... stable are derived. Finally, two numerical examples are provided to illustrate the effectiveness of the proposed conditions. 29 01 2011 18 09 2011 05 12 2011 05 12 2011 linear matrix inequalities Markov processes nonlinear systems stability stochastic systems...

... to verify the effectiveness of the proposed method. 25 08 2008 12 11 2010 25 03 2011 25 03 2011 closed loop systems delay systems hydraulic control equipment hydraulic systems linear systems Markov processes networked control systems position control predictive control...

..., finite-state Markov process with right continuous trajectories and taking values in a finite set S ≜ { 1 , 2 , … , s } with generator Π = ( π i j ) . The transition probability from mode i at time t to mode j at time t + Δ t , i...

... matrix inequalities framework. A numerical example is used to illustrate the effectiveness of the developed theoretic results. 13 03 2009 14 04 2010 29 11 2010 29 11 2010 control system synthesis linear matrix inequalities Markov processes probability stability state...

... systems Markov processes observers predictive control As a class of stochastic hybrid systems, Markovian jump linear systems (MJLSs) have received much attention in recent years. By the stochastic switching feature, MJLS can be modeled as hybrid systems with continuous and discrete dynamics...

... on output feedback is much more challenging and merits further study. 01 08 2009 28 02 2010 16 08 2010 16 08 2010 asymptotic stability control system synthesis differential equations fuzzy control Markov processes robust control stochastic systems robust...

... distributed, binary-state Markov processes with state transition probabilities designated by a central controller. Second, steady-state behavior, convergence rate, and variance of the aggregate output, i.e., the total number of recruited agents, are analyzed, and design trade-offs in terms of accuracy...

...Shuping He; Fei Liu The stochastic finite-time stabilization problem is considered for a class of linear uncertain Markov jump systems that possess randomly jumping parameters. The transition of the jumping parameters is governed by a finite-state Markov process. By using the appropriate stochastic...

... cart-pole balancing problem and a vehicle cruise-control problem. 18 03 2008 04 02 2009 20 05 2009 decision making Markov processes optimal control real-time systems state-space methods stochastic processes uncertain systems Deriving a control policy for dynamic...

.... This paper provides the conditions that the POD can be valid, and be an interpretation of its underlying structure. 18 03 2008 04 02 2009 20 05 2009 control system analysis decision making Markov processes optimal control predictive control state estimation New...

... 03 2008 29 07 2008 Gaussian processes Kalman filters Markov processes reduced order systems seals (stoppers) stators mechanical gas face seal state estimation POD reduced-order Kalman filter Noncontacting mechanical gas face seals are often used in high speed, high...

... fault tolerance fuzzy control linear matrix inequalities Markov processes nonlinear control systems stability tracking fault tolerant control fuzzy control linear matrix inequality nonlinear systems stochastic stability tracking In the past two decades, significant research...

... Markov processes radio networks servomechanisms telecommunication channels telecommunication networks Wireless networks as a control medium have garnered significant research attention for their potential to enable applications demanding either high levels of controller and plant mobility...

... dispatch TLD Monte Carlo simulation dispatch category specification aerospace industry aircraft maintenance failure analysis Markov processes Monte Carlo methods 31 05 2006 29 06 2007 29 02 2008 2008 American Society of Mechanical Engineers ...

... on the Markov chain modeling and stochastic dynamic programming (SDP). The driver demand is modeled as a Markov process to represent the future uncertainty under diverse driving conditions. The infinite-horizon SDP solution generates a stationary state-feedback control policy to achieve optimal power management...

...-time discrete-state Markov process taking values in a finite set Ω = { 1 , 2 , … , s } with transition probability matrix P ≜ { p ı ȷ } given by 2.2 p ı ȷ = Pr [ η ( t + Δ ) = ȷ ∣ η ( t ) = ı ] = { λ ı ȷ Δ + O...

... a ̃ k + i − 1 . Hence the original k th-order IRG G u , k is approximately preserved in the reduced model. 09 10 2003 22 05 2005 transient response continuous time systems iterative methods reduced order systems Markov processes matrix algebra...

... revision, Dec. 2002. Associate Editor. N. Olgac. 01 Aug 2001 01 Dec 2002 04 06 2003 robust control optimal control discrete time systems linear systems delays linear matrix inequalities uncertain systems Markov processes Jump Linear System Polytopic Uncertainty Time...

... linear quadratic Gaussian control control system synthesis Markov processes stochastic systems minimisation 06 October 1998 Contributed by the Dynamic Systems and Control Division for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL . Manuscript received...