4,593 research outputs found
New advances in H∞ control and filtering for nonlinear systems
The main objective of this special issue is to
summarise recent advances in H∞ control and filtering
for nonlinear systems, including time-delay, hybrid and
stochastic systems. The published papers provide new
ideas and approaches, clearly indicating the advances
made in problem statements, methodologies or applications
with respect to the existing results. The special
issue also includes papers focusing on advanced and
non-traditional methods and presenting considerable
novelties in theoretical background or experimental
setup. Some papers present applications to newly
emerging fields, such as network-based control and
estimation
Value of Information in Feedback Control
In this article, we investigate the impact of information on networked
control systems, and illustrate how to quantify a fundamental property of
stochastic processes that can enrich our understanding about such systems. To
that end, we develop a theoretical framework for the joint design of an event
trigger and a controller in optimal event-triggered control. We cover two
distinct information patterns: perfect information and imperfect information.
In both cases, observations are available at the event trigger instantly, but
are transmitted to the controller sporadically with one-step delay. For each
information pattern, we characterize the optimal triggering policy and optimal
control policy such that the corresponding policy profile represents a Nash
equilibrium. Accordingly, we quantify the value of information
as the variation in the cost-to-go of the system given
an observation at time . Finally, we provide an algorithm for approximation
of the value of information, and synthesize a closed-form suboptimal triggering
policy with a performance guarantee that can readily be implemented
Maximum Entropy/Optimal Projection (MEOP) control design synthesis: Optimal quantification of the major design tradeoffs
The underlying philosophy and motivation of the optimal projection/maximum entropy (OP/ME) stochastic modeling and reduced control design methodology for high order systems with parameter uncertainties are discussed. The OP/ME design equations for reduced-order dynamic compensation including the effect of parameter uncertainties are reviewed. The application of the methodology to several Large Space Structures (LSS) problems of representative complexity is illustrated
Sampled-data synchronization control of dynamical networks with stochastic sampling
Copyright @ 2012 IEEEThis technical note is concerned with the sampled-data synchronization control problem for a class of dynamical networks. The sampling period considered here is assumed to be time-varying that switches between two different values in a random way with given probability. The addressed synchronization control problem is first formulated as an exponentially mean-square stabilization problem for a new class of dynamical networks that involve both the multiple probabilistic interval delays (MPIDs) and the sector-bounded nonlinearities (SBNs). Then, a novel Lyapunov functional is constructed to obtain sufficient conditions under which the dynamical network is exponentially mean-square stable. Both Gronwall's inequality and Jenson integral inequality are utilized to substantially simplify the derivation of the main results. Subsequently, a set of sampled-data synchronization controllers is designed in terms of the solution to certain matrix inequalities that can be solved effectively by using available software. Finally, a numerical simulation example is employed to show the effectiveness of the proposed sampled-data synchronization control scheme.This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant GR/S27658/01, the Royal Society of the UK, the National Natural Science Foundation of China under Grants 61028008, 60974030, 61134009 and 61104125, the National 973 Program of China under Grant 2009CB320600, and the Alexander von Humboldt Foundation
of Germany
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Non-fragile H∞ control with randomly occurring gain variations, distributed delays and channel fadings
This study is concerned with the non-fragile H∞ control problem for a class of discrete-time systems subject to randomly occurring gain variations (ROGVs), channel fadings and infinite-distributed delays. A new stochastic phenomenon (ROGVs), which is governed by a sequence of random variables with a certain probabilistic distribution, is put forward to better reflect the reality of the randomly occurring fluctuation of controller gains implemented in networked environments. A modified stochastic Rice fading model is then exploited to account for both channel fadings and random time-delays in a unified representation. The channel coefficients are a set of mutually independent random variables which abide by any (not necessarily Gaussian) probability density function on [0, 1]. Attention is focused on the analysis and design of a non-fragile H∞ outputfeedback controller such that the closed-loop control system is stochastically stable with a prescribed H∞ performance. Through intensive stochastic analysis, sufficient conditions are established for the desired stochastic stability and H∞ disturbance attenuation, and the addressed non-fragile control problem is then recast as a convex optimisation problem solvable via the semidefinite programme method. An example is finally provided to demonstrate the effectiveness of the proposed design method
A stochastic MPC scheme for distributed systems with multiplicative uncertainty
This paper presents a novel Distributed Stochastic Model Predictive Control
algorithm for networks of linear systems with multiplicative uncertainties and
local chance constraints on the states and control inputs. The chance
constraints are approximated via the Cantelli-Chebyshev inequality by means of
expected value and covariance. The algorithm is based on the distributed
Alternating Direction Method of Multipliers and yields in a distributedly
implementable, recursive feasible and mean square stable control scheme. The
aforementioned properties are guaranteed through a distributed invariant set
and distributed terminal constraints for the mean and covariance. The paper
closes with an illustrative numerical example for a system with three
interconnected subsystems, where the distributed design procedure is
benchmarked with a centralized approach.Comment: 10 pages, 2 figure
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