Robustness analysis of discrete predictor-based controllers for input-delay systems

In this article, robustness to model uncertainties are analysed in the context of discrete predictor-based state-feedback controllers for discrete-time input-delay systems with time-varying delay, in an LMI framework. The goal is comparing robustness of predictor-based strategies with respect to other (sub)optimal state feedback ones. A numerical example illustrates that improvements in tolerance to modelling errors can be achieved by using the predictor framework.The authors are grateful for grant nos. DPI2008-06737-C02-01, DPI2008-06731-C02-01, DPI2011-27845-C02-01 and PROMETEO/2008/088 from the Spanish and Valencian governments.González Sorribes, A.; Sala, A.; García Gil, PJ.; Albertos Pérez, P. (2013). Robustness analysis of discrete predictor-based controllers for input-delay systems. International Journal of Systems Science. 44(2):232-239. https://doi.org/10.1080/00207721.2011.600469S232239442Boukas, E.-K. (2006). 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State-dependent distributed-delay model of orthogonal cutting

In this paper we present a model of turning operations with state-dependent distributed time delay. We apply the theory of regenerative machine tool chat- ter and describe the dynamics of the tool-workpiece sys- tem during cutting by delay-diferential equations. We model the cutting-force as the resultant of a force sys- tem distributed along the rake face of the tool, which results in a short distributed delay in the governing equation superimposed on the large regenerative de- lay. According to the literature on stress distribution along the rake face, the length of the chip-tool inter- face, where the distributed cutting-force system is act- ing, is function of the chip thickness, which depends on the vibrations of the tool-workpiece system due to the regenerative efect. Therefore, the additional short de- lay is state-dependent. It is shown that involving state- dependent delay in the model does not afect linear sta- bility properties, but does afect the nonlinear dynamics of the cutting process. Namely, the sense of the Hopf bi- furcation along the stability boundaries may turn from sub- to supercritical at certain spindle speed regions

Sensory uncertainty and stick balancing at the fingertip

The effects of sensory input uncertainty, ε , on the stability of time-delayed human motor control are investigated by calculating the minimum stick length, ℓcrit , that can be stabilized in the inverted position for a given time delay, τ . Five control strategies often discussed in the context of human motor control are examined: three time-invariant controllers [proportional–derivative, proportional–derivative–acceleration (PDA), model predictive (MP) controllers] and two time-varying controllers [act-and-wait (AAW) and intermittent predictive controllers]. The uncertainties of the sensory input are modeled as a multiplicative term in the system output. Estimates based on the variability of neural spike trains and neural population responses suggest that ε≈7 –13 %. It is found that for this range of uncertainty, a tapped delay-line type of MP controller is the most robust controller. In particular, this controller can stabilize inverted sticks of the length balanced by expert stick balancers (0.25–0.5 m when τ≈0.08 s). However, a PDA controller becomes more effective when ε>15% . A comparison between ℓcrit for human stick balancing at the fingertip and balancing on the rubberized surface of a table tennis racket suggest that friction likely plays a role in balance control. Measurements of ℓcrit,τ , and a variability of the fluctuations in the vertical displacement angle, an estimate of ε , may make it possible to study the changes in control strategy as motor skill develops