Modeling, Identification and Control of Model Jet Engines for Jet Powered Robotics
This work addresses control challenges for jet-powered robotics, but it is incremental as it applies existing methods to a specific domain.
The paper tackled modeling, identification, and control of model jet engines by proposing a nonlinear second-order model, identifying it using sparse and gray-box methods, and designing feedback linearization and sliding mode control laws, verified on two JetCat engines with thrusts up to 220 N.
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.