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This study aims to establish a bio-inspired controller for realizing the bounding gait of a quadruped robot system presented in this paper.

The bio-inspired controller is divided into three levels to mimic the biological patterns of animals. First, the high-level sub-controller is equivalent to the cerebellum, which could plan and control the motion of animals. Second, the effect of the middle-level sub-controller corresponds to the central nervous system. The central pattern generators in the spine generate the stable and cyclic signals as the fundamental rhythm for periodic motion of the leg and spine joints. Third, the low-level sub-controller is equal to the end effector, which adopts the simple proportional-derivative (PD) control to realize the specific motion trajectory of the legs and spine.

Combined with the stability criterion presented previously and the delayed feedback control method, the bounding gait of the cheetah virtual prototype could be actuated and stabilized by the bio-inspired controller. Moreover, the bio-inspired controller is applied to realize the bounding gait of an SQBot, which is a quadruped robot with a spine joint. Meanwhile, the validity and practicability of the bio-inspired controller for the control of quadruped robot have been verified against different forward velocities.

The bio-inspired controller and bionic quadruped robot system are instructive for the designing and actuating of the real quadruped robot.

The purpose of this paper is to provide a safe control strategy for aloft hot-line assembly of connection fittings in 110kV intelligent substations, which is significant to research on hot-line working robots.

This paper addresses challenges of the task and establish the contact models of connection fittings. By using this control strategy, neither high precision vision positioning nor preset global reference coordinate system is required. Visual computing only needs to provide an approximately position for the manipulator end-effector, after which the connection fittings assembly task could be completed with the posture of the manipulator adjusted following the guidance by force-position control. The authors also analyze the influence of the intervention of manipulators on the very non-uniform electric field during the operation.

This strategy will be particularly useful for the hot-line assembly of connection fittings in 110kV intelligent substations as well as some assembly tasks where uncertain target position and complex contact surface such as cylindrical hole is involved.

This assembly strategy is tested in energized simulated experimental system. The experiment results show that the robot can replace the manual operation to complete the assembly task safely and efficiently.

This assembly strategy is able to achieve the assembly task of connection fittings. Unlike other peg-in-hole assembly strategy, it does not require high stability of manipulator or plane contact surface around the hole.

The purpose of this paper is to present a dual manipulator system for aloft hot-line assembly tasks of connection fittings in 110-kv intelligent substation, which is significant to the research on hot-line working robots.

This paper addresses the challenges of the task and presents a dual manipulator system which can overcome these challenges to realize the robotic assembly of connection fittings in narrow space without impacting the safe distance of both phase to phase and phase to ground. Two manipulators share a same global reference coordinate. The mission of Manipulator 1 is to position the fixed part of connection fittings and screw the bolts on it. Visual computing provides the approximately position for the end-effector of Manipulator 2, after which The Manipulator 2 carries the removable part of connection fittings to this position. Then, the assembly task could be completed with the posture of the Manipulator 2 adjusted following the guidance by force-position control.

The dual manipulator system can position the target under different illumination conditions and complete fast assembly of connect fittings in 110-kV substation. No strong arc discharge or surface erosion phenomenon has been observed.

This dual manipulator system will be particularly useful for the hot-line assembly of connection fittings in 110-kv intelligent substation, as well as some assembly tasks where uncertain target position and complex contact surface such as cylindrical hole is involved.

This study presents a dual manipulator system used by a field robot working in 110-kv intelligent substation. The system is able to achieve the connection fittings assembly task under energized simulation experimental system. Unlike other peg-in-hole assembly strategy, it does not require high stability of manipulator or plane contact surface around the hole.

The magnetometer measurement update plays a key role in correcting yaw estimation in fusion algorithms, and hence, the yaw estimation is vulnerable to magnetic disturbances. The purpose of this study is to improve the ability of the fusion algorithm to deal with magnetic disturbances.

In this paper, an adaptive measurement equation based on vehicle status is derived, which can constrain the yaw estimation from drifting when vehicle is running straight. Using this new measurement, a Kalman filter-based fusion algorithm is constructed, and its performance is evaluated experimentally.

The experiments results demonstrate that the new measurement update works as an effective supplement to the magnetometer measurement update in the present of magnetic disturbances, and the proposed fusion algorithm has better yaw estimation accuracy than the conventional algorithm.

The paper proposes a new adaptive measurement equation for yaw estimation based on vehicle status. And, using this measurement, the fusion algorithm can not only reduce the weight of disturbed sensor measurement but also utilize the character of vehicle running to deal with magnetic disturbances. This strategy can also be used in other orientation estimation fields.

The purpose of this paper is to examine the relationship between a number of variables pertaining to core capability, competitive strategy and performance of construction small to medium size enterprises (SMEs) in China.

The paper consists of a quantitative survey. It involves mainly the development of instrument and testing of the hypotheses.

Core capability and competitive strategy are found to influence construction SMEs' performance. Moreover, there are positive relationships between core capability and competitive strategy. This suggests a need to align core capability and competitive strategy as a precondition for superior performance.

The paper has limitations as a result of data collection. A somewhat larger sample would obviously permit firmer conclusions to be drawn from the results of the statistical analysis.

