems as stochastic systems in which the uncertainties arising from the nescience about their real dynamics are taken into consideration. The determination of an optimal control policy for CVIU systems unveils the occurrence of cautious control strategies in a limited region in the state space. The process of determining a optimal control policy presents itself as a tough numeric challenge to overcome through the solution of Hamilton-Jacobi-Bellman via dynamic programming. This proposal aims at extending to the discrete systems the concepts which have been studied by researchers at FEEC - Unicamp and have attained, for the continuous time systems, better results than other well established methods found in the literature in scenarios involving uncertainty. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

PEDROSA, FILIPE C.; NEREU, JOAO C.; DO VAL, JOAO B. R.. When control and state variations increase uncertainty: Modeling and stochastic control in discrete time. AUTOMATICA, v. 123, JAN 2021. (16/08645-9, 16/13508-0)

PEDROSA, FILIPE C.; NEREU, JOAO C.; DO VAL, JOAO B. R.; IEEE. Stochastic Optimal Control of Systems for which Control Variation Increases Uncertainty: A Contribution to the Discrete Time Case. 2017 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), v. N/A, p. 6-pg., 2017-01-01. (16/13508-0, 16/08645-9)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

PEDROSA, Filipe de Carvalho. Modeling and control of discrete time CVIU systems. 2018. Master's Dissertation - Universidade Estadual de Campinas (UNICAMP). Faculdade de Engenharia Elétrica e de Computação Campinas, SP.