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PID Control with Intelligent Compensation for Exoskeleton Robots (Paperback)
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PID Control with Intelligent Compensation for Exoskeleton Robots (Paperback)
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PID Control with Intelligent Compensation for Exoskeleton Robots
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.
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