Iteration-based parameter identification and its applications about distributed parameter systems

This paper addresses a general problem to parameter identification in distributed parameter systems (DPSs), as well as handles a secure communication issue by the extended identification method. First, an iterative approach is put forward based on the approximator and historical information. Meanwhile, an execution scheme for the iterative approach is provided by an optimization policy. Then, combined with the reference model and measurement data, an extended identification method is applied in secure communication. Subsequently, a quantum-leading-following-based optimization with mutation strategy (MQLFBO) algorithm is proposed as the optimization policy. Next, the global convergence and computational complexity are respectively discussed for MQLFBO algorithm in theory. Finally, simulation experiments are performed on parameter identification for DPSs and its application in secure communication, which verify the fast convergence and high precision of the developed method.