Multi‐innovation gradient‐based iterative identification methods for feedback nonlinear systems by using the decomposition technique

Abstract

Summary This paper studies the parameter estimation problems of feedback nonlinear systems. Combining the multi‐innovation identification theory with the negative gradient search, we derive a multi‐innovation gradient‐based iterative algorithm. In order to reduce the computational burden and further improve the parameter estimation accuracy, a decomposition multi‐innovation gradient‐based iterative algorithm is proposed by using the decomposition technique. The key is to transform an original system into two subsystems and to estimate the parameters of each subsystem, respectively. A simulation example is provided to demonstrate the effectiveness of the proposed algorithms.

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