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Robust Design of a Control System Instrumentation Using Structural Analysis and ANFIS Neuro-Fuzzy Logic Approaches
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This paper focuses on the robust design of control system instrumentation; it proposes a design approach for determining the best hardware architecture of a control system. This method is based on Structural Analysis which consists of selecting the most relevant input variables of the system, and constructs the model Adaptive Network Fuzzy Inference System ANFIS for modelling the system that is used to quantify the dependability constraints according to Quality of Performance QoP based on the uncertainties measures from the sensors, and actuators implemented in the design phase of the control system. In this work, the speed control system vt+δt of an electrical vehicle is used as an illustrative example. A method to optimize the instrumentation is presented; it uses financial cost and dependability as criteria.
Keywords:Design of a Control System Instrumentation, Structural Analysis, Quality of Performance, ANFIS Model
Author: Zine-eddine Meguetta1, Blaise Conrard1, Mireille Bayart1
1.LAGIS UMR CNRS 8219, University of LILLE 1, Avenue Paul Langevin, Villeneuve D’Ascq, 59650, France
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