LEADER 04749nam 22007575 450 001 9910299737103321 005 20200703060529.0 010 $a981-4585-60-2 024 7 $a10.1007/978-981-4585-60-6 035 $a(CKB)3710000000134681 035 $a(EBL)1783831 035 $a(OCoLC)889305396 035 $a(SSID)ssj0001274430 035 $a(PQKBManifestationID)11758841 035 $a(PQKBTitleCode)TC0001274430 035 $a(PQKBWorkID)11326125 035 $a(PQKB)10773289 035 $a(MiAaPQ)EBC1783831 035 $a(DE-He213)978-981-4585-60-6 035 $a(PPN)179767267 035 $a(EXLCZ)993710000000134681 100 $a20140619d2014 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aPractical Iterative Learning Control with Frequency Domain Design and Sampled Data Implementation /$fby Danwei Wang, Yongqiang Ye, Bin Zhang 205 $a1st ed. 2014. 210 1$aSingapore :$cSpringer Singapore :$cImprint: Springer,$d2014. 215 $a1 online resource (232 p.) 225 1 $aAdvances in Industrial Control,$x1430-9491 300 $aDescription based upon print version of record. 311 $a1-322-17584-5 311 $a981-4585-59-9 320 $aIncludes bibliographical references at the end of each chapters. 327 $aIntroduction -- Extend Learnable Band and Multi-channel Configuration -- Learnable Bandwidth Extension by Auto-Tunings -- Reverse Time Filtering Based ILC -- Wavelet Transform based Frequency Tuning ILC -- Learning Transient Performance with Cutoff-Frequency Phase-In -- Downsampled ILC -- Cyclic Pseudo-Downsampled ILC. 330 $aThis book is on the iterative learning control (ILC) with focus on the design and implementation. We approach the ILC design based on the frequency domain analysis and address the ILC implementation based on the sampled data methods. This is the first book of ILC from frequency domain and sampled data methodologies. The frequency domain design methods offer ILC users insights to the convergence performance which is of practical benefits. This book presents a comprehensive framework with various methodologies to ensure the learnable bandwidth in the ILC system to be set with a balance between learning performance and learning stability. The sampled data implementation ensures effective execution of ILC in practical dynamic systems. The presented sampled data ILC methods also ensure the balance of performance and stability of learning process. Furthermore, the presented theories and methodologies are tested with an ILC controlled robotic system. The experimental results show that the machines can work in much higher accuracy than a feedback control alone can offer. With the proposed ILC algorithms, it is possible that machines can work to their hardware design limits set by sensors and actuators. The target audience for this book includes scientists, engineers and practitioners involved in any systems with repetitive operations. 410 0$aAdvances in Industrial Control,$x1430-9491 606 $aComputational intelligence 606 $aNeural networks (Computer science)  606 $aArtificial intelligence 606 $aStatistical physics 606 $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014 606 $aMathematical Models of Cognitive Processes and Neural Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/M13100 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aApplications of Nonlinear Dynamics and Chaos Theory$3https://scigraph.springernature.com/ontologies/product-market-codes/P33020 615 0$aComputational intelligence. 615 0$aNeural networks (Computer science) . 615 0$aArtificial intelligence. 615 0$aStatistical physics. 615 14$aComputational Intelligence. 615 24$aMathematical Models of Cognitive Processes and Neural Networks. 615 24$aArtificial Intelligence. 615 24$aApplications of Nonlinear Dynamics and Chaos Theory. 676 $a629.895630151563 700 $aWang$b Danwei$4aut$4http://id.loc.gov/vocabulary/relators/aut$0964453 702 $aYe$b Yongqiang$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aZhang$b Bin$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910299737103321 996 $aPractical Iterative Learning Control with Frequency Domain Design and Sampled Data Implementation$92199696 997 $aUNINA