Asymptotes for frequency-response of distributed-parameter components.
Frequency response of distributed parameter three terminal RC network specified by set of asymptotes for amplitude and phase with low error
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Frequency response of distributed parameter three terminal RC network specified by set of asymptotes for amplitude and phase with low error
Filtering for linear distributed parameter systems
This paper presents a theory of nonlinear state observers for nonlinear and bilinear distributed parameter systems. Convergence results are proved for these observers. Linear feedback control derived from such state observers is applied to the distributed parameter system and conditions are presented for closed-loop stability. The emphasis is on finite dimensional state observers and controllers (which can be implemented with on-line computers) and conditions for their successful operation with infinite dimensional distributed parameter systems.
In this paper, maximum likelihood estimation for distributed parameter models of large flexible structures has been formulated. Distributed parameter models involve far fewer unknown parameters than independent modal characteristics of finite element models. The closed-form solutions for the partial differential equations with general forced inputs have been derived. The closed-form expressions of the sensitivity functions lead to highly efficient algorithms for analyzing ground or on-orbit test results. Numerical simulations with impulse and step inputs to the NASA Mini-MAST trust have been demonstrated. The estimations of modal properties involve its longitudinal elongation modes, lateral bending modes and torsional modes. The results show that distributed parameter models are promising in the parameter estimation of large flexible structures.
A new modal identification method for gyroscopic distributed-parameter systems is presented. The method represents an extension of previous work for the class of self-adjoint distributed-parameter systems. The modal identification method is formulated as a variational problem in which stationary values of a functional quotient are sought. The computation of the functional quotient is carried out using a set of admissible functions defined over the spatial domain of the system. As an illustration, the modal identification of a whirling shaft undergoing bending vibration is carried out and the effectiveness of the method is verified.
Finite dimensional approximation schemes that work well for distributed parameter systems are often not suitable for the analysis and implementation of feedback control systems. The relationship between approximation schemes for distributed parameter systems and their application to optimal control problems is discussed. A numerical example is given.
Concurrent surface water measurements made from a moving oceanographic research vessel were used to calibrate and interpret remotely sensed data collected over a plume in the New York Bight Apex on June 23, 1977. Multiple regression techniques were used to develop equations to subsequently map synoptic distributions of water quality parameters, chlorophyll A and total suspended matter, in the remotely sensed scene. Thermal (which did not have surface calibration values) and water quality parameter distributions indicated a cold mass of upwelled water in the Bight Apex with an overflowing nutrient-rich warm water plume that originated in the Sandy Hook Bay and flowed south near the New Jersey shoreline. Additional comparison of remotely sensed thermal and optical properties of the water with shipboard measurements indicated that remotely sensed data may be particularly useful for studying physical and biological processes in the top several meters of surface water at the plume boundaries.
Numerical techniques for parameter identification in distributed-parameter systems are developed analytically. A general convergence and stability framework (for continuous dependence on observations) is derived for first-order systems on the basis of (1) a weak formulation in terms of sesquilinear forms and (2) the resolvent convergence form of the Trotter-Kato approximation. The extension of this framework to second-order systems is considered.
Linear distributed parameter system identification by stochastic approximation, obtaining constant parameters sequentially
Optimal control of distributed-parameter systems of hyperbolic and parabolic type
The use of FEMs of spacecraft structural dynamics is a common practice, but it has a number of shortcomings. Distributed-parameter models offer an alternative, but present both advantages and difficulties. First, the model order does not have to be reduced prior to the inclusion of control system dynamics. This advantage eliminates the risk involved with model 'order reduction'. Second, distributed parameter models inherently involve fewer parameters, thereby enabling more accurate parameter estimation using experimental data. Third, it is possible to include the damping in the basic model, thereby increasing the accuracy of the structural damping. The difficulty in generating distributed parameter models of complex spacecraft configurations has been greatly alleviated by the use of PDEMOD, BUNVIS-RG, or DISTEL. PDEMOD is being developed for simultaneously modeling structural dynamics and control system dynamics.
Optimal design of RC lines distributed parameter systems using gradient technique and variational calculus
Optimal synthesis and design of distributed parameter system for waveguides using gradient technique with devised algorithm to overcome convergence problem
Nonlinear filtering for linear parabolic distributed parameter systems with white noise, considering stochastic boundary value problem
Frequency response and design of distributed parameter networks using asymptotic approximation
A distributed-parameter model of the NASA Solar Array Flight Experiment spacecraft structure is constructed on the basis of measurement data and analyzed to generate a priori estimates of modal frequencies and mode shapes. A Newton-Raphson maximum-likelihood algorithm is applied to determine the unknown parameters, using a truncated model for the estimation and the full model for the computation of the higher modes. Numerical results are presented in a series of graphs and briefly discussed, and the significant improvement in computation speed obtained by parallel implementation of the method on a supercomputer is noted.
Systems described by partial differential equations have an infinite-dimensional state space. Feedback control of such distributed parameter systems must be accomplished by finite-dimensional controllers to be implemented by on-line digital computers. A further practical constraint is that the controller must operate in discrete (rather than continuous) time. This paper investigates the stability of such distributed parameter feedback controllers in closed-loop with the actual system.
A Chandrasekhar-type factorization method is applied to the linear-quadratic optimal control problem for distributed parameter systems. An aeroelastic control problem is used as a model example to demonstrate that if computationally efficient algorithms, such as those of Chandrasekhar-type, are combined with the special structure often available to a particular problem, then an abstract approximation theory developed for distributed parameter control theory becomes a viable method of solution. A numerical scheme based on averaging approximations is applied to hereditary control problems. Numerical examples are given.