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CDC
2008
IEEE
112views Control Systems» more  CDC 2008»
14 years 2 months ago
Application of the proximal center decomposition method to distributed model predictive control
Abstract— In this paper we present a dual-based decomposition method, called here the proximal center method, to solve distributed model predictive control (MPC) problems for cou...
Ion Necoara, Dang Doan, Johan A. K. Suykens
ISLPED
1999
ACM
91views Hardware» more  ISLPED 1999»
14 years 4 days ago
Stochastic modeling of a power-managed system: construction and optimization
-- The goal of a dynamic power management policy is to reduce the power consumption of an electronic system by putting system components into different states, each representing ce...
Qinru Qiu, Qing Wu, Massoud Pedram
CDC
2010
IEEE
186views Control Systems» more  CDC 2010»
13 years 2 months ago
Approximation and limiting behavior of random models
In this paper, we investigate limiting behavior of linear dynamic systems driven by random stochastic matrices. We introduce and study the new concepts of partial ergodicity and 1-...
Behrouz Touri, Angelia Nedic
ATAL
2008
Springer
13 years 9 months ago
Dynamics based control with PSRs
We present an extension of the Dynamics Based Control (DBC) paradigm to environment models based on Predictive State Representations (PSRs). We show an approximate greedy version ...
Ariel Adam, Zinovi Rabinovich, Jeffrey S. Rosensch...
IJON
2002
154views more  IJON 2002»
13 years 7 months ago
Nonlinear model predictive control of a cutting process
Nonlinear model predictive control (MPC) of a simulated chaotic cutting process is presented. The nonlinear MPC combines a neural-network model and a genetic-algorithm-based optim...
Primoz Potocnik, Igor Grabec