A case for using Minipop as the evolutionary engine in a CTRNN-EH control device: an analysis of area requirements and search efficacy

Continuous time recurrent neural network-evolvable hardware (CTRNN-EH) control devices comprise of an analog continuous time recurrent neural network (CTRNN) with an on-board evolutionary algorithm (EA) engine to evolve the parameters of the neural network. These control devices were demonstrated to be effective for suppressing thermoacoustic (TA) instability in simulated jet engines. Currently, the construction of a VLSI CTRNN-EH device is underway for suppressing TA instability in a real combustion chamber while it is in operation. In this paper, we present a fully function digital EA engine for the CTRNN-EH control device. An ad-hoc hardware design is presented to realize space savings. The simulation and synthesis results of the hardware EA are presented. In addition to this, a demonstration of the efficacy of the EA across a noisy real world control problem is presented.