针对立方调频(Cubic Frequency Modulated,CFM)信号的参数估计问题,提出了一种基于高阶模糊函数(High order Ambiguity Function,HAF)和相参积累三阶自相关函数(Coherently Integrated Trilinear Autocorrelation Function,CITAF)的参数估计方法。利用HAF将立方相位信号降阶为二次调频(Quadratic Frequency Modulated,QFM)信号,再利用CITAF完成参数估计。由于CITAF能够在时域和时延域完成信号能量的二维相参积累,其实现过程利用复乘、傅里叶变换和加法操作即可完成,因此该方法能够提高参数估计的分辨率和抗噪声干扰能力,并保持较低的计算量。实验结果证实了该算法的有效性和性能上的优越性。 相似文献
In this study, a novel control strategy that combines a fuzzy system and the sliding mode controller is proposed for improving stability and achieving high-accuracy control in service robots. Based on the kinematic and dynamic models of a 4-degrees of freedom manipulator, and the observed tracking error using a low-cost inertial sensor, the proposed fuzzy sliding mode controller (FSMC(IMU)) is designed to generate appropriate torques at robot joints. The FSMC(IMU) controller parameters are adjusted through a fuzzy rule that determines the state of the system. The error in trajectory tracking is reduced through this. The gain value K can be finely adjusted by fuzzy control by observing the degree of vibration after entering the sliding mode surface. The larger the observed vibration value, the faster the fuzzy controller follows the given input trajectory by selecting a smaller gain value K and reducing jitter due to the sliding mode control’s discontinuous switch characteristics. When the degree of error is small, it achieves faster and more accurate control performance than when the observer is not used. The stability of the FSMC(IMU) system is verified via disturbance experiments. The experimental data are compared with the conventional sliding mode controller and proportional-derivative control. The experimental results demonstrate that the proposed FSMC(IMU) controller is stable, fast, and highly accurate in controlling service robots.