Aiming at the problem that it is difficult to establish an accurate mathematical model for a class of continuous stirred reactor(CSTR)due to its strong nonlinear and time variability,a new method for identification and modeling of Hammerstein-Wiener model based on multi-strategy improved Sparrow algorithm optimized Deep Extreme Learning Machine(OtSSA-DELM)is proposed.In view of the shortcomings of Sparrow algorithm like other swarm intelligence algorithms,such as low optimization accuracy in late optimization and easy to fall into local optimality,three improvement measures are proposed.Firstly,orthogonal array is used to initialize sparrow population,and then the Osprey optimization algorithm is used to replace the explorer position update formula of the original sparrow algorithm with the global exploration strategy in the first stage.Finally,the follower position update formula of the original Sparrow algorithm is replaced by T-mutation strategy,and its improved performance is verified by test function.The improved Sparrow algorithm is used to optimize the input weight and bias factor of the single-layer network in the training process of DELM network,which can solve the problem of DELM falling into local optimal.Finally,the identification experiment of Hammerstein-Wiener model is carried out by using this hybrid optimization algorithm.The experiment shows that the optimization of DELM by this hybrid optimization algorithm has higher identification accuracy than that of other swarm intelligent algorithms.
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