Bounded error identification of Hammerstein systems through sparse polynomial optimization |
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| Authors: | V Cerone D Piga D Regruto |
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| Affiliation: | 1. College of Automation and Electronic Engineering, Qingdao University of Science and Technology, Qingdao 266042, PR China;2. School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, PR China;3. School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, PR China;4. Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia |
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| Abstract: | In this paper we present a procedure for the evaluation of bounds on the parameters of Hammerstein systems, from output measurements affected by bounded errors. The identification problem is formulated in terms of polynomial optimization, and relaxation techniques, based on linear matrix inequalities, are proposed to evaluate parameter bounds by means of convex optimization. The structured sparsity of the formulated identification problem is exploited to reduce the computational complexity of the convex relaxed problem. Analysis of convergence properties and computational complexity is reported. |
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