Li Aijun

Modeling of CVI process in fabrication of carbon/carbon composites by an artificial neural network

The chemical vapor infiltration (CVI) process in fabrication of carbon-carbon composites is very complex and highly inefficient, which adds considerably to the cost of fabrication and limits the application of the material. This paper tries to use a supervised artificial neural network(ANN) to model the nonlinear relationship between parameters of isothermal CVI(ICVI) processes and physical properties of C/C composites. A model for preprocessing dataset and selecting its topology is developed using the Levenberg-Marquardt training algorithm and trained with comprehensive dataset of tubal C/C components collected from experimental data and abundant simulated data obtained by the finite element method. A basic repository on the domain knowledge of CVI processes is established via sufficient data mining by the network. With the help of the repository stored in the trained network, not only the time-dependent effects of parameters in CVI processes but also their coupling effects can be analyzed and predicted. The results show that the ANN system is effective and successful for optimizing CVI processes in fabrication of C/C composites.

Design of mixed sensitivity H∞ control for four-rotor hover vehicle

During the past one decade, multirotor unmanned aerial vehicles (MUAVs)s control has become an active research area for flight control community. The reasons behind are the benefits offered by MUAV and its numerous commercial and consumer applications. In this paper, design of a robust attitude controller for four-rotor hover vehicle that is a kind of MUAV, based on H∞ mixed-sensitivity synthesis is presented. Firstly, a linear model of four-rotor hover vehicle is derived, which is formulated as a nominal plant perturbed by parameter and unstructured uncertainties. H∞ mixed-sensitivity controller is designed due to the uncertain nature of the system. The efficacy of the proposed controller is proved by simulations and experiment. Performance analysis, simulation, and experimental results show that the proposed controller guarantees stability, exhibits good performance, and robustness margins against the parameter and unstructured uncertainties.

Integral sliding mode controller design for near space vehicle with input constraints

Near space vehicle (NSV) is a nonlinear, multivariable and strongly coupled system. During the arbitrary trajectory tracking of NSV, the employment of conventional sliding mode variable structure control often results in steady-state errors, if there is some certain external disturbance. In this paper, an integral sliding mode variable structure controller is designed to eliminate the steady state error. Since the inputs of most actuators are restricted, the control performance will deteriorate or fail when the control signals are input directly into the controlled object. Therefore, the saturation limit is introduced to the controller design process to limit the input. Finally the proposed control scheme is applied to the attitude motion mode of the NSV and the simulation results confirmed its effect.

An adaptive sliding mode control based on radial basis function network for attitude tracking control of four rotor hover system

An adaptive sliding mode controller based on radial basis function network has been proposed to control the three degree-of-freedom four rotor hover system. Mathematical model of hover system is developed using equations of motions and radial basis function network is used to approximate the unmodeled dynamics of the system. Sliding mode controller based on adaptive law is designed to achieve chattering free, good attitude tracking control in the presence of modeling uncertainties. The stability of the proposed controller has been proved using the Lyapunov stability theory. Simulation results exhibit that the adaptive sliding mode controller in conjunction with radial basis function network achieves better control performance than the traditional PID, LQR controllers even without knowing the exact dynamical model.

Flying wing aircraft sliding mode LI adaptive reconfiguration flight control law design

Flying wing aircraft reconfiguration flight control law design method based on the LI adaptive control and sliding mode observer is proposed in this paper. In the condition of no failure information, the LI adaptation law and control law are used to reconfiguration actuator failures. For high gain question, low-pass filter is used to restrain the high frequency oscillation and eliminate the high frequency control signal. For LI adaptive reconfiguration control system, the asymptotical control stability is proved. In order to decrease the control error caused by reconfiguration error and airplane model uncertainty, the sliding mode observer is designed and used to generate the compensating signal. The simulation results show that the flying wing aircraft has good control performance in the condition of actuator surface failure.