Cooperative Control Reconfiguration in Networked Multi-Agent Systems

Development of a network of autonomous cooperating vehicles has attracted significant attention during the past few years due to its broad range of applications in areas such as autonomous underwater vehicles for exploring deep sea oceans, satellite formations for space missions, and mobile robots in industrial sites where human involvement is impossible or restricted, to name a few. Motivated by the stringent specifications and requirements for depth, speed, position or attitude of the team and the possibility of having unexpected actuators and sensors faults in missions for these vehicles have led to the proposed research in this thesis on cooperative fault-tolerant control design of autonomous networked vehicles. First, a multi-agent system under a fixed and undirected network topology and subject to actuator faults is studied. A reconfigurable control law is proposed and the so-called distributed Hamilton-Jacobi-Bellman equations for the faulty agents are derived. Then, the reconfigured controller gains are designed by solving these equations subject to the faulty agent dynamics as well as the network structural constraints to ensure that the agents can reach a consensus even in presence of a fault while simultaneously the team performance index is minimized. Next, a multi-agent network subject to simultaneous as well as subsequent actuator faults and under directed fixed topology and subject to bounded energy disturbances is considered. An H∞ performance fault recovery control strategy is proposed that guarantees: the state consensus errors remain bounded, the output of the faulty system behaves exactly the same as that of the healthy system, and the specified H∞ performance bound is guaranteed to be minimized. Towards this end, the reconfigured control law gains are selected first by employing a geometric control approach where a set of controllers guarantees that the output of the faulty agent imitates that of the healthy agent and the consensus achievement objectives are satisfied. Then, the remaining degrees of freedom in the selection of the control law gains are used to minimize the bound on a specified H∞ performance index. Then, control reconfiguration problem in a team subject to directed switching topology networks as well as actuator faults and their severity estimation uncertainties is considered. The consensus achievement of the faulty network is transformed into two stability problems, in which one can be solved offline while the other should be solved online and by utilizing information that each agent has received from the fault detection and identification module. Using quadratic and convex hull Lyapunov functions the control gains are designed and selected such that the team consensus achievement is guaranteed while the upper bound of the team cost performance index is minimized. Finally, a team of non-identical agents subject to actuator faults is considered. A distributed output feedback control strategy is proposed which guarantees that agents outputs’ follow the outputs of the exo-system and the agents states remains stable even when agents are subject to different actuator faults

Suboptimal control reconfiguration in switched multi-agent networked systems

In this work, the control recovery problem in a directed network of switched multi-agent systems is studied. A distributed cooperative control strategy is proposed which ensures that the agents reach a consensus while the upper bound of the team performance index is minimized even when the agents are subject to actuator faults where fault severity estimation uncertainties are presented. Using quadratic Lyapunov functions, a reconfiguration strategy is provided to design the gains of the proposed distributed reconfigurable control laws such that the team objectives are guaranteed. Our proposed reconfigurable control laws are applied to a team of seven autonomous underwater vehicles under directed switching topology and subject to simultaneous actuator faults. Simulation results demonstrate the effectiveness of the proposed reconfiguration control laws in compensating for the effects of sudden actuator faults and uncertainties. 2016 American Automatic Control Council (AACC).Scopu

A Distributed Control Reconfiguration and Accommodation for Consensus Achievement of Multiagent Systems Subject to Actuator Faults

This paper tackles the development of distributed control reconfiguration and fault accommodation strategies for consensus achievement in multiagent systems in the presence of faulty agents whose actuators are unable to produce their nominal control efforts. A faulty agent can adversely affect and prevent the team from reaching agreement and lead to catastrophic mission performance degradations. To ensure that the faulty team pursues its consensus objectives, in this paper, on-line distributed control reconfiguration strategies are developed that employ only nearest neighbor information to guarantee the team consensus while minimizing a local cost performance index. Toward the above end, the distributed Hamilton-Jacobi-Bellman equations for the faulty agent are derived and novel reconfigured controllers are designed by solving the above equations subject to the faulty agent dynamics and network structure constraints to ensure fault accommodation of the entire team. Our proposed reconfigurable controllers are applied to a network of autonomous underwater vehicles subject to actuator faults to demonstrate and illustrate the effectiveness and capabilities of our proposed fault recovery control strategies.This work was supported by the Qatar National Research Fund (a member of Qatar Foundation) through the National Priorities Research Program under Grant 5-045-2-017.Scopu

An H∞ cooperative fault recovery control of multi-agent systems

In this work, an H∞ performance fault recovery control problem for a team of multi-agent systems that is subject to actuator faults is studied. Our main objective is to design a distributed control reconfiguration strategy such that in presence of actuator faults, (a) the state consensus errors remain bounded, (b) the outputs of the faulty team behave exactly the same as that of the healthy team, and (c) the specified H∞ performance bound is guaranteed to be minimized in presence of bounded energy disturbances. The reconfigured control law gains are selected first by employing a geometric approach where a set of controllers guarantees that the output of the faulty agent imitates that of the healthy agent and that the consensus achievement objectives are satisfied. Next, the remaining degrees of freedom in selection of the control law gains are utilized to minimize the bound on a specified H∞ performance index. Finally, the effects of uncertainties and imperfections in the FDI module decision in estimating the fault severity are investigated and a bound on the maximum tolerable estimation uncertainties is obtained. Keywords: Multi-agent systems; Actuator faults; Cooperative fault recovery; Consensus achievement; Disturbance attenuationScopu

Control reconfiguration for multiple autonomous vehicles subject to actuator faults and disturbances

In this paper, control reconfiguration problem in a team of multi-agent systems subject to actuator faults and environmental disturbances is studied. The proposed distributed control strategy has the capability of being reconfigured by using local information when a fault is detected and identified. It ensures that in absence of disturbances the faulty agent errors remain bounded while its output behaves exactly the same as that of the healthy system. Moreover, the specified H? performance bound is guaranteed to be minimized in presence of bounded energy disturbances. Towards this end, first by employing a geometric approach a set of control gains are obtained that enforce the output of the faulty agent imitates that of the healthy agent while the consensus achievement objectives are satisfied. Next, the remaining degrees of freedom in the selection of the control law gains are used to minimize the bound on a specified H? performance index. Our proposed distributed and cooperative control recovery approach is applied to a team of autonomous underwater vehicles to demonstrate its effectiveness in accomplishing the overall team requirements. 2016 American Automatic Control Council (AACC).Scopu