Abstract Disk model is usually used to represent graphene nanoplatelets (GNPs) which are considered as frame‐like structure with edges and corners, and it has lack of quantitative accuracy. In order to minimize error caused by morphology, distribution, and interaction between GNPs and matrix, square and folded plate models were constructed to predict the percolation volume fraction ( ϕ c ) of GNPs‐based nanocomposites by calculating connection possibility. Meanwhile, disk model is used for comparison. The results revealed that the ϕ c of square and folded plate models is smaller than that of disk model with consistent parameters, and it is concluded that the ϕ c of GNPs‐based nanocomposites predicted by disk model should be higher than that of experimental. The correctness of mixed model of square and folded plate is also verified by experimental. Due to the agglomeration of GNPs under the actual situation, the result of simulation is slightly smaller than that of experiment.
Comparing to the big volume, large weight and high power consumption of the conventional samplers which are fixed on the lunar rover, the paper firstly described a novel flexible mini lunar sampling robot.Then the nonlinear dynamics resonance broken system is built to model the contact between the sampling robot and the lunar regolith.It is found to be suitable for drilling when the sampling robot is in the resonance condition.For the nonlinear time-varying system of the dynamic modeling of the sampler in drilling, we presented the method of the frequency neural-fuzzy adaptive control based on the dynamic resonant frequency prediction of the flexible sampling robot using neural networks.Firstly the algorithm predicts the dynamic resonant frequency of the sampling robot by GRNN.Then a neural-fuzzy adaptive control system is established, in which the frequency prediction error, the amplitude and its variable are adopted as the input and the sweep frequency bandwidth as the output, to adjust the frequency bandwidth dynamically.What's more, the simulation results verify the effectiveness of the control strategy.Finally, the experimental results show that the control algorithm can improve the drilling depth, drilling efficiency and the discarding efficiency by 66. 7%, 65.2% and 67.4%, respectively, in stimulant lunar regolith.
Telerobot system plays an important role in executing task under hazard environment. As the computer networks such as the Internet are being used as the communication channel of telerobot systems, varying time delay causes the overall system unstable and reduces the performance of transparency. In this paper, we propose twelve operation modes with different control schemes for telerobot on the Internet with time delay. And an optimal operation mode with control scheme is specified for telerobot with time delay, based on the tradeoff between passivity and transparency properties. We experimentally confirm the validity of the proposed optimal mode and control scheme by using a simple one DOF master–slave manipulator system.
The constrained command tracking problem for the cloud robotic system with unknown bounded time-varying delays is considered. Based on a novel predictor-observer approach, a command governor is proposed to modify the received command in order to guarantee the constraint enforcement of remote robot. We firstly use a prediction algorithm in the forward channel to generate a virtual command, which is close to the original one as much as possible when the danger of constraint violation exists. Then, to deal with the measurement delay and disturbance in the backward channel, interval estimations of the system states are applied instead of delayed measurements in the prediction algorithm of the command governor. The constraints can be rigorously enforced with the upper and lower estimations. The efficiency of the proposed approach is demonstrated by simulations in the case of a single-degree-of-freedom manipulator.
Multi-axis force/torque sensor is a key component for space robot force control and teleoperation. The special environment of space, however, brings huge challenges to the design of multi-axis force/torque sensor. In this paper, a six-axis force/torque sensor, which could be used as a component for the large manipulator in the space station, is developed. In order to obtain the large measurement range of force/torques, an elastic body based on cross-beam with anti-overloading capability is designed, and the size is optimized by using FEA to guarantee both high stiffness and sensitivity of the six-axis force/torque sensor. Different from the conventional method, the signal acquisition module which includes a high signal-to-noise ratio amplifier circuit is integrated in the sensor so as to be more reliable. Then, a novel calibration system is designed to provide large and accurate force/torque source. According to the particularity of the sensor's coupling errors, two decoupling algorithms are proposed in this paper to achieve high precision and flexible usage. The online decoupling algorithm is based on calculating decoupling matrices in partitioned space, while the offline algorithm is based on an optimized BP Neural Network using GA. Experimental results show that the designed six-axis force/torque sensor works well with high precision and reliability.
This paper explores the relationship between system stability conditional probability and the sliding mode control for second order continuous Markovian jump systems. By using the stochastic process theory, multi-step state transition conditional probability function is proposed for the continuous time discrete state Markovian process. A sliding mode control scheme is utilized to stabilize the continuous Markovian jump systems. The system stability conditional probability function is derived. It indicates that the system stability conditional probability is a monotonically bounded non-decreasing non-negative piecewise right continuous function of the control parameter. A numerical example is given to show the feasibility of the theoretical results.
Considering that incremental localization is influenced by the heteroscedasticity problem caused by cumulative errors and the collinearity problem among nodes, this paper has proposed an incremental localization algorithm with consideration to cumulative error and collinearity problem. Using iteratively reweighted method, the algorithm reduces the influences of error accumulation and avoids collinearity problem between nodes with a regularized method. Simulation experiment results show that compared with the previous incremental localization algorithms the proposed algorithm can not only solve the problem of heteroscedasticity, but also obtain a localization solution with high accuracy. In addition, the method also takes into account the influence of collinearity on localization calculation in the process of locating, thus the method is suitable for different monitoring areas and has high adaptability.
In this paper, the design of a wearable vibrotactile display waist belt that can impart situation awareness information on the user's waist were presented. The hardware of the vibrotactile display consists of 12 tactors attached to an elastic belt and the associated control and drive circuit. A technical overview and experiments of the system is presented as well as preliminary results on tactile perception to evaluate its performance on information transmission. These experiments show that the vibrotactile code scheme for direction is effective in increasing the users' situation awareness.
