Distributed Nonfragile Guaranteed Cost Filter Design for Nonlinear Systems With Sensor Networks

This paper addresses the distributed filter design issue of nonlinear systems in sensor networks. Furthermore, by considering the synthesized filter gain fluctuations, the nonfragile design scheme is developed to improve the implementation robustness and applicableness. Since the nonlinear system model is more practical and general to describe the real‐world dynamical systems, the nonlinear objective system measured by a sensor network grouped by sensor nodes is investigated. Moreover, in order to solve this theoretical filtering problem, the control theory and system theory are applied with control model transformation. More precisely, all the filters are supposed to be designed with the measurement of each sensor in the sensor network. Firstly, the distributed filtering problem is converted to the stability of filtering error system. Then, sufficient convex optimization conditions are accordingly established to ensure the desired H ∞ disturbance attenuation level with the desired guaranteed cost performance. Then, distributed filter gains can be derived by means of convex optimization method. Finally, the illustrative simulation of a nonlinear system with four sensor nodes is given to demonstrate the usefulness and correctness of our filter design.