Asynchronously H∞ Tracking Control and Optimization for Switched Flight Vehicles with Time-Varying Delay

Asynchronously H∞ Tracking Control and Optimization for Switched Flight Vehicles with Time-Varying Delay Xing Yang Unmanned System Reasearch Institute, Northwestern Polytechnical University, Xi’an 710072, China http://orcid.org/0009-0009-6170-6668 Bin Fu Unmanned System Reasearch Institute, Northwestern Polytechnical University, Xi’an 710072, China http://orcid.org/0000-0003-4590-0216 Xiaochuan Ma Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China Yu Liu Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China Dongyu Yuan Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China Xintong Wu Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China

The current paper verifies the asynchronous H∞ control and optimization problem for flight vehicles with a time-varying delay. The nonlinear dynamic model and Jacobian linearization establish the flight vehicle’s switched model. An asynchronous H∞ tracking controller is designed, considering the existing asynchronous switching between the controllers and corresponding subsystems. In order to promote transient efficiency, the tracking controller comprises the model-based part and the learning-based part. The model-based part guarantees stability and prescribed efficiency, and the learning-based part compensates for undesirable uncertainties. The multiple Lyapunov function (MLF) and mode-dependent average dwell time (MDADT) methods are utilized to guarantee stability and the specified attenuation efficiency. The existing conditions and the solutions of model-based sub-controllers are represented by linear matrix inequalities (LMIs). The deep Q learning (DQL) algorithm provides the learning-based part. Different from the conventional method, the controller parameters are scheduled online. Therefore, robustness, stability, and dynamic efficiency can be met simultaneously. A numerical example illustrates the efficiency and advantage of the presented approach.
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