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This paper presents a new approach to filter signals for discrete-time physical problems with stochastic uncertain in the presence of random data transmission delays, out-of-order packets and correlated noise. To deal with the packet disorder, the system model synthesizing the transmission delays and out-of-order packets from the plant to the filter is established by utilizing signal reconstruction schemes based on the zero-order-holder (ZOH) and logic ZOH. A robust finite horizon Kalman filter is proposed by augmenting the state-space model and minimizing the error covariance. To further improve the filtering performance, a linear estimation-based delay compensation strategy is proposed by employing the reorganized time-stamped measurements. Moreover, for solving the missing measurement problem whilst reducing the computational costs, an artificial delay compensation approach is established using an one-step prediction approach. Simulation results show the effectiveness of the proposed method.

The linear permanent-magnet synchronous generator (LPMSG) for direct-drive wave energy conversion (WEC) suffers from many drawbacks that have not yet been overcome, such as a low power density and a bulky system volume. Therefore, a magnetic field-modulated linear permanent-magnet generator (FMLPMG) with a simple structure has been designed and manufactured. First, the operating principle of the FMLPMG is demonstrated by the equivalent magnetic circuit method, which explains the high power density of the FMLPMG. Second, at a constant speed and a sinusoidal speed, the electromagnetic characteristics of the FMLPMG under the no-load and load conditions are analysed by the finite-element method. Finally, a direct-drive WEC test platform is built to simulate the process of wave action on the FMLPMG. No-load and load experiments of the FMLPMG are conducted on the test platform, and the results are compared with those of an LPMSG with the same volume and operating conditions. The results show that the FMLPMG with a high power density converts wave energy effectively and solves the problem of low power density faced by the LPMSG in direct-drive WEC.

The dynamic positioning system of unmanned underwater vehicles (UUVs) is a complex and large-scale system mainly due to the nonlinear dynamics, uncertainty in model parameters, and external disturbances. With the aid of the bio-inspired computing (BIC) method, the designed three-dimensional (3D) spatial positioning system is used for enlarging communication constraints and increasing signal coordination processing. With the growing of measurement scales, the issue of the networked high-precision positioning has been developed rapidly. Then, an information fusion estimation approach is presented for the distributed networked systems with data random transmission time delays and lost and disordered packets. To reduce the communication burden, an adaptive signal selection scheme is employed to reorganize the measurement sequence, and the parameter uncertainties as well as cross-correlated noise are used to describe the uncertain disturbances. Moreover, a reoptimal weighted fusion state estimation is designed to alleviate the information redundancy and maintain higher measurement accuracy. An illustrative example obtained from the 3D spatial positioning system is given to validate the effectiveness of the proposed method.

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