Autonomous Controls Laboratory (ACL)

A Proximal Method for Composite Optimization with Smooth and Convex Components

Trajectory Optimization with Continuous-time Satisfaction of Signal Temporal Logic Specifications

Optimal Preconditioning for Online Quadratic Cone Programming

Optimization with Temporal and Logical Specifications via Generalized Mean-based Smooth Robustness Measures (D-GMSR)

Successive Convexification for Nonlinear Model Predictive Control with Continuous-Time Constraint Satisfaction

Sequential Convex Programming for 6-DoF Powered Descent Guidance with Continuous-Time Compound State-Triggered Constraints

The code base for Newton-PIPG

Discrete-Time Lossless Convexification (DT-LCvx) formulates a convex relaxation for a specific class of discrete-time non-convex optimal control problems. It establishes sufficient conditions under which the solution of the relaxed problem satisfies the original non-convex constraints at specified time grid points.