... 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...

... examples show that the proposed results are effective and much less conservative than some existing results. 25 06 2009 06 04 2010 09 03 2011 09 03 2011 delays linear matrix inequalities linear systems Markov processes stability Markov jump linear systems parameter...

... close-loop properties. In this paper, we extended the definition of finite-time stabilization to a class of MJSs subject to time-varying norm bounded parameter uncertainties and external disturbances. The stochastic character in the system is described by a Markov process but with only partially...

... ∞ performance ( 5 6 7 8 ), robustness ( 9 10 11 12 13 ), etc. As a significant factor, transition probabilities in the Markov process determine the system evolution and many researches on MJLS are based on the assumption of complete access of it. A recent tendency is to consider MJLS with uncertain...

... ] ,     Q = [ 0.5 0 0 0.2 ] The Markov process s t belongs to the space S = { 1 , 2 } with generator Π = [ λ i j ] 2 × 2 given as λ 11 = − 3 , λ 12 = 3 , λ 21 = 4...

... 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...

... } 18 03 2008 04 02 2009 20 05 2009 control system analysis decision making Markov processes optimal control predictive control state estimation New technologies in mechatronics and actuators have induced significant enhancement in the complexity of modern engineering...

... are modeled as three uncoupled, first-order Gauss–Markov processes 10 F ̇ Z , net = w Z , M ̇ X = w X , M ̇ Y = w Y where F Z , net = F Z − F Z , eq is the net axial gas film force and the terms w Z , w X...

... 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 Set ξ 0 = 0 . Using Eqs. 23 , 19 , we have 31...

... feedback. 3 The communication network is sufficiently modeled by a two state Markov process. This system fits into a two-state switched dynamic system framework whose state depends on the success of the last round-trip transmissions. If no transmissions are lost, the loop will be successfully...

... , J. D. , and Moss , T. R. , 2002 , Reliability and Risk Assessment , 2nd ed. , ASME , New York. 31 05 2006 29 06 2007 29 02 2008 aerospace industry aircraft maintenance failure analysis Markov processes Monte Carlo methods time-limited dispatch TLD...

... 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...

... fuzzy set theory Markov processes linear matrix inequalities nonlinear control systems robust control uncertain systems fuzzy system models Lyapunov function stabilizing controller Markovian jumps Many physical systems may experience abrupt changes in their structure and parameters...

... order systems Markov processes matrix algebra In many engineering problems, it is often desirable to approximate a high-order system by a low-order model since it facilitates simulation and implementation of the system. In the last three decades, considerable efforts have been made in the area...

... 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 Delay LMI Jump linear system (JLS) is very popular to characterize a class...

... expression for the minimum cost of the closed-loop system. linear quadratic Gaussian control control system synthesis Markov processes stochastic systems minimisation LQG Control Markov Parameters Digital Control Output Variance Constraint Control Finite Horizon Optimal Control...