Fault-tolerant Predictive Control with trajectory planning in the presence of obstacles

• Grant number: 11/18632-8
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: March 01, 2012
• End date: January 31, 2014
• Field of knowledge: Engineering - Electrical Engineering - Industrial Electronics, Electronic Systems and Controls
• Principal Investigator: Roberto Kawakami Harrop Galvão
• Grantee: Rubens Junqueira Magalhães Afonso
• Host Institution: Divisão de Engenharia Eletrônica (IEE). Instituto Tecnológico de Aeronáutica (ITA). Ministério da Defesa (Brasil). São José dos Campos , SP, Brazil
• Associated research grant: 11/17610-0 - Monitoring and control of dynamic systems subject to faults, AP.TEM

Abstract

Predictive Control techniques have been increasingly widespread in industry, mainly due to their ability to handle constraints on inputs and states of the plant. Approaches equipped with terminal constraint invariant sets are frequently used to achieve stability of the control loop. However, in vehicle guiding missions, the terminal set can be imposed by mission requirements and not necessarily invariant. Another difficulty is the occurrence of faults that limit the authority of the actuators, compromising the ability to achieve the specified terminal set within the horizon, thus requiring the use of larger horizons. Moreover, the presence of obstacles makes the optimization problem in general non-convex. These factors contribute to increase the computational load associated with the solution of the optimization problem that generates the control signal. Therefore, the time required for solution can be prohibitive in front of the sampling period. In this context, it is convenient to have a trajectory planner capable of dividing the task into parts, allowing the use of smaller horizons. In this work, path planning techniques in the presence of obstacles and dynamic constraints will be studied, which define waypoints, i. e., intermediate points, to be used by the predictive control loop. The results will be analyzed in terms of demanded computational resources, as well as the ability to meet mission requirements even in the presence of actuator faults.

Scientific publications

(4)

(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)

AFONSO, RUBENS J. M.; GALVAO, ROBERTO K. H.; KIENITZ, KARL H.. Reduction in the number of binary variables for inter-sample avoidance in trajectory optimizers using mixed-integer linear programming. INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, v. 26, n. 16, p. 3662-3669, NOV 10 2016. (11/17610-0, 11/18632-8)

MAGALHAES AFONSO, RUBENS JUNQUEIRA; HARROP GALVAO, ROBERTO KAWAKAMI; KIENITZ, KARL HEINZ; ALYAMI, HASHEM; BECERRA, VICTOR M.; HADJILOUCAS, SILLAS. Constrained pre-equalization accounting for multi-path fading emulated using large RC networks: applications to wireless and photonics communications. OPTICAL AND QUANTUM ELECTRONICS, v. 48, n. 7, JUL 2016. (11/13777-8, 11/17610-0, 11/18632-8)

MAGALHAES AFONSO, RUBENS JUNQUEIRA; HARROP GALVAO, ROBERTO KAWAKAMI; KIENITZ, KARL HEINZ. Sense Avoidance Constraints for Conflict Resolution between Autonomous Vehicles. IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE, v. 9, n. 1, p. 110-122, SPR 2017. (11/17610-0, 11/18632-8)

HARROP GALVAO, ROBERTO KAWAKAMI; HADJILOUCAS, SILLAS; KIENITZ, KARL HEINZ; PAIVA, HENRIQUE MOHALLEM; MAGALHAES AFONSO, RUBENS JUNQUEIRA. Fractional Order Modeling of Large Three-Dimensional RC Networks. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, v. 60, n. 3, p. 624-637, MAR 2013. (11/13777-8, 11/17610-0, 11/18632-8)