16,537 research outputs found
A New Data Source for Inverse Dynamics Learning
Modern robotics is gravitating toward increasingly collaborative human robot
interaction. Tools such as acceleration policies can naturally support the
realization of reactive, adaptive, and compliant robots. These tools require us
to model the system dynamics accurately -- a difficult task. The fundamental
problem remains that simulation and reality diverge--we do not know how to
accurately change a robot's state. Thus, recent research on improving inverse
dynamics models has been focused on making use of machine learning techniques.
Traditional learning techniques train on the actual realized accelerations,
instead of the policy's desired accelerations, which is an indirect data
source. Here we show how an additional training signal -- measured at the
desired accelerations -- can be derived from a feedback control signal. This
effectively creates a second data source for learning inverse dynamics models.
Furthermore, we show how both the traditional and this new data source, can be
used to train task-specific models of the inverse dynamics, when used
independently or combined. We analyze the use of both data sources in
simulation and demonstrate its effectiveness on a real-world robotic platform.
We show that our system incrementally improves the learned inverse dynamics
model, and when using both data sources combined converges more consistently
and faster.Comment: IROS 201
Control strategies for integration of electric motor assist and functional electrical stimulation in paraplegic cycling: Utility for exercise testing and mobile cycling
AIM: The aim of this study was to investigate feedback
control strategies for integration of electric motor assist and functional electrical stimulation (FES) for paraplegic cycling, with particular focus on development of a testbed for exercise testing in FES cycling, in which both cycling cadence and workrate are simultaneously well controlled and contemporary physiological measures of exercise performance derived. A second aim was
to investigate the possible benefits of the approach for mobile, recreational cycling.
METHODS: A recumbent tricycle with an auxiliary electric motor is used, which is adapted for paraplegic users, and instrumented for stimulation control. We propose a novel integrated control strategy which simultaneously provides feedback control of leg power output (via automatic adjustment of stimulation intensity) and cycling cadence (via electric motor control). Both loops are
designed using system identification and analytical (model-based) feedback design methods. Ventilatory and pulmonary gas exchange response profiles are derived using a portable system for real-time breath-by-breath acquisition.
RESULTS:We provide indicative results from one paraplegic subject in which a series of feedback-control tests illustrate accurate control of cycling cadence, leg power control, and external disturbance rejection. We also provide physiological response profiles from a submaximal exercise step test and a maximal incremental exercise test, as facilitated by the control strategy.
CONCLUSION: The integrated control strategy is effective in facilitating
exercise testing under conditions of well-controlled cadence
and power output. Our control approach significantly extends the
achievable workrate range and enhances exercise-test sensitivity
for FES cycling, thus allowing a more stringent characterization
of physiological response profiles and estimation of key parameters
of aerobic function.We further conclude that the control approach
can significantly improve the overall performance of mobile recreational
cycling
Permanent Magnet Synchronous Motors are Globally Asymptotically Stabilizable with PI Current Control
This note shows that the industry standard desired equilibrium for permanent
magnet synchronous motors (i.e., maximum torque per Ampere) can be globally
asymptotically stabilized with a PI control around the current errors, provided
some viscous friction (possibly small) is present in the rotor dynamics and the
proportional gain of the PI is suitably chosen. Instrumental to establish this
surprising result is the proof that the map from voltages to currents of the
incremental model of the motor satisfies some passivity properties. The
analysis relies on basic Lyapunov theory making the result available to a wide
audience
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