1,157 research outputs found
Probabilistic Plan Synthesis for Coupled Multi-Agent Systems
This paper presents a fully automated procedure for controller synthesis for
multi-agent systems under the presence of uncertainties. We model the motion of
each of the agents in the environment as a Markov Decision Process (MDP)
and we assign to each agent one individual high-level formula given in
Probabilistic Computational Tree Logic (PCTL). Each agent may need to
collaborate with other agents in order to achieve a task. The collaboration is
imposed by sharing actions between the agents. We aim to design local control
policies such that each agent satisfies its individual PCTL formula. The
proposed algorithm builds on clustering the agents, MDP products construction
and controller policies design. We show that our approach has better
computational complexity than the centralized case, which traditionally suffers
from very high computational demands.Comment: IFAC WC 2017, Toulouse, Franc
Prescribed Performance Control for Signal Temporal Logic Specifications
Motivated by the recent interest in formal methods-based control for dynamic
robots, we discuss the applicability of prescribed performance control to
nonlinear systems subject to signal temporal logic specifications. Prescribed
performance control imposes a desired transient behavior on the system
trajectories that is leveraged to satisfy atomic signal temporal logic
specifications. A hybrid control strategy is then used to satisfy a finite set
of these atomic specifications. Simulations of a multi-agent system, using
consensus dynamics, show that a wide range of specifications, i.e., formation,
sequencing, and dispersion, can be robustly satisfied.Comment: 9 pages - this an extended version of the 56th IEEE Conference on
Decision and Control (2017) versio
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