Unmanned Aerial Vehicle Ad-hoc Network (UANET) are gaining extensive attention in fire monitoring, communication relay and other fields. Because of mobility of UAVs, network topology changes frequently. In OLSR routing protocol, each node broadcasts HELLO packets at regular intervals for link sensing and neighborhood detection. However, if the HELLO interval is too small when the node speed is slow, unnecessary traffic will appear in the network. If the HELLO interval is too large when the node speed is fast, the performance will be degraded too. This paper proposes a routing protocol that adaptively adjusts the HELLO interval. Large amount of simulation results of NS-3 is used as samples, the neural network is trained by GA-BP (Genetic Algorithm, Back Propagation) algorithm, and the chosen network performance metrics under different HELLO intervals are predicted according to the speed of nodes. The MADM (Multiple Attribute Decision Making) method is used to comprehensively evaluate these metrics and select the optimal HELLO interval. Our simulation results show that compared with the original OLSR and other schemes, the proposed scheme can achieve a large performance improvement at a very small cost.
In order to compensate for the disadvantages of the large computational scale and high requirements for chip arithmetic of the traditional extended Kalman filter, reduce the computational volume of the extended Kalman filter, improve the stability of the motor controller, and reduce the dependence of the algorithm on chip arithmetic while ensuring the control accuracy. An extended Kalman filter motor control system based on weighted average fusion is designed. A weighted average fusion extended Kalman filter without position sensor control algorithm is also designed, which can complete the control of the motor with significantly reduced arithmetic load on the main controller chip, and the algorithm has high robustness and high anti-interference capability. Finally, the effectiveness and feasibility of this motor control system is further verified by simulink simulation analysis and physical platform experiments.
KEYWORDS: Source mask optimization, Optical fiber cables, Control systems, Control systems design, Switching, Linear filtering, Distributed interactive simulations, Tunable filters, Switches, Signal attenuation
This article presents a sensor-less control strategy of Surface Permanent Magnet Synchronous Motor (SPMSM) in full speed operations. To realize closed-loop control of currents and velocity in middle-to-high speed, a Sliding Mode Observer (SMO) is designed to estimate the rotor position and velocity which is provide for Field-Oriented Control (FOC). To suppress the high frequency chattering induced by signum function, an improved SMO based on saturation function control law is adopted. Because the SMO based on back-electromotive force to extract rotor position failed to start up SPMSM and inaccurate to estimate rotor position and speed in zero-to-low range, a startup strategy based on mechanical rotor alignment and I/F scheme is proposed. After the rotate velocity is high enough, the system transitions to the sensor-less FOC based on improved SMO. The designed control system is simulated using MATLAB/Simulink. The simulation results demonstrate that the system can realize the speed regulation of SPMSM in full speed domain, and the improved SMO has high precision of estimation, strong robustness and small chattering in medium-to-high speed operations.
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