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An experimental verification of the influence matrix approach to fault diagnosis and automatic tuning is proposed. The coefficients of the system transfer function are identified and the Jacobian of the coefficient vector with respect to physical parameters, termed the influence mam, is computed. The influence matrix is used to detect and isolate faults. The optimal controller parameters are obtained using the influence matrix. It is assumed that the system is linear and time invariant, and the physical parameters enter the coefficient vector multiliaearly. The proposed method is verified on a physical robot manipulator arm.

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This papet propcwes a method to compute n-th order moments of objects in a binary image. The aaditional method is order Nz. The method consists of an edge following routine followed by a second recursive moment generation routine which operates on the edge information. The speedup was determined to be on the order of 3 to 6 times for a 256 by 256 pixel image.