Three-Term Fault Diagnostic Algorithm for Optimized Incubator Control System
Publication Date : 01/04/2019
Given the increasing need to optimize production time of incubators, a number of approaches have been used to develop incubator control system but none of these methods used fault diagnostic and tolerant algorithms integrated within Proportional-Integral-Derivative (PID) control algorithm. Besides, most of the existing fault diagnostic and tolerant algorithms were not developed with remote based applications in mind. This work developed and integrated a fault diagnostic and tolerant algorithm with remote reporting capability into the Existing PID Algorithm (EPIDA). Behavioral models of the priority components were used to develop an Intelligent Algorithm (IA) on embedded c language, a hybrid of c and c++ languages while arduino uno was used as a target controller for the developed IA. Validation of the IA for Fault Diagnosis and Tolerant Control (IAFDTC) was done using the EPIDA and the IAFDTC to control the process plant under the absence and presence of simulated fault. With 99.05% accuracy as the minimum benchmark, EPIDA had accuracy of 99.78% under normal conditions and dropped to 96.95% in the presence of simulated fault confirming that the EPIDA was not originally designed to diagnose and tolerate faults. However, the IAFDTC had accuracy of 99.96% under normal operation and 99.62% accuracy under the influence of fault. In addition, it sends remote reports via wireless network to control system custodians. This shows that IAFDTC achieved an improvement of 2.67% in the accuracy of the existing algorithm while maintaining the system’s availability and integrity under the influence of fault condition.
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