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Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

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Fully probabilistic control design in an adaptive critic framework.

Randa Herzallah¹, Miroslav Kárný

¹Faculty of Engineering Technology, Al-Balsa Applied University, Jordan. herzallah.r@gmail.com

Neural Networks : the Official Journal of the International Neural Network Society

|July 15, 2011

Summary

This summary is machine-generated.

This study introduces a new fully probabilistic control algorithm to overcome computational challenges in optimal stochastic control. By employing adaptive critic methods, it avoids complex calculations, making advanced control theory more accessible.

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Area of Science:

Control Theory
Computational Mathematics
Artificial Intelligence

Background:

Optimal stochastic control aims to align closed-loop system behavior with desired performance.
Fully Probabilistic Design (FPD) minimizes Kullback-Leibler divergence for probabilistic control.
Existing FPD methods face computational hurdles due to complex multivariate integration and interpolation.

Purpose of the Study:

To develop a novel fully probabilistic control algorithm that reduces computational complexity.
To circumvent the need for explicit evaluation of the optimal value function in FPD.
To enhance the practical applicability of fully probabilistic design control theory.

Main Methods:

The proposed algorithm utilizes adaptive critic methods.
It avoids the computationally intensive numerical solution of stochastic dynamic programming.
Focuses on reducing the burden of multivariate integration and function approximation.

Main Results:

The new algorithm significantly reduces computational requirements for fully probabilistic control.
It offers a more computationally tractable approach to optimal stochastic control problems.
Demonstrates the effectiveness of adaptive critic methods in addressing FPD's computational bottlenecks.

Conclusions:

The developed fully probabilistic control algorithm offers a computationally efficient alternative.
This advancement facilitates the practical implementation of FPD control theory.
Adaptive critic methods provide a viable solution to the computational challenges in stochastic dynamic programming.