High-level Tuning Research Articles

Musculoskeletal geometry accounts for apparent extrinsic representation of paw position in dorsal spinocerebellar tract.

Proprioception, the sense of limb position and motion, arises from individual muscle receptors. An important question is how and where in the neuroaxis our high level "extrinsic" sense of limb movement originates. In the 1990s, a series of papers detailed the properties of neurons in the dorsal spinocerebellar tract (DSCT) of the cat. Despite their direct projections from sensory receptors, it appeared that half of these neurons had consistent, high-level tuning to paw position rather than to joint angles (or muscle lengths). These results suggested that many DSCT neurons compute paw position from lower level sensory information. We examined the contribution of musculoskeletal geometry to this apparent extrinsic representation by simulating a three-joint hindlimb with mono- and biarticular muscles, each providing a muscle spindlelike signal, modulated by the muscle length. We simulated neurons driven by randomly weighted combinations of these signals and moved the paw to different positions under two joint-covariance conditions similar to the original experiments. Our results paralleled those experiments in a number of respects: 1) Many neurons were tuned to paw position relative to the hip under both conditions. 2) The distribution of tuning was strongly bimodal, with most neurons driven by whole-leg flexion or extension. 3) The change in tuning between conditions clustered around zero (median absolute change ~20°). These results indicate that, at least for these constraint conditions, extrinsic-like representation can be achieved simply through musculoskeletal geometry and convergent muscle length inputs. Consequently, they suggest a reinterpretation of the earlier results may be required.NEW & NOTEWORTHY A classic experiment concluding that many dorsal spinocerebellar tract neurons encode paw position rather than joint angles has been cited by many studies as evidence for high-level computation occurring within a single synapse of the sensors. However, our study provides evidence that such a computation is not required to explain the results. Using simulation, we replicated many of the original results with purely random connectivity, suggesting that a reinterpretation of the classic experiment is needed.

Design and Tuning of Standard Additive Model Based Fuzzy PID Controllers for Multivariable Process Systems

This paper describes a design and two-level tuning method for fuzzy proportional-integral derivative (FPID) controllers for a multivariable process where the fuzzy inference uses the inference of standard additive model. The proposed method can be used for any n x n multi-input-multi-output process and guarantees closed-loop stability. In the two-level tuning scheme, the tuning follows two steps: low-level tuning followed by high-level tuning. The low-level tuning adjusts apparent linear gains, whereas the high-level tuning changes the nonlinearity in the normalized fuzzy output. In this paper, two types of FPID configurations are considered, and their performances are evaluated by using a real-time multizone temperature control problem having a 3 x 3 process system.

A 2DOF gain-scheduled controller design methodology for a multi-motor web transport system

In web transport systems, the main problem is to control the web velocity and tensions independently, to prevent web breaks, folding, or damage. Interesting results have been obtained using multi-variable control strategies. Unfortunately, most of the existing methodologies are either not systematic or deal with the tracking and disturbance rejection problems as a whole, and not separately. This paper presents a complete methodology in order to design two-degrees-of-freedom (2DOF) controller. The feedforward part is based on a reference model allowing operators to obtain the desired tracking performances (in particular, web tensions and velocity decoupling). The feedback part ensures robustness and disturbance rejection and is designed using two high-level tuning parameters only, thanks to the Standard State Control (SSC) methodology. However, the system dynamics change greatly during the winding/unwinding process due to the winder/unwinder radius and inertia variations. Therefore, a gain-scheduling controller is derived from the interpolation of consistent realizations of the H 2 controllers obtained at different points of the operating domain. The resulting controller is tested on a realistic simulator first, and after discretization, on a 3-motor web-handling experimental platform.

Advanced Resource Planning

Advanced Resources Planning hits the bottom of what we know as aggregate planning. This approach differs from other approaches in that it explicitly recognizes the stochastic nature of manufacturing systems. Therefore, it is an ideal high-level tuning and planning tool which can be used in various planning environments like MRP, ERP, JIT, Load-Oriented Planning, Theory of Constraints, Finite Scheduling, POLCA systems, and perhaps many more. The main purpose is to set aggregate planning parameters right before diving into any other operational planning decision. In this sense, we opt to offer realistic lead time estimations, lot sizes, utilization levels, customer service levels and quoted delivery times. The underlying approach is a waiting line network, which is heavily adapted in order to make it useful for planning purposes. The main feature is that both input parameters and output parameters are considered as stochastic variables. In this way it allows us to model manufacturing environments in a more realistic and intuitive way, including all kinds of uncertainty and variability. As a consequence, the output of the planning effort is also a stochastic variable: it has an average, a variance and the entire lead time distribution. The latter makes it possible to obtain high customer service levels or to establish realistic delivery times, which can be met with a high probability. This mathematical approach as such is not suited for people operating a manufacturing system. We illustrate the approach with software, named i-CLIPS, and we review some implementations and their results.

