Data-driven Linear Quadratic Regulation via Semidefinite Programming

2019/11/18 by Rotulo, Monica, De Persis, Claudio, Tesi, Pietro · 1 citation
#FOS: Electrical engineering #FOS: Mathematics #Optimization and Control (math.OC) #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · doi:10.48550/arxiv.1911.07767

Abstract

This paper studies the finite-horizon linear quadratic regulation problem where the dynamics of the system are assumed to be unknown and the state is accessible. Information on the system is given by a finite set of input-state data, where the input injected in the system is persistently exciting of a sufficiently high order. Using data, the optimal control law is then obtained as the solution of a suitable semidefinite program. The effectiveness of the approach is illustrated via numerical examples.

Cited by

• A Data-Ensemble-Based Approach for Sample-Efficient LQ Control of Linear Time-Varying Systems

Related

• Determining optimal input-output properties: A data-driven approach
• Safely Learning to Control the Constrained Linear Quadratic Regulator
• Designing Experiments for Data-Driven Control of Nonlinear Systems
• Guarantees for data-driven control of nonlinear systems using semidefinite programming: A survey
• Formulas for Data-driven Control: Stabilization, Optimality and\n Robustness