Control Theory and Technology

Journal Information
ISSN / EISSN : 2095-6983 / 2198-0942
Published by: Springer Nature (10.1007)
Total articles ≅ 295
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, Fengzhen Tang, Jun Chen,
Published: 26 November 2021
Control Theory and Technology, Volume 19, pp 455-464; https://doi.org/10.1007/s11768-021-00063-x

The publisher has not yet granted permission to display this abstract.
Published: 15 November 2021
Control Theory and Technology, Volume 19, pp 563-572; https://doi.org/10.1007/s11768-021-00066-8

Abstract:
In this paper, the problem of inverse quadratic optimal control over finite time-horizon for discrete-time linear systems is considered. Our goal is to recover the corresponding quadratic objective function using noisy observations. First, the identifiability of the model structure for the inverse optimal control problem is analyzed under relative degree assumption and we show the model structure is strictly globally identifiable. Next, we study the inverse optimal control problem whose initial state distribution and the observation noise distribution are unknown, yet the exact observations on the initial states are available. We formulate the problem as a risk minimization problem and approximate the problem using empirical average. It is further shown that the solution to the approximated problem is statistically consistent under the assumption of relative degrees. We then study the case where the exact observations on the initial states are not available, yet the observation noises are known to be white Gaussian distributed and the distribution of the initial state is also Gaussian (with unknown mean and covariance). EM-algorithm is used to estimate the parameters in the objective function. The effectiveness of our results are demonstrated by numerical examples.
, Khaterah Kohneshin, Erik Aarnoutse, Mariska Vansteensel, Mariana Branco, Sacha Leinders, Max Van Den Boom, Elmar G. M. Pels, Nick Ramsey
Published: 12 November 2021
Control Theory and Technology, Volume 19, pp 444-454; https://doi.org/10.1007/s11768-021-00062-y

Abstract:
While brain computer interfaces (BCIs) offer the potential of allowing those suffering from loss of muscle control to once again fully engage with their environment by bypassing the affected motor system and decoding user intentions directly from brain activity, they are prone to errors. One possible avenue for BCI performance improvement is to detect when the BCI user perceives the BCI to have made an unintended action and thus take corrective actions. Error-related potentials (ErrPs) are neural correlates of error awareness and as such can provide an indication of when a BCI system is not performing according to the user’s intentions. Here, we investigate the brain signals of an implanted BCI user suffering from locked-in syndrome (LIS) due to late-stage ALS that prevents her from being able to speak or move but not from using her BCI at home on a daily basis to communicate, for the presence of error-related signals. We first establish the presence of an ErrP originating from the dorsolateral pre-frontal cortex (dLPFC) in response to errors made during a discrete feedback task that mimics the click-based spelling software she uses to communicate. Then, we show that this ErrP can also be elicited by cursor movement errors in a continuous BCI cursor control task. This work represents a first step toward detecting ErrPs during the daily home use of a communications BCI.
Published: 5 November 2021
Control Theory and Technology, Volume 19, pp 430-443; https://doi.org/10.1007/s11768-021-00060-0

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