Identification of intermittent control in man and machine

Abstract

Regulation by negative feedback is fundamental to engineering and biological processes. Biological regulation is usually explained using continuous feedback models from both classical and modern control theory. An alternative control paradigm, intermittent control, has also been suggested as a model for biological control systems, particularly those involving the central nervous system. However, at present, there is no identification method explicitly formulated to distinguish intermittent from continuous control; here, we present such a method. The identification experiment uses a special paired-step set-point sequence. The corresponding data analysis use a conventional ARMA model to relate a theoretically derived equivalent set-point to control signal; the novelty lies in sequentially and iteratively adjusting the timing of the steps of this equivalent set-point to optimize the linear time-invariant fit. The method was verified using realistic simulation data and was found to robustly distinguish not only between continuous and intermittent control but also between event-driven intermittent and clock-driven intermittent control. When applied to human pursuit tracking, event-driven intermittent control was identified, with an intermittent interval of 260 -310 ms (n ¼ 6, p , 0.05). This new identification method is applicable for machine and biological applications.

Semidiscretization for Time-Delayed Neural Balance Control

“…Indeed, for certain balancing tasks, intermittent control works better than continuous control [46]. These observations have prompted many investigators to develop mathematical models which emphasize a role for event-and clock-driven intermittent control strategies [1,5,9,10,11,12,13,24,25,31,47,48]. Here we consider the possibility that the neural feedback lies somewhere between these two extremes.…”

Intermittent control of unstable multivariate systems with uncertain system parameters

“…Recent theoretical and methodological advances have provided new experimental evidence that while human sustained tracking masquerades as continuous control, humans actually uses sensory feedback intermittently to sequentially update intervals of open loop predictive control [2,5,6]. An attribute of open loop predictive control of unstable systems, is that control is sensitive to inaccurate model values of physical system parameters.…”

Refractoriness in Sustained Visuo-Manual Control: Is the Refractory Duration Intrinsic or Does It Depend on External System Properties?

“…Recently [36], a novel approach to discriminating continuous control from intermittent control and identifying the extent of refractoriness, was developed and tested on theoretical control models and on data of human pursuit tracking (discrete stimuli-response task where control is known to be refractory). As discussed in Section 2.2 of [36], the relation between stimulus and response is modelled as a linear time-invariant (LTI) system together with a varying stimulus delay; an optimization algorithm determines the LTI system together with a stimulus delay for each stimulus which best matches the data.…”

“…As discussed in Section 2.2 of [36], the relation between stimulus and response is modelled as a linear time-invariant (LTI) system together with a varying stimulus delay; an optimization algorithm determines the LTI system together with a stimulus delay for each stimulus which best matches the data. The statistical properties of the estimated stimulus delays are then used to distinguish the competing continuous and intermittent hypotheses and, in the latter case, determine an estimate for the refractory duration (i.e.…”