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PID control with intelligent compensation for exoskeleton robots
正題名/作者 ： PID control with intelligent compensation for exoskeleton robots/ Wen Yu.
作者 ： Yu, Wen.
出版者 ： London :Academic Press,2018.
面頁冊數 ： 1 online resource :ill.
標題 ： PID controllers. -
電子資源 ： 線上閱讀(Elsevier)
ISBN ： 9780128134641$q(electronic bk.)
ISBN ： 012813464X$q(electronic bk.)
ISBN ： 9780128133804$q(print)
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020 $a9780128134641$q(electronic bk.)
020 $a012813464X$q(electronic bk.)
020 $a9780128133804$q(print)
035 $a00357816
041 0 $aeng
050 4$aTJ223.P55
082 04$a629.8$223
090 $aE-BOOK/629.8///UE040102
100 1 $aYu, Wen.$3407057
245 10$aPID control with intelligent compensation for exoskeleton robots$h[electronic resource] /$cWen Yu.
260 $aLondon :$bAcademic Press,$c2018.
300 $a1 online resource :$bill.
504 $aIncludes bibliographical references and index.
505 0 $aStable PID control and systematic tuning of PID gains -- PID control in task space -- PD control with neural compensation -- PID control with neural compensation -- PD control with fuzzy compensation -- PD control with sliding mode compensation -- PID admittance control in task space -- PID admittance control in joint space -- Robot trajectory generation in joint space -- Design of upper limb exoskeletions.
520 $aExplains how to use neural PD and PID controls to reduce integration gain, and provides explicit conditions on how to select linear PID gains using proof of semi-global asymptotic stability and local asymptotic stability with a velocity observer. These conditions are applied in both task and joint spaces, with PID controllers compensated by neural networks. This is a great resource on how to combine traditional PD/PID control techniques with intelligent control. Dr. Wen Yu presents several leading-edge methods for designing neural and fuzzy compensators with high-gain velocity observers for PD control using Lyapunov stability. Proportional-integral-derivative (PID) control is widely used in biomedical and industrial robot manipulators. An integrator in a PID controller reduces the bandwidth of the closed-loop system, leads to less-effective transient performance and may even destroy stability. Many robotic manipulators use proportional-derivative (PD) control with gravity and friction compensations, but improved gravity and friction models are needed. The introduction of intelligent control in these systems has dramatically changed the face of biomedical and industrial control engineering.
650 0$aPID controllers.$3407060
650 0$aIntelligent control systems.$3171014
650 0$aRobotics.$3170207
655 4$aElectronic books.$3297295
856 40$uhttps://erm.library.ntpu.edu.tw/login?url=https://www.sciencedirect.com/science/book/9780128133804$z線上閱讀(Elsevier)
Yu, Wen.
PID control with intelligent compensation for exoskeleton robots[electronic resource] /Wen Yu. - London :Academic Press,2018. - 1 online resource :ill.
Includes bibliographical references and index.
Stable PID control and systematic tuning of PID gains -- PID control in task space -- PD control with neural compensation -- PID control with neural compensation -- PD control with fuzzy compensation -- PD control with sliding mode compensation -- PID admittance control in task space -- PID admittance control in joint space -- Robot trajectory generation in joint space -- Design of upper limb exoskeletions.
Explains how to use neural PD and PID controls to reduce integration gain, and provides explicit conditions on how to select linear PID gains using proof of semi-global asymptotic stability and local asymptotic stability with a velocity observer. These conditions are applied in both task and joint spaces, with PID controllers compensated by neural networks. This is a great resource on how to combine traditional PD/PID control techniques with intelligent control. Dr. Wen Yu presents several leading-edge methods for designing neural and fuzzy compensators with high-gain velocity observers for PD control using Lyapunov stability. Proportional-integral-derivative (PID) control is widely used in biomedical and industrial robot manipulators. An integrator in a PID controller reduces the bandwidth of the closed-loop system, leads to less-effective transient performance and may even destroy stability. Many robotic manipulators use proportional-derivative (PD) control with gravity and friction compensations, but improved gravity and friction models are needed. The introduction of intelligent control in these systems has dramatically changed the face of biomedical and industrial control engineering.
ISBN: 9780128134641$q(electronic bk.)Subjects--Topical Terms:
407060
PID controllers.
Index Terms--Genre/Form:
297295
Electronic books.
LC Class. No.: TJ223.P55
Dewey Class. No.: 629.8
PID control with intelligent compensation for exoskeleton robots[electronic resource] /Wen Yu. - London :Academic Press,2018. - 1 online resource :ill.
Includes bibliographical references and index.
Stable PID control and systematic tuning of PID gains -- PID control in task space -- PD control with neural compensation -- PID control with neural compensation -- PD control with fuzzy compensation -- PD control with sliding mode compensation -- PID admittance control in task space -- PID admittance control in joint space -- Robot trajectory generation in joint space -- Design of upper limb exoskeletions.
Explains how to use neural PD and PID controls to reduce integration gain, and provides explicit conditions on how to select linear PID gains using proof of semi-global asymptotic stability and local asymptotic stability with a velocity observer. These conditions are applied in both task and joint spaces, with PID controllers compensated by neural networks. This is a great resource on how to combine traditional PD/PID control techniques with intelligent control. Dr. Wen Yu presents several leading-edge methods for designing neural and fuzzy compensators with high-gain velocity observers for PD control using Lyapunov stability. Proportional-integral-derivative (PID) control is widely used in biomedical and industrial robot manipulators. An integrator in a PID controller reduces the bandwidth of the closed-loop system, leads to less-effective transient performance and may even destroy stability. Many robotic manipulators use proportional-derivative (PD) control with gravity and friction compensations, but improved gravity and friction models are needed. The introduction of intelligent control in these systems has dramatically changed the face of biomedical and industrial control engineering.
ISBN: 9780128134641$q(electronic bk.)Subjects--Topical Terms:
407060
PID controllers.
Index Terms--Genre/Form:
297295
Electronic books.
LC Class. No.: TJ223.P55
Dewey Class. No.: 629.8
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