Control of Interacting Level Process Under Sensor Failure Conditions using Coactive Adaptive Neuro-Fuzzy Observer

This paper presents the design of Coactive Adaptive Neuro-Fuzzy Observer based sensor fault detection and fault tolerant control under sensor failure conditions for a three-tank interacting level process. Fault detection is performed by estimating the states of the level process and comparing them with measured values. A fault is signaled when the difference between the estimated and measured values crosses a threshold value. Three pairs of observers estimate the three system states. These Observers are designed with Coactive Adaptive Neuro-Fuzzy Inference System (CANFIS) that uses a neural network to fix optimal shape and parameters for the membership functions and effective rule base for the fuzzy system. Decision functions are built from estimation errors to detect the fault. If any failure is identified, the control law is modified accordingly using the estimated value replacing the failed sensor output. In this work, CANFIS observer based fault detection is designed and simulated. The individual failures of three level sensors are considered and the results are discussed. The results show that the system is able to detect any sensor failure and to control the level in interacting tanks perfectly under failure situations.