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Manipulators are often subjected to joint flexibility caused by various causes in industrial applications, such as shaft windup, harmonic drives and bearing deformation. However, many industrial robots are only equipped with motor-side encoders because link-side encoders and torque transducers are expensive. Because of joint flexibility and resulted slow response rate, control performance of these manipulators is very limited. Based on this, the purpose of this paper is to use easy-to-install and cheap accelerometers to improve control performance of such manipulators.

First, a novel tip-acceleration feedback method is proposed to avoid amplifications of approximation errors caused by inversion of the Jacobian matrix. Then, a new control scheme, consisting an artificial neural network, a proportional-derivative (PD) controller and a reference model, is proposed to track motor-side position and suppress link-side vibration.

By using the proposed tip-acceleration feedback method, each link’s vibration can be suppressed correlatively. Through the networks, smaller motor-side tracking errors can be obtained and unknown dynamics can be compensated. Tracking and convergence performance of the network-based system can be improved by using the additional PD controller.

The originality is based on using accelerometers to improve link-side vibration suppression and control performance of flexible-joint manipulators. The previously used methods need expensive link-side sensors or accurate robot model, which is unavailable for many industrial robots only equipped with motor-side encoders. The report proposed a novel acceleration feedback method and used networks to solve such problems.

This paper aims to present a method for improving the state estimation of a robot in the presence of noise measurement, which can improve the performance of the robot controller.

In this work, a novel nonlinear tracking differentiator (NTD) was formulated to solve the problems of phase lag, low stability and amplitude attenuation faced by traditional tracking differentiators, which can be used for the state estimation of a robot. Based on the user-defined function stu() with linear and nonlinear characteristics, the authors establish a new acceleration function of NTD and confirm its global asymptotic stability by using the Lyapunov method and the system equivalence method. Phase plane analysis shows that the origin is its stable nodal point or focus point and uncovers the basic constraint conditions for parameter regulation. In addition, the convergence property and robustness performance against noises are studied by describing function method.

Comparative simulations, robot state estimation experiments and joint trajectory tracking experiments have indicated that NTD proposed integrates tracking rapidness, accuracy and transitional stability and has high approximation and filtering effects on generalized derivatives of the signal, which contribute to an excellent performance of robot controller in stability and response speed in practice.

The main contribution of this paper lies in the design of a novel NTD, which successfully improves the state estimation of a robot joint in noisy surroundings, the tracking performance of robot controller and the stability of the system.

In the long-term network operation, the power distribution network will be subjected to the effects of ultra-high voltage, strong electromagnetic interference and harsh natural environment on the power system, which will lead to the occurrence of different faults in the distribution network and directly affect the normal operation of the power grid.

The purpose of this study is to solve the problems of labor intensity, high risk and low efficiency of distribution network manual maintenance operation, this paper proposed a new configuration of the live working robot for distribution network maintenance, the robot is equipped with dual working arms through the mobile platform, which can realize the coordination movement, the autonomous reorganization and replacement of the end tools, respectively, so as the robot power distribution maintenance function such as stripping, trimming, wiring and the operation control problem of the distribution network-robot with small arms and in small operation space can be realized.

To effective elimination or reduce the adverse effects of the internal forces in the closed chain between the working object and manipulator under the typical task of the 10 kV distribution network, this paper has established the robot coordinated control dynamics model in the closed-chain between the dual-working object and proposed the dynamic distribution method of closed-chain internal force and the effectiveness has been proved by simulation experiments and 10 kV field operation.

The force-position hybrid control can realize the mutual compensation of force and position so as to effectively reduce the internal force in the closed chain. Finally, the engineering practicality of the method is verified by field operation experiment, the effective implementation of this control method greatly improves the robot working efficiency and the operation reliability, the promotion and application of the control method have great theoretical and practical value and maintenance management system, so as to achieve automation of electric.

The purpose of this paper is to present a simple yet effective force control scheme for collaborative robots by addressing the problem of disturbance rejection in joint torque: inherent actuator flexibility and nonlinear friction.

In this paper, a joint torque controller with an extended state observer is used to decouple the joint actuators from the multi-rigid-body system of a constrained robot and compensate the motor friction. Moreover, to realize robot force control, the authors embed this controller into the impedance control framework.

Results have been given in simulations and experiments in which the proposed joint torque controller with an extended state observer can effectively estimate and compensate the total disturbance. The overall control framework is analytically proved to be stable, and further it is validated in experiments with a robot testbed.

