Benchmarking MLC against linear control

Abstract

In this chapter, we demonstrate the use of genetic programming for machine learning control (MLC) on linear systems where optimal control laws are known. In particular, we benchmark MLC against the linear quadratic regulator (LQR) for full-state feedback and the Kalman filter for full-state estimation, providing code for each example. MLC is able to identify the optimal linear control solutions and outperforms linear control even for small nonlinearity.