No abstract

As a complex system, control performance of small rotary-wing unmanned aircraft is easily affected by measurement errors and environment disturbances. This paper proposes a nonlinear disturbance observer-based control to improve control performance. The constant and harmonic disturbance that is generated by the exogenous system with modeling perturbation can be estimated and rejected effectively. The random disturbance with certain bound can be reduced by the feedback control. By solving linear matrix inequality, the parameters for feedback control and nonlinear disturbance observer can be selected simultaneously. Therefore, the system stability can be guaranteed and the control performance can be improved effectively. The effectiveness of the nonlinear disturbance observer-based control is proved by a series of flight tests. Compared with feedback control, the disturbance observer-based control yields a better tracking performance in the presence of disturbances.

To improve flight performance of small rotary-wing unmanned aircraft under complex environment, a composite control method based on internal model control (IMC) and adaptive radial basis neural network (RBFNN) is proposed. With the analysis of the characteristics of system disturbance, an IMC system is constructed to eliminate system errors. Furthermore, an adaptive RBFNN without prior training is proposed to eliminate residual estimation errors to augment the control performance. The effectiveness of the composite control method is validated by a series of flight tests. Compared with the feedback control method, the composite control method can yield good tracking performance under wind disturbances.

A CAN/LIN bus-based distributed vehicle electronic control system is designed and nodes of the control system are defined in this paper. The simulation of system designed is completed by Vector CANoe, which gives the results of bus load, peak load and the delayed time that transmitted on CAN bus. The sequence of message scheduling and the interval of message transmitted on LIN bus are also listed to show the reliability of CAN/LIN bus-based distributed vehicle electronic control system.

The main contents of this dissertation are the application of swarm intelligence to multi-unmanned vehicle system and the realization of cooperative control of multi-unmanned vehicle system. Firstly, this thesis introduces the research background and significance of multi-unmanned vehicle system and swarm intelligence. Secondly, we introduce the research contents of cooperative control of multi-unmanned vehicle system. Then the research status of cooperative control of multi-unmanned vehicle system in the domestic and overseas are introduced. Finally, this dissertation summarizes the mainstream types of architecture and algorithm of the multi-unmanned vehicle system.