The focus of this paper is on the development of models for use in the design of active surge control/rotating stall avoidance systems in aircraft gas turbine engines. Model development is illustrated for the case of ...
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The focus of this paper is on the development of models for use in the design of active surge control/rotating stall avoidance systems in aircraft gas turbine engines. Model development is illustrated for the case of a single-spool, centrifugal compressor, turbojet engine currently housed within the LICCHUS experimental facility at Georgia Tech. This engine is equipped with high bandwidth fuel flow, nozzle area, and compressor discharge bleed area servos. The model developed for this engine is based on engine component steady state performance maps and unsteady quasi one-dimensional flow equations. The latter are rigorously developed herein. Special attention is paid to the assumptions underlying the model development, particularly those pertaining to the unsteady flow aspects of the model and its dynamic order. The resulting model has three control inputs, three states, and incorporates the dynamic linkage of the compressor and turbine through the spool. The three states are compressor mass flow, plenum pressure, and spool speed. Simulation results are given for the model which indicate that the model is capable of predicting and modeling surge phenomena. Because of its quasi one-dimensional nature, the model is not capable of predicting and modeling rotating stall per se. However, the model is capable of predicting and modeling the state of rotating stall as a condition of steady, greatly reduced, annulus-averaged compressor mass flow rate, and thus is adequate for the design of rotating stall avoidance systems. Additional simulation results are given which show the response of the model to the various control inputs.
This paper examines the system identification problem from the standpoint of control system design. Noting first that nearly all robust control design methods require explicit worst-case/deterministic bounds on the ex...
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This paper examines the system identification problem from the standpoint of control system design. Noting first that nearly all robust control design methods require explicit worst-case/deterministic bounds on the existing plant uncertainty, it is argued that the class of system identification methods which are inherently compatible with robust control design methods-or control-oriented is a subset of the class of system identification methods which yield an explicit worst-case/deterministic bound on the resulting identification error. An abstract theoretical framework for control-oriented system identification is then developed. This framework is inherently worst-case/deterministic in nature, and makes precise such notions as identification error, algorithm convergence, and algorithm optimality from a worst-case/deterministic standpoint. Finally, the abstract theoretical framework is utilized to formulate and solve two related control-oriented system identification problems for stable, linear, shift-invariant, distributed parameter plants. In each of these problems the assumed apriori information is minimal, consisting only of a lower bound on the relative stability of the plant, an upper bound on a certain gain associated with the plant, and an upper bound on the noise level. In neither case are any assumptions made concerning the structure of either the plant (i.e., dynamic order, relative order, etc.) or the noise (i.e., zero-mean, etc.). The first of these problems involves identification of a point sample of the plant frequency response from a noisy, finite, output time series obtained in response to an applied sinusoidal input with frequency corresponding to the frequency point of interest.
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