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This paper presents a novel wavelet kernel neural network (WKNN) with wavelet kernel function. It is applicable in online learning with adaptive parameters and is applied on parameters tuning of fractional-order PID (FOPID) controller, which could handle time delay problem of the complex control system. Combining the wavelet function and the kernel function, the wavelet kernel function is adopted and validated the availability for neural network. Compared to the conservative wavelet neural network, the most innovative character of the WKNN is its rapid convergence and high precision in parameters updating process. Furthermore, the integrated pressurized water reactor (IPWR) system is established by RELAP5, and a novel control strategy combining WKNN and fuzzy logic rule is proposed for shortening controlling time and utilizing the experiential knowledge sufficiently. Finally, experiment results verify that the control strategy and controller proposed have the practicability and reliability in actual complicated system. [ABSTRACT FROM AUTHOR]

For discrete system, the reaching law election and controller design are two crucial and important problems. In this paper, an improved double power reaching law of SMC and a controller combined with neural network have been investigated. Theory proves that this method can eliminate the chattering and increase the reaching rate. Furthermore, when there is a certain external interference, the regulating function of neural network can ensure strong robustness of the system. Simulation results show that compared with exponential reaching law, single power reaching law, and traditional double power reaching law, the proposed reaching law has faster convergence speed and better dynamic performance. [ABSTRACT FROM AUTHOR]

The moving mass actuation technique offers significant advantages over conventional aerodynamic control surfaces and reaction control systems, because the actuators are contained entirely within the airframe geometrical envelope. Modeling, control, and simulation ofMassMoment Aerospace Vehicles (MMAV) utilizing moving mass actuators are discussed. Dynamics of the MMAV are separated into two parts on the basis of the two time-scale separation theory: the dynamics of fast state and the dynamics of slow state. And then, in order to restrain the system chattering and keep the track performance of the system by considering aerodynamic parameter perturbation, the flight control system is designed for the two subsystems, respectively, utilizing fuzzy sliding mode control approach. The simulation results describe the effectiveness of the proposed autopilot design approach. Meanwhile, the chattering phenomenon that frequently appears in the conventional variable structure systems is also eliminated without deteriorating the system robustness. [ABSTRACT FROM AUTHOR]

For hybrid positioning systems (HPSs), the estimator design is a crucial and important problem. In this paper, a finite-elementmethod- (FEM-) based state estimation approach is proposed to HPS. As the weak solution of hybrid stochastic differential model is denoted by the Kolmogorov's forward equation, this paper constructs its interpolating point through the classical fourth-order Runge-Kuttamethod. Then, it approaches the solution with biquadratic interpolation function to obtain a prior probability density function of the state. A posterior probability density function is gained through Bayesian formula finally. In theory, the proposed scheme has more advantages in the performance of complexity and convergence for low-dimensional systems. By taking an illustrative example, numerical experiment results show that the new state estimator is feasible and has good performance than PF and UKF. [ABSTRACT FROM AUTHOR]