語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Iterative learning control = an opti...
~
Owens, David H.
Iterative learning control = an optimization paradigm /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Iterative learning control/ by David H. Owens.
其他題名:
an optimization paradigm /
作者:
Owens, David H.
出版者:
London :Springer London : : 2016.,
面頁冊數:
xxviii, 456 p. :ill., digital ; : 24 cm.;
Contained By:
Springer eBooks
標題:
Intelligent control systems. -
電子資源:
http://dx.doi.org/10.1007/978-1-4471-6772-3
ISBN:
9781447167723
Iterative learning control = an optimization paradigm /
Owens, David H.
Iterative learning control
an optimization paradigm /[electronic resource] :by David H. Owens. - London :Springer London :2016. - xxviii, 456 p. :ill., digital ;24 cm. - Advances in industrial control,1430-9491. - Advances in industrial control..
This book develops a coherent theoretical approach to algorithm design for iterative learning control based on the use of optimization concepts. Concentrating initially on linear, discrete-time systems, the author gives the reader access to theories based on either signal or parameter optimization. Although the two approaches are shown to be related in a formal mathematical sense, the text presents them separately because their relevant algorithm design issues are distinct and give rise to different performance capabilities. Together with algorithm design, the text demonstrates that there are new algorithms that are capable of incorporating input and output constraints, enable the algorithm to reconfigure systematically in order to meet the requirements of different reference signals and also to support new algorithms for local convergence of nonlinear iterative control. Simulation and application studies are used to illustrate algorithm properties and performance in systems like gantry robots and other electromechanical and/or mechanical systems. Iterative Learning Control will interest academics and graduate students working in control who will find it a useful reference to the current status of a powerful and increasingly popular method of control. The depth of background theory and links to practical systems will be of use to engineers responsible for precision repetitive processes. Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
ISBN: 9781447167723
Standard No.: 10.1007/978-1-4471-6772-3doiSubjects--Topical Terms:
557331
Intelligent control systems.
LC Class. No.: TJ217.5
Dewey Class. No.: 629.8
Iterative learning control = an optimization paradigm /
LDR
:02717nam a2200313 a 4500
001
860736
003
DE-He213
005
20160720113953.0
006
m d
007
cr nn 008maaau
008
170720s2016 enk s 0 eng d
020
$a
9781447167723
$q
(electronic bk.)
020
$a
9781447167709
$q
(paper)
024
7
$a
10.1007/978-1-4471-6772-3
$2
doi
035
$a
978-1-4471-6772-3
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
TJ217.5
072
7
$a
TJFM
$2
bicssc
072
7
$a
TEC004000
$2
bisacsh
082
0 4
$a
629.8
$2
23
090
$a
TJ217.5
$b
.O97 2016
100
1
$a
Owens, David H.
$3
1102624
245
1 0
$a
Iterative learning control
$h
[electronic resource] :
$b
an optimization paradigm /
$c
by David H. Owens.
260
$a
London :
$c
2016.
$b
Springer London :
$b
Imprint: Springer,
300
$a
xxviii, 456 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
Advances in industrial control,
$x
1430-9491
520
$a
This book develops a coherent theoretical approach to algorithm design for iterative learning control based on the use of optimization concepts. Concentrating initially on linear, discrete-time systems, the author gives the reader access to theories based on either signal or parameter optimization. Although the two approaches are shown to be related in a formal mathematical sense, the text presents them separately because their relevant algorithm design issues are distinct and give rise to different performance capabilities. Together with algorithm design, the text demonstrates that there are new algorithms that are capable of incorporating input and output constraints, enable the algorithm to reconfigure systematically in order to meet the requirements of different reference signals and also to support new algorithms for local convergence of nonlinear iterative control. Simulation and application studies are used to illustrate algorithm properties and performance in systems like gantry robots and other electromechanical and/or mechanical systems. Iterative Learning Control will interest academics and graduate students working in control who will find it a useful reference to the current status of a powerful and increasingly popular method of control. The depth of background theory and links to practical systems will be of use to engineers responsible for precision repetitive processes. Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
650
0
$a
Intelligent control systems.
$3
557331
650
1 4
$a
Engineering.
$3
561152
650
2 4
$a
Control.
$3
782232
650
2 4
$a
Systems Theory, Control.
$3
669337
650
2 4
$a
Artificial Intelligence (incl. Robotics)
$3
593924
650
2 4
$a
Machinery and Machine Elements.
$3
670866
650
2 4
$a
Robotics and Automation.
$3
782979
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer eBooks
830
0
$a
Advances in industrial control.
$3
639855
856
4 0
$u
http://dx.doi.org/10.1007/978-1-4471-6772-3
950
$a
Engineering (Springer-11647)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入