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Model Transformation (model + transformation)
Selected AbstractsConsensus problem of high-order multi-agent systems with external disturbances: An H, analysis approachINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 14 2010Yang Liu Abstract This paper is devoted to the output consensus problem of directed networks of multiple high-order agents with external disturbances, and proposes a distributed protocol using the neighbors' measured outputs. By defining an appropriate controlled output and conducting a model transformation in two steps, consensus performance analysis of the multi-agent system under the proposed protocol is transformed into a normal H, problem. Then using H, theory of linear systems, conditions are derived to ensure the consensus performance with a prescribed H, index for networks with fixed and switching topologies, respectively. A numerical example of the formation control application is included to validate the theoretical results. Copyright © 2009 John Wiley & Sons, Ltd. [source] Robust absolute stability criteria for uncertain Lur'e systems of neutral typeINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 3 2008Qing-Long Han Abstract This paper is concerned with robust absolute stability of uncertain Lur'e systems of neutral type. Some delay-dependent stability criteria are obtained and formulated in the form of linear matrix inequalities. The criteria cover some existing results as their special cases. Neither model transformation nor bounding technique for cross terms is involved through derivation of the stability criteria. Numerical examples show the effectiveness of the criteria. Copyright © 2007 John Wiley & Sons, Ltd. [source] Approximation and complexity trade-off by TP model transformation in controller design: A case study of the TORA system,ASIAN JOURNAL OF CONTROL, Issue 5 2010Zoltán Petres Abstract The main objective of the paper is to study the approximation and complexity trade-off capabilities of the recently proposed tensor product distributed compensation (TPDC) based control design framework. The TPDC is the combination of the TP model transformation and the parallel distributed compensation (PDC) framework. The Tensor Product (TP) model transformation includes an Higher Order Singular Value Decomposition (HOSVD)-based technique to solve the approximation and complexity trade-off. In this paper we generate TP models with different complexity and approximation properties, and then we derive controllers for them. We analyze how the trade-off effects the model behavior and control performance. All these properties are studied via the state feedback controller design of the Translational Oscillations with an Eccentric Rotational Proof Mass Actuator (TORA) System. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society [source] Computational relaxed TP model transformation: restricting the computation to subspaces of the dynamic model,ASIAN JOURNAL OF CONTROL, Issue 5 2009Szabolcs Nagy Abstract The tensor-product (TP) model transformation is a recently proposed numerical method capable of transforming linear parameter varying state-space models to the higher order singular value decomposition (HOSVD) based canonical form of polytopic models. It is also capable of generating various types of convex TP models, a type of polytop models, for linear matrix inequality based controller design. The crucial point of the TP model transformation is that its computational load exponentially explodes with the dimensionality of the parameter vector of the parameter-varying state-space model. In this paper we propose a modified TP model transformation that leads to considerable reduction of the computation. The key idea of the method is that instead of transforming the whole system matrix at once in the whole parameter space, we decompose the problem and perform the transformation element wise and restrict the computation to the subspace where the given element of the model varies. The modified TP model transformation can readily be executed in higher dimensional cases when the original TP model transformation fails. The effectiveness of the new method is illustrated with numerical examples. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society [source] APPROXIMATION PROPERTIES OF TP MODEL FORMS AND ITS CONSEQUENCES TO TPDC DESIGN FRAMEWORKASIAN JOURNAL OF CONTROL, Issue 3 2007Domonkos Tikk ABSTRACT Tensor Product Distributed Compensation (TPDC) is a recently established controller design framework, that links TP model transformation and Parallel Distributed Compensation (PDC) framework. TP model transformation converts different models to a common representational form: the TP model form. The primary aim of this paper is to investigate the approximation capabilities of TP model forms, because the universal applicability of TPDC framework strongly relies on it. We point out that the set of functions that can be approximated arbitrarily well by TP forms with bounded number of components lies no-where dense in the set of continuous functions. Consequently, in a class of control problems this property necessitates the usage of tradeoff techniques between the accuracy and the complexity of the TP form, which is easily feasible within the TPDC framework unlike in analytic models. [source] STOCHASTIC STABILIZATION AND H, CONTROL FOR DISCRETE JUMPING SYSTEMS WITH TIME DELAYSASIAN JOURNAL OF CONTROL, Issue 3 2005Jing Wu ABSTRACT In this paper, robust stochastic stabilization and H, control for a class of uncertain discrete-time linear systems with Markovian jumping parameters are considered. Based on a new bounded real lemma derived upon an inequality recently proposed, a new iterative state-feedback controller design procedure for discrete time-delay systems is presented. Sufficient conditions for stochastic stabilization are derived in the form of linear matrix inequalities (LMIs) based on an equivalent model transformation, and the corresponding H, control law is given. Finally, numerical examples are given to illustrate the solvability of the problems and effectiveness of the results. [source] IMPROVED CONDITIONS FOR DELAY-DEPENDENT ROBUST STABILITY AND STABILIZATION OF UNCERTAIN DISCRETE TIME-DELAY SYSTEMSASIAN JOURNAL OF CONTROL, Issue 3 2005Shengyuan Xu ABSTRACT This paper provides improved delay-dependent conditions for the robust stability and robust stabilization of discrete time-delay systems with norm-bounded parameter uncertainties. It is theoretically established that the proposed conditions are less conservative than those discussed in the literature. The new approach proposed in this paper in a derivation of delay-dependent conditions and involves the use of neither model transformation nor bounding techniques for some cross terms. A numerical example is provided to demonstrate the reduced conservatism of the proposed conditions. [source] | ||||||||||