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The thermal stress imbalance is a challenge for the reliability and in-service lifetime of modular multilevel converters, especially in traction drive applications. The finite control set model predictive control (FCS-MPC) can offer an effective solution to this issue, but it is faced with two difficulties, that is the weight allocation of electrical and thermal variables with different natures in control objectives functions, and dynamic weighting factor adjustment during the switching of variable operations. Therefore, an electro-thermal performance-based FCS-MPC (ETP-FCS-MPC) for dynamic thermal balance control is proposed, which can not only achieve thermal stress balance in converters with more intuitive and time saving ways, but also offer dynamic compromise schemes between the electrical and thermal performance of converters in the speed switching process. First of all, dynamic electrical and thermal models of converters are presented. Then, the absolute error-based electrical control objective and the energy loss variance-based thermal control objective are designed. Moreover, a performance-based normalized control objective function and an outer loop control feedback-based dynamic weighting factor are proposed. Finally, HIL-based test is carried out to verify the effectiveness of the proposed method, the test results show the merits of the proposed method.

This paper proposes a pressure-type generator that collects human mechanical energy by stepping, a prototype is finally designed and manufactured. The proposed pressure-type generator has a volume of 82.8 c m 3 when subjected to pressure. The average output power can reach to 97 mW when under the walking speed of 4 km/h. As a result we can get the power density of 1.17 m W / c m 3 , higher than most electromagnetically powered devices. Unlike some other generators, this pressure-type generator uses magnets as the recovery device, making the durability of the device better. And also, the wearable design is completely made to let the device can be comfortable used. Finally, we did a series of tests to prove that the device can have great power output performance in the low frequency environment of the human foot movement.

This paper presents the design, implementation, and characterization of a hardware platform applicable to a self-powered wireless sensor network (WSN) node. Its primary design objective is to devise a hybrid energy harvesting system to extend the operational lifetime of WSN node after they are deployed in the field environment. Besides the implementation of optimal components (microcontroller, sensor, radio frequency (RF) transceiver, and others) to achieve the lowest power consumption, it is also necessary to consider the sources of energy instead of the frequent recharging or replacement of batteries. Therefore, the platform incorporates a multisource energy harvesting module to collect energy from the surrounding environment, including wind, solar radiation, and thermal energy. The platform also includes an energy storage module through a super-capacitor, RF transceiver module, and the primary microcontroller module. Experimental results showed that the WSN node system with appropriate integration will reserve sufficient energy and meet the long-term power supply requirements of the WSN node without batteries in the field environment. The experimental results and empirical measurements taken over nine days demonstrated that the average daily generating capacity was 7805.09 J, which is far more than the energy consumption of the WSN node (about 2972.88 J).

We proposed a novel Raman distributed temperature sensor (RDTS) based on intensity-modulated pulse compression technique. The spatial resolution and temperature resolution are 1.6 m and 1.8 °C at a range of 24 km.

On one hand, aiming at the prominent problem of improving the reliability of Faster-than-Nyquist (FTN) wireless transmission, abandoning the channel estimation, we propose the Radial Basis Function Least Squares Support Vector Machine (RBF LSSVM) algorithm based on Intelligent Signal Processing for FTN equalization and form FTN time domain transverse filter equalizer. The model of FTN wireless communication system based on equalization of LSSVM algorithm is established by adding 50-bit training sample sequence module. On the other hand, in the FTN transmission BPSK modulation system receiving terminal, we propose joint research equalization of LSSVM algorithm and adaptive channel decoding scheme of Chase algorithm, to improve the reliable transmission performance of FTN wireless communication. The threshold value is 20, and the adaptive 2-D Turbo Product Codes (TPC) encoding and decoding is simulated by four iterations. The BER performance of FTN wireless communication combined with LSSVM algorithm and TPC adaptive decoding is simulated.

This paper studies a kind of sliding mode fault tolerant control method which used in aircraft engine sensor failure occurs. Firstly, reconstruct the fault signal of the fault sensor by using state observer. Secondly, design the sliding mode controller which can realize the processing for sensor fault, and proving the asymptotic stability of the system based on the Lyapunov stability theory. Finally, prove the aero-engine control system based on sliding mode has a certain fault tolerance capability through the simulation. In order to verify the effect of the fault tolerance by sliding mode controller, also introduced the PID controller and the H ∞ controller in the same fault signal to fault tolerant control, results are compared to illustrate that the sliding mode fault tolerant controller could improve the flight performance in the sensor fault cases.