Asymptotically optimum recursive prediction error methods in adaptive estimation and control

✍ Scribed by John B. Moore; Rene K. Boel

• Book ID: 102639854
• Publisher: Elsevier Science
• Year: 1986
• Tongue: English
• Weight: 367 KB
• Volume: 22
• Category: Article
• ISSN: 0005-1098
• DOI: 10.1016/0005-1098(86)90086-5

✦ Synopsis

Al~tract--The challenge taken up in this paper is to devise a parameter identification algorithm for linear, discrete-time, stochastic plants which exploits the strengths of both the extended least squares (ELS) and the recursive prediction error (RPE) parameter estimation methods. The focus is On adaptive control of parameterized state space models which exploit a priori plant information in that the unknown parameter vector 0" is of lower dimension than that for a corresponding input-output model parameterized by 0.

A triple parameter estimation scheme consisting of ELS, RPE and a hybrid oftbe two, denoted HPE, is proposed. The purpose of the HPE scheme is to permit information flow from the ELS to RPE algorithms so as to effectively project RPE into a stability domain, and to have it avoid local prediction error index minima that are not the global minimum.