12 papers
A Koopman--Polynomial Chaos Framework for SMPC of Nonlinear Stochastic Processes
Wallace Gian Yion Tan, Efstathios Iliakis, Liang Wu +2
This paper develops a polynomial parametric Koopman operator (PPKO) framework for stochastic model predictive control (SMPC) of nonlinear systems with parametric uncertainty and ti…
DR-MPC: Fast and Feasible Dynamics-Relaxed Model-Predictive Control for Legged Locomotion
Run Wang, Alapati Tuerxun, Shuo Liu +4
This paper presents dynamics-relaxed model predictive control (DR-MPC), a novel MPC formulation for legged locomotion, and a tailored interior-point method (IPM) solver. The formul…
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…
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…
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…
EIQP: Execution-time-certified and Infeasibility-detecting QP Solver
Liang Wu, Wei Xiao, Richard D. Braatz
Solving real-time quadratic programming (QP) is a ubiquitous task in control engineering, such as in model predictive control and control barrier function-based QP. In such real-ti…
A Parallel Vector-form Decomposition for Accelerating Execution-time-certified -penalty Soft-constrained MPC
Liang Wu, Liwei Zhou, Richard D. Braatz
Handling possible infeasibility and providing an execution time certificate are two pressing requirements of real-time Model Predictive Control (MPC). To meet these two requirement…
Time-certified Input-constrained NMPC via Koopman Operator
Liang Wu, Krystian Ganko, Richard D. Braatz
Determining solving-time certificates of nonlinear model predictive control (NMPC) implementations is a pressing requirement when deploying NMPC in production environments. Such a…
An Execution-time-certified Riccati-based IPM Algorithm for RTI-based Input-constrained NMPC
Liang Wu, Krystian Ganko, Shimin Wang +1
Establishing an execution time certificate in deploying model predictive control (MPC) is a pressing and challenging requirement. As nonlinear MPC (NMPC) results in nonlinear progr…