With the proposed robot force controller, the robot is able to change its stiffness in real time and therefore take variable tasks without any accessories, such as the RCC or 6-DOF F/T sensor. In addition, programing by demonstration can be realized easily within the proposed framework, which makes the robot accessible to unprofessional users.

The main contribution of the presented work is the design of a model-free robot force controller with the ability to reject torque disturbances from robot-actuator coupling effect and motor friction, applicable for both constrained and unconstrained environments. Simulation and experiment results from a 7-DOF robot are given to show the effectiveness and robustness of the proposed controller.

This paper aims to reveal how different types of events and top management teams' (TMTs’) cognitive frames affect the generation of breakthrough innovations.

Drawing on the event system theory and upper echelon theory, this study chose a Chinese manufacturing enterprise as the case firm and conducted an exploratory single-case study to unpack how breakthrough innovation generates over time.

By conducting the in-depth case analysis, the study revealed that firms do not produce breakthrough innovation in the catch-up stage and parallel-running stage but achieve it in the leading stage. It also indicated that when facing proactive events in the catch-up stage, TMTs often adopt a contracted lens, being manifested as consistency orientation, less elastic organizational identity and narrower competitive boundaries. In addition, they tend to adopt a contracted lens when facing reactive and proactive events in the parallel-running stage. In the face of reactive and proactive events in the leading stage, they are more inclined to adopt an expanded lens, being manifested as a coexistence orientation, more elastic organizational identity and wider competitive boundaries.

First, by untangling how TMT's cognitive frame functions in breakthrough innovations, this paper provides a micro-foundation for producing breakthrough innovations and deepens the understanding of upper echelon theory by considering the cognitive dimension of TMTs. Second, by teasing out several typical events experienced by the firm, this paper is the first attempt to reveal how events affect the generation of breakthrough innovation. Third, the work extends the application of the event system theory in technological innovation. It also provides insightful implications for promoting breakthrough innovations by considering the role of proactive and reactive events a firm experiences and TMT's perceptions.

Drawing on the upper echelons theory, this study focuses on how top management team (TMT) heterogeneity affects breakthrough innovations and examines how strategic decision-making logic (including causation and effectuation) moderates the relationship between TMT heterogeneity and breakthrough innovation.

By conducting an empirical test of 227 sample firms in China, the authors applied linear hierarchical regression analysis to test the hypotheses on the TMT heterogeneityinnovation relationship and the moderating roles of causation and effectuation.

The empirical tests show that TMT heterogeneity positively affects breakthrough innovation, and both causation and effectuation positively moderate the positive relationship between TMT heterogeneity and breakthrough innovation. In addition, effectuation has a stronger moderating effect on the positive correlation between TMT heterogeneity and breakthrough innovation than causation.

This study extends the upper echelons theory to explain how the characteristics of TMTs affect firm innovation. Specifically, the authors explore the TMT heterogeneity–breakthrough innovation relationship from the perspectives of information processing and core competence and reveal the boundary condition of strategic decision-making logic in the correlation between TMT heterogeneity and breakthrough innovation. In this vein, the authors contribute to the literature by untangling the internal mechanisms between TMT heterogeneity and breakthrough innovation and extending the discussion on effectuation theory from the entrepreneurship domain to the innovation field. Furthermore, the research findings can provide helpful implications for TMTs to manage breakthrough innovation effectively.

This study explores how firms develop innovation ecosystems through forming alliances with suppliers and the effects on innovation, economics and consumer welfare.

This study develops two game theory models to compare supply chain structures with and without ecosystem alignment. (1) A single supplier provides components to two competing manufacturers (one innovative and one non-innovative). (2) An innovative manufacturer (focal firm) aligns with a supplier that also supplies components to a competing manufacturer.

An ecosystem construction strategy that alliances use to reconfigure coopetitive relationships and ecosystem alignment is identified. A manufacturer aligning with a supplier will strengthen the monopoly of the alignment, which is beneficial to both Allies but always harmful to the competitor. Interestingly, such an ecosystem construction strategy may be beneficial to future innovation, the industry and consumers.

The findings raise several topics that warrant further exploration. For example, scenarios with multiple suppliers were not considered. Furthermore, the implementation of regulatory measures to mitigate the harmful effects of alignment on innovation should be investigated.

This paper provides a guide for enterprises seeking alignment and to the corresponding measures required to stimulate innovation within ecosystems. What’s more, the aligned firm should not always attempt to win the race but should instead take measures to encourage the competitor to share demand information.

