Cooperative Planning Control and Formation Control of Multi-Agent Systems

Cooperative planning control is an active topic of research, with many practical applications including multi-robot systems, transportation, multi-point surveillance and biological systems. The contributions of this thesis lie in the scope of three topics: formation control, time-constrained cooperative planning control and probabilistic control synthesis, all of the them in the framework of multi-agent systems. In the first part of the thesis, given a team of rigid-bodies, we propose decentral-ized control protocols such that desired position and orientation-based formationbetween neighboring agents is achieved. Inter-agent collisions and collisions betweenagents and static obstacles of the workspace are guaranteed to be avoided by theproposed control scheme. Furthermore, the connectivity between the agents thatare initially connected is preserved. In the second part of the thesis, we considera team of agents, modeled by coupled single-integrator dynamics. Each agent isassigned with individual high-level tasks, given in Metric Interval Temporal Logic(MITL). By abstracting the motion of each agent into Transition Systems (TS), wepropose decentralized control methodologies that guarantee the satisfaction of thedesired tasks of each agent. In the final part, a coupled multi-agent system underthe presence of uncertainties and model errors is considered. Each agent is modeledby a Markov Decision Process (MDP) and is assigned with a high-level task givenin Probabilistic Computational Tree Logic (PCTL). The goal is to design controlpolicies such that each agent is performing a desired task. By clustering the agentsinto dependency clusters, we propose control algorithms that guarantee that thedesired specifications are fulfilled. Numerical simulations conducted in MATLABverify the claimed results.QC 20170512