7 papers
Fixed-time-stable ODE Representation of Lasso
Liang Wu, Yunhong Che, Wallace Gian Yion Tan +3
Lasso problems arise in many areas, including signal processing, machine learning, and control, and are closely connected to sparse coding mechanisms observed in neuroscience. A co…
Polynomial Parametric Koopman Operators for Stochastic MPC
Efstathios Iliakis, Wallace Gian Yion Tan, Liang Wu +2
This paper develops a parametric Koopman operator framework for Stochastic Model Predictive Control (SMPC), where the Koopman operator is parametrized by Polynomial Chaos Expansion…
Least-Squares Multi-Step Koopman Operator Learning for Model Predictive Control
Liang Wu, Wallace Gian Yion Tan, Leqi Zhou +2
MPC is widely used in real-time applications, but practical implementations are typically restricted to convex QP formulations to ensure fast and certified execution. Koopman-based…
Arbitrarily Small Execution-Time Certificate: What was Missed in Analog Optimization
Liang Wu, Ambrose Adegbege, Yongduan Song +1
Numerical optimization (solving optimization problems using digital computers) currently dominates but has three major drawbacks: high energy consumption, poor scalability, and lac…
A Time-certified Predictor-corrector IPM Algorithm for Box-QP
Liang Wu, Yunhong Che, Richard D. Braatz +1
Minimizing both the worst-case and average execution times of optimization algorithms is equally critical in real-time optimization-based control applications such as model predict…
A Quadratic Programming Algorithm with Time Complexity
Liang Wu, Richard D. Braatz
Solving linear systems and quadratic programming (QP) problems are both ubiquitous tasks in the engineering and computing fields. Direct methods for solving systems, such as Choles…