The natural neuromuscular model has greatly inspired the development of control mechanisms in addressing the uncertainty challenges in robotic systems. Although the underpinning neural reaction of posture control remains unknown, recent studies suggest that muscle activation driven by the nervous system plays a key role in human postural responses to environmental disturbance. Given that the human calf is mainly formed by two muscles, this paper presents an integrated calf control model with the two comprising components representing the activations of the two calf muscles. The contributions of each component towards the artificial control of the calf are determined by their weights, which are carefully designed to simulate the natural biological calf. The proposed calf modelling has also been applied to robotic ankle exoskeleton control. The proposed work was validated and evaluated by both biological and engineering simulation approaches, and the experimental results revealed that the proposed model successfully performed over 92% of the muscle activation naturally made by human participants, and the actions led by the simulated ankle exoskeleton wearers were overall consistent with that by the natural biological response.INDEX TERMS Muscle stretch reflex, calf muscle activation, standing control, exoskeleton control.

Robotic exoskeletons have emerged as effective rehabilitation and ability-enhancement tools, by mimicking or supporting natural body movements. The control schemes of exoskeletons are conventionally developed based on fixed torque-ankle state relationship or various human models, which are often lack of flexibility and adaptability to accurately address personalized movement assistance needs. This paper presents an adaptive control strategy for personalized robotic ankle exoskeleton in an effort to address this limitation. The adaptation was implemented by applying the experience-based fuzzy rule interpolation approach with the support of a muscle-tendon complex model. In particular, this control system is initialized based on the most common requirements of a ''standard human model,'' which is then evolved during its performance by effectively using the feedback collected from the wearer to support different body shapes and assistance needs. The experimental results based on different human models with various support demands demonstrate the power of the proposed control system in improving the adaptability, and thus applicability, of robotic ankle exoskeletons.INDEX TERMS Robotic ankle exoskeleton, muscle-tendon complex model, adaptive fuzzy rule interpolation, rehabilitation support.

Power electronics-based apparatuses absorb non-sinusoidal currents. These are considered non-linear and non-symmetrical loads for the power grid, and they generate a harmonic current. The dynamic tuning passive filter (DTPF) is one of the best solutions for improving power quality and filtering out harmonic currents to get a symmetrical current waveform. The electrical parameters of DTPF can influence its absorbing harmonic current, tuning performance, and cost. In this paper, a method for designing and optimizing the electrical parameters of dynamic tuning passive filter is proposed in order to improve the effectiveness of DTPF and the symmetry level of the power source. First, according to the characteristics of the harmonic source, the design technical indicators of DTPF, and its topology, the design procedure for the electrical parameters of DTPF is proposed. Second, based on detailed analysis of the test results, the range of the harmonic current absorption coefficient is determined. Third, the range of the relationship coefficient is determined by analyzing the impact of the filter capacitor’s capacity on the filter performance. Fourth, the calculation method for the electrical parameters of DTPF is devised. Finally, the validity of this method is verified by several engineering cases, and the electrical parameters of the filter capacitor and electromagnetic coupling reactance converter (ECRC) under the lowest total cost are simulated and optimized. Our approach can optimize the electrical parameters of DTPF and improve the harmonic suppression effectiveness, thus leading to a more symmetrical waveform and successfully avoiding power grid problems. The research results of this study not only provide a basis for the design of ECRC, but also lay a foundation for the machining DTPF.

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Focusing on the starting problems of a high-voltage and high-power motor, such as large starting current, low power factor, waste of resources, and lack of harmonic control, this paper proposes a current-limiting soft starting method for a high-voltage and high-power motor. The method integrates functions like autotransformer voltage reduction–current limiting starting, magnetron voltage regulation–current limiting starting, and reactive power compensation during starting, and then the power filtering subsystem is turned on to filter out harmonics in power system as the starting process terminates. According to the current-limiting starting characteristic curve, the topological structure of the integrated device is established and then the functional logic switching strategy is put forward. Afterwards, the mechanisms of current-limiting starting, reactive compensation and dynamic harmonic filtering are analyzed, and the simulation and experimental evaluation are completed. In particular, the direct starting and the current-limiting are performed by developing a simulation system. In addition, a 10 kV/19,000 kW fan-loaded motor of a steel plant is chosen as the subject to verify the performance of the current-limiting soft starting method. As shown by the experimental results, the motor’s starting current is about 2 times that of its rated current, the power factor is raised to over 0.9 after the reactive power compensation, and the harmonic filter can effectively eliminate current harmonics and reduce the total harmonic distortion (THD) of supply currents.