Firstly, most research on supply chain management has focused on its economic impacts. There is a lack of research on the influence of ecosystem alignment on the innovation incentives of firms. Furthermore, the literature still lacks evidence of how ecosystem construction strategies can increase consumer welfare. In the present study, the authors model a complex market structure that includes a competitor, which is becoming increasingly common in high-tech markets. Thirdly, this paper is one of the few that examines the impacts of market-structure changes on innovation incentives. Most importantly, this study extends the current literature by studying coopetition in the ecosystem context.

The coronavirus disease 2019 (COVID-19) pandemic caused significant disruption to the global labor market, resulting in a rapid transition toward remote work, e-commerce and workforce automation. This shift has sparked a considerable amount of public discussion. This study aims to explore the online public's sentiment toward remote work amid the pandemic.

Based on justice theory, this paper examines user-generated content on social media platforms, particularly Twitter, to gain insight into public opinion and discourse surrounding remote work during the COVID-19 pandemic. Employing content analysis techniques such as sentiment analysis, text clustering and evolutionary analysis, this study aims to identify prevalent topics, temporal patterns and instances of sentiment polarization in tweets.

Results show that people with positive opinions focus mainly on personal interests, while others focus on the interests of the company and society; people's subjectivities are higher when they express extremely negative or extremely positive emotions. Distributive justice and interactional justice are distinguishable with a high degree of differentiation in the cluster map.

Previous research has inadequately addressed public apprehensions about remote work during emergencies, particularly from a justice-based perspective. This study seeks to fill this gap by examining how justice theory can shed light on the public's views regarding corporate policy-making during emergencies. The results of this study provide valuable insights and guidance for managing public opinion during such events.

This study aims to enhance the understanding of fiber-reinforced polymer (FRP) applications in partially confined concrete, with a specific focus on improving economic value and load-bearing capacity. The research addresses the need for a more comprehensive analysis of non-uniform vertical strain responses and precise stress–strain models for FRP partially confined concrete.

DIC and strain gauges were employed to gather data during axial compression tests on FRP partially confined concrete specimens. Finite element analysis using ABAQUS was utilized to model partial confinement concrete with various constraint area ratios, ranging from 0 to 1. Experimental findings and simulation results were compared to refine and validate the stress–strain model.

The experimental results revealed that specimens exhibited strain responses characterized by either hardening or softening in both vertical and horizontal directions. The finite element analysis accurately reflected the relationship between surface constraint forces and axial strains in the x, y and z axes under different constraint area ratios. A proposed stress–strain model demonstrated high predictive accuracy for FRP partially confined concrete columns.

The stress–strain curves of partially confined concrete, based on Teng's foundation model for fully confined stress–strain behavior, exhibit a high level of predictive accuracy. These findings enhance the understanding of the mechanical behavior of partially confined concrete specimens, which is crucial for designing and assessing FRP confined concrete structures.

This research introduces innovative insights into the superior convenience and efficiency of partial wrapping strategies in the rehabilitation of beam-column joints, surpassing traditional full confinement methods. The study contributes methodological innovation by refining stress–strain models specifically for partially confined concrete, addressing the limitations of existing models. The combination of experimental and simulated assessments using DIC and FEM technologies provides robust empirical evidence, advancing the understanding and optimization of FRP-concrete structure performance. This work holds significance for the broader field of concrete structure reinforcement.

The purpose of this paper is to demonstrate a multipurpose inspection robot that can both walk on the ground and climb on poles. The structure design, size optimization, kinematics analysis, experiment and arithmetic of the robot are discussed in the paper.

The robot consists of three adjustable modules and a two-degree-of-freedom parallel mechanism in tandem, and the wheel-finger mechanism of each module can realize wheel-finger opening and closing for fast movement and obstacle crossing. This paper uses geometric analysis and simulation analysis to derive size optimization, and vector coordinate method to derive kinematics. Finally, the experiment is carried out by simulating the working environment of the robot.

The robot can realize ground walking and ground turning through the robot entity prototype experiment on the built working environment and efficiently realize 0°–90° pole climbing by the assemble design, optimization and machining. In addition, the robot can also smoothly complete the state transition process from 0° ground to 90° pole climbing. Furthermore, the robot shows good environmental self-adaptation and can complete daily inspection work.

The robot can pitch and yaw at a large angle and has six-legged characteristics. It is a multipurpose inspection robot that can walk on the ground and climb on poles. And through structure design, size optimization, kinematics analysis and simulation, the existing robots’ common shortcomings such as poor barrier-crossing ability and poor environmental adaptability are solved.