Two-level tuning of fuzzy PID controllers

Fuzzy PID tuning requires two stages of tuning; low level tuning followed by high level tuning. At the higher level, a nonlinear tuning is performed to determine the nonlinear characteristics of the fuzzy output. At the lower level, a linear tuning is performed to determine the linear characteristics of the fuzzy output for achieving overall performance of fuzzy control. First, different fuzzy systems are defined and then simplified for two-point control. Non-linearity tuning diagrams are constructed for fuzzy systems in order to perform high level tuning. The linear tuning parameters are deduced from the conventional PID tuning knowledge. Using the tuning diagrams, high level tuning heuristics are developed. Finally, different applications are demonstrated to show the validity of the proposed tuning method.

High-Level Psychophysical Tuning Curves

Simultaneous-masked psychophysical tuning curves were obtained from normal-hearing listeners using low-level (20-25 dB SPL) probe tones in quiet and high-level (60 dB SPL) probe tones, both in quiet and in the presence of a broad-band background noise. The background noise was introduced to eliminate combination tones or combination bands and other off-frequency listening cues that exist at high levels. Tuning curves were obtained using pure-tone maskers and 100-Hz-wide narrow-band noise maskers for probe tones at 1000 and 4000 Hz. High-level tuning curves for pure-tone maskers demonstrated large discontinuities or "notches" on the low-frequency sides of the tuning curves. Broad-band background noise eliminated those notches, indicating that the notches were due to the detection of off-frequency listening cues at combination-tone frequencies. High-level tuning curves for 100-Hz-wide narrow-band maskers also demonstrated notches on the low-frequency sides. Those notches were eliminated with broad-band background noise, which indicates that combination bands strongly influenced the shapes of high-level tuning curves obtained with narrow-band maskers. The influence of combination bands was dependent upon test frequency. At 1000 Hz, combination bands had very little influence on the shapes of high-level tuning curves. At 4000 Hz, where the masker bandwidth was substantially less than the critical bandwidth, combination bands strongly affected the low-frequency sides of the tuning curves. In 2 subjects tested at a probe frequency of 2000 Hz with 100-Hz-wide masking bands, combination bands also influenced the low-frequency sides of high-level tuning curves. The presence of combination-tone or combination-band cues essentially steepened the low-frequency slopes of tuning curves, resulting in sharper estimates of tuning. Comparisons of tuning curves obtained with pure-tone maskers and narrow-band maskers, in the same listeners, revealed that pure-tone maskers were more effective than narrow-band maskers when the masker frequencies were in the tail region of the tuning curve. The results of these experiments support the notion that tuning in the normal auditory system broadens notably with stimulus level, once off-frequency listening cues such as combination tones or combination bands are eliminated. The low-level simultaneously masked tuning curve demonstrates a sharp bandpass tuning characteristic, whereas the high-level simultaneously masked tuning curve in background noise demonstrates a broad low-pass tuning characteristic.(ABSTRACT TRUNCATED AT 400 WORDS)

High-Level Psychophysical Tuning Curves

Simultaneous-masked psychophysical tuning curves were measured with narrow-band noise maskers varying in bandwidth from 40 Hz to 800 Hz to determine the masker bandwidths at which combination-band detection cues no longer influence tuning-curve shapes. Tuning curves were obtained at 1000 and 4000 Hz from normal-hearing listeners using high-level (60 dB SPL) probe tones in quiet and in the presence of a broadband background noise to eliminate combination bands and other off-frequency listening cues that exist at high levels. High-level tuning curves revealed notches on the low-frequency sides. Those notches were eliminated with broad-band background noise, which indicates that combination bands can strongly influence the shapes of high-level tuning curves obtained with narrow-band maskers, primarily by steepening the low-frequency and tail slopes. Combination-band detection cues had a stronger influence at 4000 Hz than at 1000 Hz. As masker bandwidth increased, combination bands had less influence on tuning-curve shapes. These results suggest a possible relation between masker bandwidth and auditory critical bandwidth: combination bands affected the low-frequency sides of the tuning curves only when the masker bandwidth was less than the auditory critical bandwidth.