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Active noise control systems currently in use and/or described in the research literature are typically based on adaptive signal processing theory or, equivalently, adaptive feedforward control theory. This paper presents a modern control approach to the problem of active noise cancellation in a three-dimensional space. The controller is designed based on a direct self-tuning regulator. Two forms of adaptive control, namely, pole placement and minimum variance controls are considered and compared in simulation. An implementation of the adaptive minimum variance controller is used to successfully attenuate a harmonic disturbance in a laboratory setting.

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The fundamental concept of feedback to control dynamic systems has played a major role in many areas of engineering. Increases in complexity and more stringent requirements have introduced new challenges for control systems. This paper presents an introduction to and appreciation for intelligent control systems, their application areas, and justifies their need. Specific problem related to automated human comfort control is discussed. Some analytical derivations related to neural networks and fuzzy optimal control as elements of proposed intelligent control systems, along with experimental results, are presented. A brief glossary of common terminology used in this area is included.