Expert adaptive control applied to turbogenerator systems

Deficiencies in the performance of conventional controllers has led to the development of self-tuning strategies for excitation control of turbogenerator systems. However, before such schemes can be implemented substantial monitoring or jacketing software is required. An expert system is proposed to perform these duties, allowing a distinction to be made between the control and identification algorithms and the accompanying supervisory functions. Test results on a laboratory microalternator are presented, illustrating the advantages of self-tuning control and how expert system intervention enhances controller performance and robustness.