Abstract
The requirement for the high quality control of complex and/or structure-unknown plant is growing in the real-world industrial machine. Indiect Adaptive Control (IAC), which identifies model and updates the controllers automatically, is expected as on of the promising way to meet this requirement. The conventional IAC, however, required to know the structure of the structure of the controlled plant, i.e. the order of its transfer function in advance. This paper presents a new IAC scheme which makes use of Genetic Algorithm (GA) in its identification part. In the proposed framework, the information on the order of the plant is not required since GA searches both the structure of the plant dynamics and its parameters autonomously. A two-degree-of freedom Internal Model Control (IMC) is adopted as a basic control architecture since the indirect adaptation can be harmoniously embedded in it. The effectiveness of the proposed scheme is verified though numerical simulations and experiments applied to a velocity control of multi-mass systems.
