Modeling, Identification and Control of Model Jet Engines for Jet Powered Robotics

TL;DR

This paper presents a comprehensive approach to modeling, identifying, and controlling model jet engines using nonlinear dynamics, sparse identification, and advanced control techniques, validated on JetCat engine models.

Contribution

It introduces a novel nonlinear second-order model for jet engines and applies sparse and gray-box identification methods, along with feedback linearization and sliding mode control.

Findings

Successful modeling and identification of JetCat engines

Effective control laws implemented and verified

Enhanced understanding of jet engine dynamics

Abstract

The paper contributes towards the modeling, identification, and control of model jet engines. We propose a nonlinear, second order model in order to capture the model jet engines governing dynamics. The model structure is identified by applying sparse identification of nonlinear dynamics, and then the parameters of the model are found via gray-box identification procedures. Once the model has been identified, we approached the control of the model jet engine by designing two control laws. The first one is based on the classical Feedback Linearization technique while the second one on the Sliding Mode control. The overall methodology has been verified by modeling, identifying and controlling two model jet engines, i.e. P100-RX and P220-RXi developed by JetCat, which provide a maximum thrust of 100 N and 220 N, respectively.