ON-Line Nonlinear Systems Identification of Coupled Tanks via Fractional Differential Neural Networks
fractional differential neural network (FDNN) is the extended neural network using fractional-order operators. On-line nonlinear system identification using FDNN is studied in this paper. Here all states of the non-linear system are assumed to be available in the system output. Through Lyapunov-like analysis, the fractional neural network parameters are adjusted so it will be proven that the identification error becomes bounded and tends to zero. To illustrate the applicability of the FDNN as a nonlinear identifier, two coupled tanks are considered as a case study. The results of simulation are very promising.
Fractional Differential Neural Networks (FDNNs) Nonlinear System identification State Estimation Coupled Tanks
Arefeh Boroomand Mohammad Bagher Menhaj
Electrical Engineering Department, Amirkabir University of Technology, Tehran, Iran 15914
国际会议
2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)
广西桂林
英文
2185-2189
2009-06-17（万方平台首次上网日期，不代表论文的发表时间）