XXXX-XXXX/XXXX/XX(XX)/X-页 数 Chinese Physics and IOP Publishing Ltd Parameters Estimation On–line for Lorenz System by A Novel Quantum–behaved Particle Swarm Optimization∗

To estimate the unknown parameters of chaos system on–line is of vital importance in chaos control and syn-chronization, but the traditional methods ’ validity is not satisfactory. In this paper, a novel quantum–behaved particle swarm optimization(NQPSO) was proposed to parameters estimation by transforming them into nonlinear functions’ optimization. With the techniques to NQPSO in two aspects: contracting the searching space self–adaptively and boundaries restriction strategy, a more effective search mechanism with fine equilibrium between exploitation and ex-ploration will be achieved. Details of applying the put method and other methods into Lorenz systems ’ unknown parameters with noises are given, and experiments done show that NQPSO has better adaptability, dependability and robustness. And it is a successful approach in parameter estimation on–line for chaos system