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In order to realize precise position tracking of a novel circular hydraulic actuator with parameter uncertainties and bounded disturbances, an adaptive sliding mode controller (ASMC) that incorporates a fuzzy tuning technique is proposed in this paper. The mechanical structure and basic principle of the actuator are first introduced, and the mathematical model of its corresponding valve-controlled hydraulic servo system is constructed. Based on Lyapunov stability theory, online parameter estimation and sliding mode controller design are effectively integrated to approximate the equivalent control of sliding mode. To mitigate the undesired chattering phenomenon and further improve system performance, a fuzzy tuning scheme is employed to regulate the proportional gain of the approaching control term. In addition, a realtime control platform is established, and the controllers parameter identification and position tracking are verified by preliminary experiments. Finally, the traditional PID controller and the exponent approaching sliding controller are also conduced to further evaluate the control performances of the designed controller, and the comparative results demonstrate that the proposed control scheme has better control performance in reducing errors for trajectory tracking.INDEX TERMS Position tracking, circular hydraulic actuator, parameter uncertainties, adaptive sliding mode control, fuzzy tuning scheme.

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Purpose Periodic inspection of bridge cables is essential, and cable-climbing robots can replace human workers to perform risky tasks and improve inspection efficiency. However, cable inspection robots often fail to surmount large obstacles and cable clamps. The purpose of this paper is to develop a practical cable inspection robot with stronger obstacle-surmounting performance and circumferential rotation capability. Design/methodology/approa/ch A cable inspection robot with novel elastic suspension mechanisms and circumferential rotation mechanisms is designed and proposed in this study. The supporting force and spring deformation of the elastic suspension are investigated and calculated. Dynamic analysis of obstacle surmounting and circumferential rotation is performed. Experiments are conducted on vertical and inclined cables to test the obstacle-surmounting performance and cable-clamp passing of the robot. The practicality of the robot is then verified in field tests. Findings With its elastic suspension mechanisms, the cable inspection robot can carry a 12.4 kg payload and stably climb a vertical cable. The maximum heights of obstacles surmounted by the driving wheels and the passive wheels of the robot are 15 mm and 13 mm, respectively. Equipped with circumferential rotation mechanisms, the robot can flexibly rotate and successfully pass cable clamps. Originality/value The novel elastic suspension mechanism and circumferential rotation mechanism improve the performance of the cable inspection robot and solve the problem of surmounting obstacles and cable clamps. Application of the robot can promote the automation of bridge cable inspection.

This paper carried out a series of designs, simulations and implementations by using the physical-like mechanism of a bionic quadruped robot dog as a vehicle. Through an investigation of the walking mechanisms of quadrupeds, a bionic structure is proposed that is capable of omnidirectional movements and smooth motions. Furthermore, the kinematic and inverse kinematic solutions based on the DH method are explored to lay the foundation for the gait algorithm. Afterward, a classical compound pendulum equation is applied as the foot-end trajectory and inverse kinematic solutions are combined to complete the gait planning. With appropriate foot–ground contact modeling, MATLAB and ADAMS are used to simulate the dynamic behavior and the diagonal trot gait of the quadruped robot. Finally, the physical prototype is constructed, designed and debugged, and its performance is measured through real-world experiments. Results show that the quadruped robot is able to balance itself during trot motion, for both its pitch and roll attitude. The goal of this work is to provide an affordable yet comprehensive platform for novice researchers in the field to study the dynamics, contact modeling, gait planning and attitude control of quadruped robots.

Recent years have witnessed the rapid development of microelectromechanical systems, and human motion tracking technology based on IMU (inertial measurement unit) has attracted much attention. However, the magnetic field varies with time and position, which makes it necessary to calibrate sensors before tracking. To address the poor adaptability of IMU to the environments and improve the accuracy of estimated traces, this paper presents an ENN-based (Elman neural network) method to track human arm motions, which consists of two steps. First, the data derived from IMUs are preprocessed for the rough Euler angles; then, an ENN is trained to estimate motions. We explore the initially estimated position to calibrate the acceleration measurements as the input of the ENN. Real-world experiments of arm motion tracking are carried out with the ground truth from an optical motion tracking system. The experimental results show that the mean tracking errors are around 35 mm, with a strong ability to eliminate the effect of extreme measurement and environment noises, avoiding calibrating the magnetometer. The implementation of the well-trained model to independent motions indicates that the robustness of the proposed method is excellent, and the errors reduce by 37.2% on the x -axis and perform similarly on the z -axis compared with 4 traditional methods. This method quite suits those situations where trajectory tracking of the standardized motions is required, such as the medical habilitation.