This paper will contribute to the literature on SMEs, strategic management and resource‐based theory. This integration of scope is particularly new to the context of the Chinese construction industry. Similarly, this research will have implications for practice. The research findings help SMEs' managers to understand the impact of the unique resources of their enterprises and competitive strategy.

Traditional algorithms require at least two complete vector observations to estimate orientation parameters. However, sensor faults and disturbances may cause some components of vector observations unavailable. This paper aims to propose algorithms to realize orientation estimation using vector observations with one or two components lost.

The fundamental of the proposed method is using norm equation and dot product equation to estimate the lost components, then, using an improved TRIAD to calculate attitude matrix. Specific algorithms for one and two lost components cases are constructed respectively, and the nonuniqueness of orientation estimation is analyzed from a geometric point of view. At last, experiments are performed to test the proposed algorithms.

The loss of components results in the loss of orientation information. The introduction of the norm equation and dot product equation can partially compensate for the loss of information. Experiment results and analysis show that the proposed algorithms can provide effective orientation estimation, and in vast majority of applications, the proposed algorithms can provide a unique solution in one lost component case and double solutions in two lost components case.

The proposed method addresses the problem of orientation estimation when one or two components of vector observations are unavailable. The introduction of the norm equation and dot product equation makes the calculation cost low, while the analyses from a geometric point of view makes the study of nonuniqueness more intuitive.

The sources of magnetic sensors errors are numerous, such as currents around, soft magnetic and hard magnetic materials and so on. The traditional methods mainly use explicit error models, and it is difficult to include all interference factors. This paper aims to present an implicit error model and studies its high-precision training method.

A multi-level extreme learning machine based on reverse tuning (MR-ELM) is presented to compensate for magnetic compass measurement errors by increasing the depth of the network. To ensure the real-time performance of the algorithm, the network structure is fixed to two ELM levels, and the maximum number of levels and neurons will not be continuously increased. The parameters of MR-ELM are further modified by reverse tuning to ensure network accuracy. Because the parameters of the network have been basically determined by least squares, the number of iterations is far less than that in the traditional BP neural network, and the real-time can still be guaranteed.

The results show that the training time of the MR-ELM is 19.65 s, which is about four times that of the fixed extreme learning algorithm, but training accuracy and generalization performance of the error model are better. The heading error is reduced from the pre-compensation ±2.5° to ±0.125°, and the root mean square error is 0.055°, which is about 0.46 times that of the fixed extreme learning algorithm.

MR-ELM is presented to compensate for magnetic compass measurement errors by increasing the depth of the network. In this case, the multi-level ELM network parameters are further modified by reverse tuning to ensure network accuracy. Because the parameters of the network have been basically determined by least squares, the number of iterations is far less than that in the traditional BP neural network, and the real-time training can still be guaranteed. The revised manuscript improved the ELM algorithm itself (referred to as MR-ELM) and bring new ideas to the peers in the magnetic compass error compensation field.

The aim of this paper is reviewing the discipline development course of the history of socialist political economy with Chinese characteristics and recognising the changes of its development and its historic mission in the new stage will be beneficial to the construction of socialist political economy with Chinese characteristics from the perspective of doctrinal history.

In this paper from the aspect of discipline formation and development, the history of China’s socialist political economy has experienced two stages: emergence and formation (the first stage) and steady development (the second stage). It has explored new research fields and improved the quality of research levels. However, the role of studying the history of socialist political economy with Chinese characteristics has not been fully played regarding satisfying the needs of constructing socialist political economy with Chinese characteristics.

In this study when the construction of socialist political economy with Chinese characteristics entered a new era, the study of the history of socialist political economy also entered a new stage, showing new features in terms of research objectives, principles, scale and methods.

Therefore, the research on the history of socialist political economy with Chinese characteristics should be highly emphasised, and the focus on serving the construction of socialist political economy with Chinese characteristics should be its historic mission and core task. Also, researchers should pay attention to changing ideas, laying a good foundation, highlighting key points, building platforms and broadening horizons.

The purpose of this study is to meta-analytically compare the effect of differentiation strategy formulation on financial and non-financial performance to explore the agency problem.

This study was conducted using a meta-analysis approach and CMA2 software. Hypotheses has been tested using cumulative effect sizes. Then, the cumulative effect sizes if some subsamples are also tested for robustness check by manipulation of circumstances.

Based on the findings, differentiation affects performance dimensions. However, spite of shareholders’ wealth maximization, differentiation has a smaller effect on financial performance (as the proxy of shareholders’ wealth) compared with operational performance. Meanwhile, the robustness test showed that the results in all subcategories has also confirmed, and this supports the results.

The results catch attentions of shareholders to review the elements of management evaluation in the corporate governance system in a way that they focus more on stakeholders’ interests in developing differentiation strategy. Limitations of this study is firstly based on limitations of meta-analysis approach, which provide general results of relevant studies so that the local conditions of each firm should be considered in deploying implications.

Exploring the overall schema of firms (from past to present and in different research conditions) regarding the impact of differentiation strategy on performance has been the originality of this research because of potentials of meta-analysis against past field studies. This originality led to the discovery of the general confusion of firms in the development of differentiation strategy so that it emphasizes operational performance more than financial performance.