Retractable worm robots possess hyper-flexibility, allowing them to work in confined spaces that are difficult for humans. However, the spatial locomotion control of these robots remains challenging due to the robots’ large degrees of freedom. To address this challenge, we propose a phase synthesis (PS) scheme for retractable worm robots. The scheme combines an undulating gait inspired by caterpillars with three-dimensional movement commands. We first introduce the kinematics model and real-world prototype of our retractable worm robot, called RW-Robot, and then we introduce footstep phases to express the timing of segments’ spatial movement. According to the length of movement periods, we classify the movement into short-term movements and long-term movements and compress their patterns in the frequency domain. Our PS scheme aligns the patterns according to the footstep phases to generate new gaits of spatial locomotion. We evaluate the scheme in real-world experiments, including steering and climbing a slope. The experimental results indicate that our scheme allows the RW-Robot to perform flexible spatial locomotion from simple user input.

An air supply strategy based on a centrifugal compressor with turbocharging for Unmanned Aerial Vehicle (UAV) fuel cells is proposed in this paper. The turbocharging is used to recover the energy of the exhausted gas from the fuel cell cathode. The mathematical model of the system is established and analyzed. And the air supply control method is proposed to satisfy the requirement of the fuel cell stack. The validation of the proposed strategy is verified by simulation. The simulation results show that the proposed strategy improves the efficiency of the fuel cell system by 7.8%.

A Hybrid Model Predictive Current Control(H-MPC) for Permanent-Magnet Synchronous Motor(PMSM) is proposed in this paper. It incorporates the advantages of feedback Enhanced Model Predictive Control (E-MPC) and Multi-Step MPC based on Linear Extended State Observer (LESO-MPC), which results in rapid dynamic performance and a low steady-state error. E-MPC is utilized for dynamic processes to improve dynamic performance. LESO-MPC is utilized for steady-state processes to reduce steady-state errors and improve robustness. In addition, an adaptive switching method based on a sliding window is proposed to maintain a smooth transition between LESO-MPC and E-MPC. Simulation results verify the effectiveness of the H-MPC over the typical MPC.

The prognostic of proton exchange membrane fuel cells (PEMFCs) degradation and the estimation of its remaining useful life (RUL) are effective ways to improve the reliability of the target system and reduce maintenance costs, which is of great significance for the wide commercialization of PEMFCs. Many factors cause the degradation of PEMFCs, and these factors are often difficult to measure accurately. The prognostic method based on long short-term memory networks (LSTMs) has better memory ability for time series and has been demonstrated able to describe the degradation trend of PEMFCs. However, the traditional LSTM prediction algorithm seems to easily fall into the local optimal solution in long-term prediction cases. Overfitting like errors may result in an imprecise or even unstable prognostic. This paper proposes a novel method, named navigation sequence driven LSTMs (NSD-LSTMs), to enhance the accuracy of PEMFCs degradation trend prediction. Two types of PEMFCs aging test data under different load conditions were used to verify the performance of NSD-LSTMs. Experimental results show that, compared with traditional LSTMs, NSD-LSTMs can improve the accuracy of trend prediction. Accurate degradation prognostic can be used to predict RUL and provide guidance for the commercial application of PEMFCs.

During transient process, it may take plenty of steps for PMSM to reach the reference torque and flux linkage. Multistep model predictive torque and flux control (MPTC) can select the best sequence of voltage vectors from the initial state to the reference state to achieve the fastest torque response. However, the computation burden is a significant challenge for real-time implementation. This paper proposes a novel fast-response MPTC strategy for PMSM drives. The reference torque is converted to flux linkage in d-axis and q-axis to eliminate the weighting factor in cost function. During the transient process, Pontryagin's maximum principle is used to design minimum-time flux linkage trajectories from the initial state to the reference state. In each control period, along the reference flux linkage trajectories, one-step MPTC is used to select the best voltage vector. The computational burden and dynamic performance of the proposed method are verified by experiments.

This paper presents hardware-in-the-loop (HIL) validation of an air supply method for the fuel cell in automotive applications. A 12 kW proton exchange membrane fuel cell (PEMFC) model is developed and implemented in dSPACE. The performances of the fuel cell stack and compressor during a classic European Driving Cycle are tested. The experimental results show that the compressor consumes up to 25 % of the fuel cell generated power in the worst operating point, whereas only 4.2 % on average.