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PID control with intelligent compensation for exoskeleton robots /

紀錄類型:	書目-電子資源 : Monograph/item
杜威分類號:	629.8
書名/作者:	PID control with intelligent compensation for exoskeleton robots // Wen Yu, CINVESTAV-IPN (National Polytechnic Institute), Mexico City, Mexico.
作者:	Yu, Wen,
面頁冊數:	1 online resource : : illustrations
標題:	PID controllers.
標題:	Intelligent control systems.
標題:	Robotics.
ISBN:	9780128134641
ISBN:	012813464X
ISBN:	9780128133804
書目註:	Includes bibliographical references and index.
內容註:	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.
摘要、提要註:	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.
電子資源:	https://www.sciencedirect.com/science/book/9780128133804

PID control with intelligent compensation for exoskeleton robots /
Yu, Wen,profesor titular,

PID control with intelligent compensation for exoskeleton robots /Wen Yu, CINVESTAV-IPN (National Polytechnic Institute), Mexico City, Mexico. - 1 online resource :illustrations

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: 9780128134641Subjects--Topical Terms:

622632
PID controllers.
Index Terms--Genre/Form:

336502
Electronic books.

LC Class. No.: TJ223.P55

Dewey Class. No.: 629.8

PID control with intelligent compensation for exoskeleton robots /
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504 $a Includes bibliographical references and index.
505 0 $a 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.
520 $a 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.
650 0 $a PID controllers. $3 622632
650 0 $a Intelligent control systems. $3 184990
650 0 $a Robotics. $3 175953
655 4 $a Electronic books. $2 local $3 336502
856 4 0 $u https://www.sciencedirect.com/science/book/9780128133804