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Showing 1 to 6 of 6 for “"Neural Controller"”.

  1. Adaptive neural controller based on convex parametrization

    … of nonlinear plants has been addressed by using neural networks together with sliding mode control to lead to global boundedness. We revisit this problem in this thesis and suggest a specific class of neural networks that employ convex activation functions. By using the algorithms that have been …

    mit Repository record for Adaptive neural controller based on convex parametrization (opens in a new tab)

  2. Development and evaluation of postural control models for lifting motions and balance control

    … in this model, fuzzy logic was used to specify a neural controller which was generally considered as the part in the postural control system that plans human motions. Fuzzy rules were generated according to certain trends observed from actual human motions. An optimization procedure was performed …

    vt Repository record for Development and evaluation of postural control models for lifting motions and balance control (opens in a new tab)

  3. Suppression of limit cycle oscillations in an aeroelastic system using robust and adaptive control

    … stable; Secondly, an adaptive and a neural controller is designed with structural nonlinearity using leading- and trailing-edge control surfaces. (Abstract shortened by UMI.).

    unlv Repository record for Suppression of limit cycle oscillations in an aeroelastic system using robust and adaptive control (opens in a new tab)

  4. Muscle activation mapping of skeletal hand motion: an evolutionary approach.

    … by borrowing principles from biomechanics and neural con- trol. A generic physics engine compliant muscle model primitive is also de- veloped. The muscle model primitive forms the motion actuator and is an integral part of the physical model used in the simulation. This thesis investigates a …

    bournemouth Repository record for Muscle activation mapping of skeletal hand motion: an evolutionary approach. (opens in a new tab)

  5. Learning based algorithms for temperature control and fouling prediction in heat-exchangers

    … Designing robust and accurate temperature controllers for heat exchangers is very challenging primarily because of complexities associated with the synthesis of dynamics of industrial heat exchangers. It is practically infeasible to synthesize an accurate dynamical model of heat-exchanger's …

    uiuc Repository record for Learning based algorithms for temperature control and fouling prediction in heat-exchangers (opens in a new tab)