Adaptivity and Robustness in Automatic Control Systems
This paper deals with various approaches to the solution of control problems for dynamic plants under uncertainty conditions. It gives a description of the principles for designing discrete-time adaptive and robust control systems and presents a discussion of their properties and specificities. A broader range of possibilities is given by robustly nominal systems that incorporate, together with a feedback loop from the system output, also a feedback that depends on the bias between the system output and the output of a special nominal model.
Robustly nominal systems allow to eliminate or to diminish substantially the effect of input as well as parametric disturbances that are due to parameter fluctuations within the range of uncertainty.
The principles of constructing robustly nominal systems are described together with the conditions for their realization based on criteria for robust stability.
For improving the quality of such systems we use algorithms for identifying the bias between the system output and the nominal model rather than those of identifying the dynamic plant itself. This simplifies the system structure and broadens the range of applications of robustly nominal systems as compared with traditional adaptive systems.
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