Learning Stable Koopman Operators with Convex Constraints for Improved Nonlinear System Modeling

A novel sufficient condition for the stability of discrete-time linear systems is presented, which can be expressed using piecewise linear constraints. This condition is leveraged to impose stability on a learnable Koopman matrix during the training process using a control barrier function-based projected gradient descent optimization.