{"product_id":"9781849966580","title":"Communications and Control Engineering: Robustness and Monotonic Convergence for Interval Systems","description":"\u003ch1\u003eCommunications and Control Engineering: Robustness and Monotonic Convergence for Interval Systems\u003c\/h1\u003e \u003ch2\u003eAhn, Hyo-Sung; Moore, Kevin L.; Chen, YangQuan\u003c\/h2\u003e \u003cp\u003eThis monograph studies the design of robust, monotonically-convergent it- ative learning controllers for discrete-time systems. Iterative learning control (ILC) is well-recognized as an e?cient method that o?ers signi?cant p- formance improvement for systems that operate in an iterative or repetitive fashion (e. g. , robot arms in manufacturing or batch processes in an industrial setting). Though the fundamentals of ILC design have been well-addressed in the literature, two key problems have been the subject of continuing - search activity. First, many ILC design strategies assume nominal knowledge of the system to be controlled. Only recently has a comprehensive approach to robust ILC analysis and design been established to handle the situation where the plant model is uncertain. Second, it is well-known that many ILC algorithms do not produce monotonic convergence, though in applications monotonic convergencecan be essential. This monograph addresses these two keyproblems by providingauni?ed analysisanddesignframeworkforrobust, monotonically-convergent ILC. The particular approach used throughout is to consider ILC design in the iteration domain, rather than in the time domain. Using a lifting technique, the two-dimensionalILC system, whichhas dynamics in both the time and - erationdomains,istransformedintoaone-dimensionalsystem,withdynamics only in the iteration domain. The so-called super-vector framework resulting from this transformation is used to analyze both robustness and monotonic convergence for typical uncertainty models, including parametric interval - certainties, frequency-like uncertainty in the iteration domain, and iterati- domain stochastic uncertainty.\u003c\/p\u003e \u003ch3\u003eDetails\u003c\/h3\u003e \u003cp\u003ePublished by: Springer\u003c\/p\u003e \u003cp\u003ePublication Date: 2010-10-19\u003c\/p\u003e \u003cp\u003eFormat: Paperback\u003c\/p\u003e \u003cp\u003eISBN-13: 9781849966580\u003c\/p\u003e \u003cp\u003eDOI: 10.1007\/978-1-84628-859-3\u003c\/p\u003e \u003cp\u003eDimensions: 235cm x155cm\u003c\/p\u003e \u003cp\u003ePages: 230\u003c\/p\u003e ","brand":"Springer London","offers":[{"title":"Default Title","offer_id":47982686142604,"sku":"9781849966580","price":152.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9781849966580.jpg?v=1777376969","url":"https:\/\/fh90cf-fv.myshopify.com\/products\/9781849966580","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}