Integrated electrical and heating systems (IEHSs) are promising for increasing the flexibility of power systems by exploiting the heat energy storage of pipelines. With the recent development of advanced communication technology, distributed optimization is employed in the coordination of IEHSs to meet the practical requirement of information privacy between different system operators. Existing studies on distributed optimization algorithms for IEHSs have seldom addressed packet loss during the process of information exchange. In this paper, a distributed paradigm is proposed for coordinating the operation of an IEHS considering communication packet loss. The relaxed alternating direction method of multipliers (R-ADMM) is derived by applying Peaceman-Rachford splitting to the Lagrangian dual of the primal problem. The proposed method is tested using several test systems in a lossy communication and transmission environment. Simulation results indicate the effectiveness and robustness of the proposed R-ADMM algorithm.
The real-time measurement of the projectile attitude is the key to realize the whole process guidance of the projectile. Due to the high dynamic characteristics of the projectile motion, the attitude measurement is affected by the real-time and accuracy of the gyro signal de-noising. For the nonlinear discontinuity of the conventional extension method in real-time wavelet de-noising, a function extension real-time wavelet de-noising method is proposed in this paper. In this method, a prediction model of gyro signal is established based on the Roggla formula. According to the model, the signal is fitted in the sliding window, and the signal of the same length is predicted to realize the right boundary extension. The simulation and experiment results show that compared with the traditional extension method, the proposed method can in-crease the signal-to-noise ratio (SNR) and the smoothness, and can decrease the attitude mean absolute error (AMAE) and the attitude root mean square error (ARMSE). Moreover, the time delay caused by signal de-noising can be effectively solved. The real-time performance of the attitude measurement can be ensured.
In a highly dynamic environment, a Micro Electro Mechanical Systems (MEMS) gyroscope becomes inaccurate after being calibrated using the traditional calibration methods. In this paper, a high-order calibration method for MEMS gyroscopes is proposed. The effects of a highly dynamic environment on gyroscope outputs are analyzed, and a high-order calibration model of the gyroscope is established according to a nonlinear relationship between the measured value and the real value of the gyroscope. An improved generalized recursive least squares (IGRLSs) algorithm is developed to solve the high-order calibration model, and an adaptive forgetting factor is introduced to correct the algorithm update capability. Compared with traditional gyroscope calibration methods, the proposed method solves the problem of data saturation and colored noise, and provides an unbiased and consistent parameter estimation. The results of calibration experiments show that the gyroscope calibration precision of the x-axis (roll axis) and the z-axis (yaw axis) are effectively increased by more than 58.30% and 19.14%, respectively.
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