Semi-global self-adaptive control method aiming at non-standard nonlinear aircrafts
A technology of adaptive control and adaptive controller, applied in the direction of adaptive control, general control system, control/regulation system, etc., can solve problems such as the inability to expand the aircraft system
Patent Information
- Authority / Receiving Office
- CN · China
- Current Assignee / Owner
- Publication Date
- 2019-08-09
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Abstract
Description
technical field
[0001] The invention relates to a semi-global self-adaptive control method for non-standard non-linear aircraft, and belongs to the field of self-adaptive control of rigid aircraft longitudinal dynamics systems. Background technique
[0002] Aircraft systems usually have large parameter or structural uncertainties due to the large operating range, the influence of external environment changes and system failures. As an important issue of aircraft system, adaptive control has been extensively studied and important progress has been made.
[0003] Existing aircraft flight control methods are mainly limited to locally linearized aircraft systems or standard nonlinear systems. For example, in the document "Multivariable adaptive algorithms for reconfigurable flightcontrol", the model reference adaptive control problem of the local linearization model of the F / A-18C / D aircraft is studied. However, this control method using a locally linearized aircraft system mo...
Examples
Embodiment
[0108] Below in conjunction with a group of linearized Boeing 737 longitudinal dynamics models and accompanying drawings to demonstrate the proposed control method, the present invention will be described in further detail.
[0109] In this embodiment, the semi-global adaptive control method includes the following steps:
[0110] 1. T-S fuzzy intelligent modeling of non-standard nonlinear aircraft system
[0111] 1) Locally linearized aircraft system model, using three locally linearized Boeing 737 longitudinal dynamic models, covering three modes of aircraft climbing, cruising and descending;
[0112] In the climbing case, the linearization matrix is
[0113]
[0114] In the descending case, the linearization matrix is
[0115]
[0116] In the cruise case, the linearization matrix is
[0117]
[0118] For each operating point (climb, cruise, descent) in this simulation, the system output matrix is chosen as
[0119] C=[0,1,0,0]
[0120] 2) T-S fuzzy intelligen...