This paper presents a novel and efficient method to realize both structure and parameter identification
in a multivariable system with hybrid particle swarm optimization(PSO) algorithm and the sequential quadratic
programming(SQP) algorithm. The conbination of classic mathematical models constitute a system model, so the problem
of system structure identification is transformed into a problem of combinatorial optimization. Then by using hybrid PSO
algorithm and the SQP algorithm, both structure and parameter identification of the system are realized at the same time.
In order to further illustrate the effectiveness of the algorithm, the proposed method is compared with the standard PSO
algorithm and the dynamical inertia weight of PSO algorithm. The simulation results show that the proposed hybrid algorithm
is reasonable, effective, and has high precision and practicability.