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To solve the problem of low equalization or discharge efficiency, and improve the poor equalization effect due to large dispersion of individual batteries in the discharge process of redundancy equalization, a pre-equalization strategy of redundancy equalization based on K-means clustering analysis was proposed in this paper. According to this strategy, the battery pack can be divided into three classes, that is, high power type, medium power type, and low power type, which are then used as the foundation to achieve the charge and discharge between implementation classes based on Buck - Boost circuit. Compared with the traditional maximum-power battery which discharges to the minimum-power one, this strategy uses a type of battery as the balance standard, improves the balance of the efficiency of the pre-balanced adjustment battery discrete degree. At the same time, appropriate limitation is applied to the number of access to the battery to reduce the size of the equilibrium current, thereby reducing the power consumption. The simulation results of MATLAB/Simulink show that, under the condition of small battery quantity and large discrete degree of individual battery, the pre-equalization speed following clustering strategy is 4 times higher than that of traditional pre-equalization, which greatly improves the efficiency of pre-equalization, and shows certain practical value.

Purpose The purpose of this paper is to provide a novel training-responding controlling approach for human–robot interaction. The approach is inspired by the processes of muscle memory and conditioned reflex. The approach is significant for dealing with the problems of robot’s redundant movements and operator’s fatigue in human–robot interaction system. Design/methodology/approach This paper presented a directional double clustering algorithm (DDCA) to achieve the training process. The DDCA ensured that the initial clustering centers uniformly distributed in every desired cluster. A minimal resource allocation network was used to construct a memory responding algorithm (MRA). When the human–robot interaction system needed to carry out a task for more than one time, the desired movements of the robot were given by the MRA without repeated training. Experimentally demonstrated results showed the proposed training-responding controlling approach could successfully accomplish human–robot interaction tasks. Findings The training-responding controlling approach improved the robustness and reliability of the human–robot interaction system, which presented a novel controlling method for the operator. Practical implications This approach has significant commercial applications, as a means of controlling for human–robot interaction could serve to point to the desired target and arrive at the appointed positions in industrial and household environment. Originality/value This work presented a novel training-responding human-robot controlling method. The human-robot controlling method dealt with the problems of robot’s redundant movements and operator’s fatigue. To the authors’ knowledge, the working processes of muscle memory and conditioned reflex have not been reported to apply to human-robot controlling.

With the integration of new technologies such as smart technologies and cloud computing in the industrial Internet of Things, the complexity of industrial IoT applications is increasing. Real-time performance and determinism are becoming serious challenges for system implementation in these Internet of Things systems, especially in critical security areas. This paper provides a framework for a software-defined bus-based intelligent robot system and designs scheduling algorithms to make TTEthernet play the role of scheduling in the framework. Through the framework, the non-real-time and uncertainties problem of distributed robotic systems can be solved. Moreover, a fragment strategy was proposed to solve the problem of large delay caused by Rate-Constrained traffic. Experimental results indicate that the improved scheme based on fragmentation strategy proposed in this paper can improve the real-time performance of RC traffic to a certain extent. Besides, this paper made a performance test and comparison experiments of the improved scheme in the simulation software to verify the feasibility of the improved scheme. The result showed that the delay of Rate-Constrained traffic was reduced and the utilization rate of network was improved.