Titlebook: Iterative Learning Control for Systems with Iteration-Varying Trial Lengths; Synthesis and Analys Dong Shen,Xuefang Li Book 2019 Springer N

木讷

Dong Shen,Xuefang Lieen high and our methodologies can be summarized by discussing three tenants of GAMESPECT: 1) composition specifications, which define source to source transition properties 2) pluggable aspect interpreters and 3) high level language constructs and modeling language constructs (MDAML) which encourag

AXIS

Dong Shen,Xuefang Liel including the metamodel itself, can be transformed. Moreover, the transformation of application data to or from RDF is also possible. Having the NS metamodel, NS models, and potentially also data in RDF opens further research possibilities in terms of analysis and integrations. The use of NS Expa

眨眼

联邦

Iterative Learning Control for Systems with Iteration-Varying Trial LengthsSynthesis and Analys

思想上升

Iterative Learning Control for Systems with Iteration-Varying Trial Lengths978-981-13-6136-4

袭击

sintuitive figures to allow readers to develop an in-depth understanding of the intrinsic relationship between the incomplete information environment and the essential tracking performance. This book is intende978-981-13-6136-4

Excitotoxin

万灵丹

Averaging Techniques for Linear Discrete-Time Systemsial lengths. An ILC scheme with an iteration-average operator is introduced for tracking tasks with nonuniform trial lengths, which thus mitigates the requirement on classic ILC that all trial lengths must be identical. In addition, the identical initialization condition can be absolutely removed. T

Cholagogue

Averaging and Lifting Techniques for Linear Discrete-Time Systemshap. ., this chapter aims to avoid using the traditional .-norm in convergence analysis which may lead to a non-monotonic convergence. Compared to Chap. ., the main contributions of the chapter can be summarized as follows: (i) A new formulation is presented for ILC of discrete-time systems with ran

Accommodation