2,065 research outputs found
Diagnosis and Repair for Synthesis from Signal Temporal Logic Specifications
We address the problem of diagnosing and repairing specifications for hybrid
systems formalized in signal temporal logic (STL). Our focus is on the setting
of automatic synthesis of controllers in a model predictive control (MPC)
framework. We build on recent approaches that reduce the controller synthesis
problem to solving one or more mixed integer linear programs (MILPs), where
infeasibility of a MILP usually indicates unrealizability of the controller
synthesis problem. Given an infeasible STL synthesis problem, we present
algorithms that provide feedback on the reasons for unrealizability, and
suggestions for making it realizable. Our algorithms are sound and complete,
i.e., they provide a correct diagnosis, and always terminate with a non-trivial
specification that is feasible using the chosen synthesis method, when such a
solution exists. We demonstrate the effectiveness of our approach on the
synthesis of controllers for various cyber-physical systems, including an
autonomous driving application and an aircraft electric power system
A Finite-Time Cutting Plane Algorithm for Distributed Mixed Integer Linear Programming
Many problems of interest for cyber-physical network systems can be
formulated as Mixed Integer Linear Programs in which the constraints are
distributed among the agents. In this paper we propose a distributed algorithm
to solve this class of optimization problems in a peer-to-peer network with no
coordinator and with limited computation and communication capabilities. In the
proposed algorithm, at each communication round, agents solve locally a small
LP, generate suitable cutting planes, namely intersection cuts and cost-based
cuts, and communicate a fixed number of active constraints, i.e., a candidate
optimal basis. We prove that, if the cost is integer, the algorithm converges
to the lexicographically minimal optimal solution in a finite number of
communication rounds. Finally, through numerical computations, we analyze the
algorithm convergence as a function of the network size.Comment: 6 pages, 3 figure
Electric Vehicle Charging Station Placement: Formulation, Complexity, and Solutions
To enhance environmental sustainability, many countries will electrify their
transportation systems in their future smart city plans. So the number of
electric vehicles (EVs) running in a city will grow significantly. There are
many ways to re-charge EVs' batteries and charging stations will be considered
as the main source of energy. The locations of charging stations are critical;
they should not only be pervasive enough such that an EV anywhere can easily
access a charging station within its driving range, but also widely spread so
that EVs can cruise around the whole city upon being re-charged. Based on these
new perspectives, we formulate the Electric Vehicle Charging Station Placement
Problem (EVCSPP) in this paper. We prove that the problem is non-deterministic
polynomial-time hard. We also propose four solution methods to tackle EVCSPP
and evaluate their performance on various artificial and practical cases. As
verified by the simulation results, the methods have their own characteristics
and they are suitable for different situations depending on the requirements
for solution quality, algorithmic efficiency, problem size, nature of the
algorithm, and existence of system prerequisite.Comment: Submitted to IEEE Transactions on Smart Grid, revise
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