A set of parameters such as ionic radi i,electronegativity,base state L v alues,and periodic factors,defined in this work,were used to nonlinearly c orrelate hydrolysis constants p K1of the lanthanide and actinide met...A set of parameters such as ionic radi i,electronegativity,base state L v alues,and periodic factors,defined in this work,were used to nonlinearly c orrelate hydrolysis constants p K1of the lanthanide and actinide metal ions(Ln3?and An 3?￡(c)with the functional￡-link net￡¨FLN￡(c)￡(r)Training the functional￡-link net￡¨FLN￡(c)with a group mix stylebooks make up of 13Ln3? and 4An3?,10An 3?p K 1 were predicted by FLN￡(r)展开更多
The design of a turbofan rotor speed control system, using model reference adaptive control（MRAC） method with input and output measurements, is discussed for the purpose of practical application. The nonlinear compe...The design of a turbofan rotor speed control system, using model reference adaptive control（MRAC） method with input and output measurements, is discussed for the purpose of practical application. The nonlinear compensator based on functional link neural network is used to deal with the engine nonlinearity and the hardware-in-loop simulation is also developed. The results show that the nonlinear MRAC controller has the adequate performance of compensating and adapting nonlinearity arising from the change of engine state or working environment. Such feature demonstrates potential practical applications of MRAC for aeroengine control system.展开更多
文摘A set of parameters such as ionic radi i,electronegativity,base state L v alues,and periodic factors,defined in this work,were used to nonlinearly c orrelate hydrolysis constants p K1of the lanthanide and actinide metal ions(Ln3?and An 3?￡(c)with the functional￡-link net￡¨FLN￡(c)￡(r)Training the functional￡-link net￡¨FLN￡(c)with a group mix stylebooks make up of 13Ln3? and 4An3?,10An 3?p K 1 were predicted by FLN￡(r)
文摘The design of a turbofan rotor speed control system, using model reference adaptive control（MRAC） method with input and output measurements, is discussed for the purpose of practical application. The nonlinear compensator based on functional link neural network is used to deal with the engine nonlinearity and the hardware-in-loop simulation is also developed. The results show that the nonlinear MRAC controller has the adequate performance of compensating and adapting nonlinearity arising from the change of engine state or working environment. Such feature demonstrates potential practical applications of MRAC for aeroengine control system.
