Tracking a Diffusing Three-Dimensional Source via Nonholonomic Extremum Seeking

Ashley, Trevor T.; Andersson, Sean B.

doi:10.1109/tac.2017.2779876

Cited by 12 publications

(13 citation statements)

References 27 publications

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“…The controller in this case used a simplex method to measure the photon count rate, and used a gradient ascent to align the laser to the molecule automatically. More recently, an extremum-seeking controller was developed to converge to an orbit around a fixed fluorescent particle [115,20,116,117,21,118,119]. Through simulations and experiments, it was shown that this controller naturally switches between two distinct behaviors, converging to the desired orbital motion for slow moving particles and transitioning to a chasing behavior as the speed of the particle increases.…”

Section: Controller Architecturementioning

confidence: 99%

“…For further guidance on the convergence properties of the extremum-seeking approach and on selecting controller gains, see Refs. [118,120].…”

Section: Controller Architecturementioning

confidence: 99%

“…The maximum distance traveled within one time step is described by a probability distribution defined by the particular dynamics of the particle. Assuming the particle starts at the center of the detection volume at each step (perfect tracking), the notion of the first passage time to reach the edge of the detection volume sets an upper bound on the particle speeds that can be tracked [8,118]. This upper bound can be increased either by increasing the update rate or by increasing the detection volume.…”

Section: Control Challenges and Limitationsmentioning

confidence: 99%

“…The first is the work in [19], where the online estimates used for tracking were numerically unbiased after tracking had concluded to improve the overall localization accuracy. The second is in the signal maximization approach [21,118]. Because this approach reacts directly to the intensity, there is no need for online estimation; in addition, the pattern-less trajectory is ill-suited to many of the estimation approaches noted above.…”

Section: Estimationmentioning

confidence: 99%

“…The tracking probability directly relates to the mean duration of tracking. A second approach uses the mean escape time [26,118]. This is the time at which the particle first exits the detection volume.…”

Section: Fundamental Performance and Trade-offsmentioning

confidence: 99%

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Real-Time Feedback-Driven Single-Particle Tracking: A Survey and Perspective

van Heerden,

Vickers,

Krüger

et al. 2021

Preprint

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Real-time feedback-driven single-particle tracking (RT-FD-SPT) is a class of techniques in the field of singleparticle tracking that uses feedback control to keep a particle of interest in a detection volume. These methods provide high spatiotemporal resolution on particle dynamics and allow for concurrent spectroscopic measurements. This review article begins with a survey of existing techniques and of applications where RT-FD-SPT has played an important role. We then systematically discuss each of the core components of RT-FD-SPT in order to develop an understanding of the trade-offs that must be made in algorithm design and to create a clear picture of the important differences, advantages, and drawbacks of existing approaches. These components are feedback tracking and control, ranging from simple proportional-integral-derivative control to advanced nonlinear techniques, estimation to determine particle location from the measured data, including both online and offline algorithms, and techniques for calibrating and characterizing different RT-FD-SPT methods. We then introduce a collection of metrics for RT-FD-SPT to help guide experimentalists in selecting a method for their particular application and to help reveal where there are gaps in the techniques that represent opportunities for further development. Finally, we conclude with a discussion on future perspectives in the field.

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Section: Controller Architecturementioning

confidence: 99%

“…For further guidance on the convergence properties of the extremum-seeking approach and on selecting controller gains, see Refs. [118,120].…”

Section: Controller Architecturementioning

confidence: 99%

Section: Control Challenges and Limitationsmentioning

confidence: 99%

Section: Estimationmentioning

confidence: 99%

Section: Fundamental Performance and Trade-offsmentioning

confidence: 99%

See 3 more Smart Citations

Real-Time Feedback-Driven Single-Particle Tracking: A Survey and Perspective

van Heerden,

Vickers,

Krüger

et al. 2021

Preprint

Self Cite

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Real‐Time Feedback‐Driven Single‐Particle Tracking: A Survey and Perspective

Heerden

Vickers

Krüger

et al. 2022

Small

Self Cite

View full text Add to dashboard Cite

Real‐time feedback‐driven single‐particle tracking (RT‐FD‐SPT) is a class of techniques in the field of single‐particle tracking that uses feedback control to keep a particle of interest in a detection volume. These methods provide high spatiotemporal resolution on particle dynamics and allow for concurrent spectroscopic measurements. This review article begins with a survey of existing techniques and of applications where RT‐FD‐SPT has played an important role. Each of the core components of RT‐FD‐SPT are systematically discussed in order to develop an understanding of the trade‐offs that must be made in algorithm design and to create a clear picture of the important differences, advantages, and drawbacks of existing approaches. These components are feedback tracking and control, ranging from simple proportional‐integral‐derivative control to advanced nonlinear techniques, estimation to determine particle location from the measured data, including both online and offline algorithms, and techniques for calibrating and characterizing different RT‐FD‐SPT methods. Then a collection of metrics for RT‐FD‐SPT is introduced to help guide experimentalists in selecting a method for their particular application and to help reveal where there are gaps in the techniques that represent opportunities for further development. Finally, this review is concluded with a discussion on future perspectives in the field.

show abstract