This paper proposes an optimal way of allocating collocated input-output pairs for stabilizing distributed parameter systems. We first introduce a finite-dimensional reduced model from sampled initial responses of the...
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This paper proposes an optimal way of allocating collocated input-output pairs for stabilizing distributed parameter systems. We first introduce a finite-dimensional reduced model from sampled initial responses of the systems via the POD (Proper Orthogonal Decomposition)Galerkin method. Next, optimal gains of the stabilizing controller for the reduced systems are designed by the stable manifold method that is an exact numerical solver of Hamilton-Jacobi equations. Filially, we present three allocation methods derived front. state shape matching, dissipation enhancement, and their mixed evaluation, and we show that the optimal allocations car be associated with energy controls in terms of port representations. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
This paper presents a P-type iterative learning control（ILC） scheme for a class of fractional order distributedparameter switched systems. First, by analyzing of the control and learning processes, a discrete syste...
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This paper presents a P-type iterative learning control（ILC） scheme for a class of fractional order distributedparameter switched systems. First, by analyzing of the control and learning processes, a discrete system for P-type ILC is established and the ILC design problem is then converted to a stabilization problem for such a discrete system. Next, a sufficient condition for the convergence of the tracking errors is obtained, which is less conservative than the existing one. Finally, the validity of the proposed method is verified by a numerical example.
NASA Technical Reports Server (Ntrs) 19810020922: the Reduced Order Model Problem in distributed parameter systems Adaptive Identification and Control. [large Space Structures by NASA Technical Reports Server (Ntrs); ...
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NASA Technical Reports Server (Ntrs) 19810020922: the Reduced Order Model Problem in distributed parameter systems Adaptive Identification and Control. [large Space Structures by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 19860009522: Factorization and Reduction Methods for Optimal Control of distributed parameter systems by NASA Technical Reports Server (Ntrs); NASA Technical Reports Server (Ntrs);...
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NASA Technical Reports Server (Ntrs) 19860009522: Factorization and Reduction Methods for Optimal Control of distributed parameter systems by NASA Technical Reports Server (Ntrs); NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 19870008396: Model Reference Control of distributed parameter systems: Application to the Scole Problem by NASA Technical Reports Server (Ntrs); NASA Technical Reports Server (Ntrs...
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NASA Technical Reports Server (Ntrs) 19870008396: Model Reference Control of distributed parameter systems: Application to the Scole Problem by NASA Technical Reports Server (Ntrs); NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 20060053356: Model Predictive Optimal Control of a Time-Delay distributed-parametersystems by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 20060053356: Model Predictive Optimal Control of a Time-Delay distributed-parametersystems by NASA Technical Reports Server (Ntrs); published by
This paper treats the control problem of a class of monodimensional (1D) hyperbolic differential models with nonlinear components by using the boundary controller, the state measuring, and the control action on the bo...
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This paper treats the control problem of a class of monodimensional (1D) hyperbolic differential models with nonlinear components by using the boundary controller, the state measuring, and the control action on the boundary of the system. This controller is easy to implement from point of view of measuring techniques and actuation. The proposed algorithm provides the exponential convergence to the desired reference trajectory and rejects the effect of the nonlinear components by using the constraints in state space. A maximum principle of this class of system is inferred in order to evaluate the effect of boundary control. A constructive Lyapunov-based proof of convergence of the control algorithm is carried out. Numerical simulations of a technical model are presented.
A fault detection and isolation scheme is addressed for a class of linear distributed parameter systems (DPS) described by partial differential equations (PDE). In contrast to using ordinary differential equations (OD...
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ISBN:
(纸本)9781467386838
A fault detection and isolation scheme is addressed for a class of linear distributed parameter systems (DPS) described by partial differential equations (PDE). In contrast to using ordinary differential equations (ODE) for describing DPS, in this paper, a filter based observer based on the linear PDE representation is proposed with an output measurement. A fault is declared active when the magnitude of the detection residual exceeds a predefined threshold. Upon detection, an actuator and a sensor fault isolation estimators are activated to identify the fault type when their isolation residual is below a predefined threshold and the other is above the threshold. When both actuator and sensor fault isolation estimator residuals are above their isolation thresholds, a state fault is considered to have occurred. Upon isolation, the magnitude of the fault parameter is identified. Finally, the performance of the fault detection and isolation scheme is demonstrated on a heat reactor system which is represented by linear parabolic PDEs.
Control and estimation of second-order distributed parameter systems are of importance in mechanical systems. In particular, flexible structures can be modeled as second-order distributed parameter systems. This paper...
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Control and estimation of second-order distributed parameter systems are of importance in mechanical systems. In particular, flexible structures can be modeled as second-order distributed parameter systems. This paper investigates adaptive consensus filtering for a class of second-order distributed parameter systems under an abstract framework. We propose an adaptive consensus mechanism to minimize the disagreement among all local filters consisting of different sensor nodes and written in the natural setting of a second-order formulation with an additional coupling. A parameter-dependent Lyapunov function is presented to analyze the stability of the collective dynamics, that is, all filters agree with each other and converge to the true state of the second-order system. The performance is demonstrated on a numerical example of a second-order partial differential equation with point measurements.
This work is concerned with the design and effects of the synchronization gains on the synchronization problem for a class of networked distributed parameter systems. The networked systems, assumed to be described by ...
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This work is concerned with the design and effects of the synchronization gains on the synchronization problem for a class of networked distributed parameter systems. The networked systems, assumed to be described by the same evolution equation in a Hilbert space, differ in their initial conditions. To address the synchronization problem, a coupling term containing the pairwise state differences of all the networked systems weighted by the synchronization gains is included in the controller of each networked system. By considering the aggregate closed-loop systems, an optimization scheme for the synchronization gains is proposed by minimizing an appropriate measure of synchronization. The integrated control and synchronization design is subsequently cast as an optimal control problem, the solution of which is found via the solution of parameterized operator Lyapunov equations. An alternative to the optimization of the synchronization gains is also proposed in which the adaptation of synchronization gains is derived from Lyapunov redesign methods. Both choices of the proposed synchronization controllers aim at achieving both the control and the synchronization objectives. An extensive numerical study examines the various aspects of the optimization and adaptation of the gains on the control and synchronization of networked 1D parabolic differential equations.
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