Fuzzy fault tolerant control for smart lights

Abstract

This paper investigates the implementation of adaptive and nonadaptive controls for a smart lights experimental testbed. The objective is to accurately regulate the light level across the experimental testbed to a desired value, and to test the performance of the controllers under cross-illumination effects and bulb and sensor failures. As an initial approach, a decentralized (i.e., no communication between controllers) nonadaptive is implemented and applied to the smart lights. This approach is convenient for this type of experimental testbed where a mathematical model of the plant is not available and heuristic information about how to control the system is sufficient. The nonadaptive controller, when properly tuned, is able to achieve uniform lighting across the entire testbed floor in most of the tested situations but it fails whenever an on/off light bulb failure is introduced. In order to attain uniform lighting in the presence of failures, a fuzzy model reference learning controller (i.e., adaptive controller) is implemented for the smart lights, and this algorithm proves to be able to successfully adapt to uncertainties such as disturbances and failures.