VHDL‐AMS based genetic optimisation of fuzzy logic controllers

This paper presents a VHDL‐AMS based genetic optimisation methodology for fuzzy logic controllers (FLCs) used in complex automotive systems and modelled in mixed physical domains. A case study applying this novel method to an active suspension system has been investigated to obtain a new type of fuzzy logic membership function with irregular shapes optimised for best performance.

The geometrical shapes of the fuzzy logic membership functions are irregular and optimised using a genetic algorithm (GA). In this optimisation technique, VHDL‐AMS is used not only for the modelling and simulation of the FLC and its underlying active suspension system but also for the implementation of a parallel GA directly in the system testbench.

Simulation results show that the proposed FLC has superior performance in all test cases to that of existing FLCs that use regular‐shape, triangular or trapezoidal membership functions.

The test of the FLC has only been done in the simulation stage, no physical prototype has been made.

This paper proposes a novel way of improving the FLC's performance and a new application area for VHDL‐AMS.