Abstract
A gas turbine engine represents a complex dynamic control object. Its characteristics change depending on the state of the environment and the regimes of its operation. This paper discusses an algorithmic approach to the design of a nonlinear controller, based on the concept of constant eigenvectors and analytical design of the control system. The proposed design method makes it possible to ensure the stability and the required quality of transient processes at different acceleration modes. In this case, the constancy of the matrix of the canonical basis of the closed-loop control system is assumed, which guarantees stability. The design of a neural network dynamic model of a gas turbine engine based on a neural network approximator with one input and multiple outputs is considered. An example of the design of a nonlinear controller for a gas turbine engine is considered, the neural network model of which is given in the state space. The application of neural network approximation of controller coefficients is presented.
Highlights
A gas turbine engine is a complex heat machine in which numerous subsystems serve the main purpose of creating jet thrust for aircraft movement [1]
The main tasks of the control system of a gas turbine engine are to ensure the efficiency of the power plant in various regimes [5], and to provide the safe running of the processes of generating thrust [6], taking into account technological limitations [7,8]
Gas turbine engines belong to the class of complex heat machines, which are widely used to solve various tasks
Summary
A gas turbine engine is a complex heat machine in which numerous subsystems serve the main purpose of creating jet thrust for aircraft movement [1]. The main tasks of the control system of a gas turbine engine are to ensure the efficiency of the power plant in various regimes [5], and to provide the safe running of the processes of generating thrust [6], taking into account technological limitations [7,8]. These parameters determine the performance of this complex control object [9,10]. The design of an algorithm for controlling a dynamic object in a state space is usually understood as the problem of determining the structure and parameters of controllers that provide the specified spectral properties of closed-loop control system eigenvalues. The algorithmic complexity of this control algorithm depends linearly on the dimension of the input problem or the order of the control system [21]
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