1,418 research outputs found
A Structured Systems Approach for Optimal Actuator-Sensor Placement in Linear Time-Invariant Systems
In this paper we address the actuator/sensor allocation problem for linear
time invariant (LTI) systems. Given the structure of an autonomous linear
dynamical system, the goal is to design the structure of the input matrix
(commonly denoted by ) such that the system is structurally controllable
with the restriction that each input be dedicated, i.e., it can only control
directly a single state variable. We provide a methodology that addresses this
design question: specifically, we determine the minimum number of dedicated
inputs required to ensure such structural controllability, and characterize,
and characterizes all (when not unique) possible configurations of the
\emph{minimal} input matrix . Furthermore, we show that the proposed
solution methodology incurs \emph{polynomial complexity} in the number of state
variables. By duality, the solution methodology may be readily extended to the
structural design of the corresponding minimal output matrix (commonly denoted
by ) that ensures structural observability.Comment: 8 pages, submitted for publicatio
A linear programming based heuristic framework for min-max regret combinatorial optimization problems with interval costs
This work deals with a class of problems under interval data uncertainty,
namely interval robust-hard problems, composed of interval data min-max regret
generalizations of classical NP-hard combinatorial problems modeled as 0-1
integer linear programming problems. These problems are more challenging than
other interval data min-max regret problems, as solely computing the cost of
any feasible solution requires solving an instance of an NP-hard problem. The
state-of-the-art exact algorithms in the literature are based on the generation
of a possibly exponential number of cuts. As each cut separation involves the
resolution of an NP-hard classical optimization problem, the size of the
instances that can be solved efficiently is relatively small. To smooth this
issue, we present a modeling technique for interval robust-hard problems in the
context of a heuristic framework. The heuristic obtains feasible solutions by
exploring dual information of a linearly relaxed model associated with the
classical optimization problem counterpart. Computational experiments for
interval data min-max regret versions of the restricted shortest path problem
and the set covering problem show that our heuristic is able to find optimal or
near-optimal solutions and also improves the primal bounds obtained by a
state-of-the-art exact algorithm and a 2-approximation procedure for interval
data min-max regret problems
A reactive control strategy for networked hydrographical system management
A reactive control strategy is proposed to improve the water asset management of complex hydrographical systems. This strategy requires the definition of rules to achieve a generic resource allocation and setpoint assignment. A modelling method of the complex hydro- graphical network based on a weighted digraph of instrumented points, is also presented. The simulation results of the strategy applied to a hydrographical system composed of one confluent and two difluents show its efficiency and its effectiveness
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