A robust adaptive output-feedback control scheme based on K-filters is proposed for a class of nonlinear interconnected time-varying delay systems with immeasurable states. It is difficult to design the controller due to the existence of the immeasurable states and the time-delay couplings among interconnected subsystems. This difficulty is overcome by use of the fuzzy system, the K-filters and the appropriate Lyapunov-Krasovskii functional. Based on Lyapunov theory, the closed-loop control system is proved to be semi-global uniformly ultimately bounded (SGUUB), and the output tracking error converges to a neighborhood of zero. Simulation results demonstrate the effectiveness of the approach.
Quality of service and customer perception is the focus of the telecommunications industry. This paper proposes a low-cost approach to the acquisition of terminal data, collected from LTE networks with the application of a soft probe, based on the Java language. The soft probe includes support for fast call in the form of a referenced library, and can be integrated into various Android-based applications to automatically monitor any exception event in the network. Soft probe-based acquisition of terminal data has the advantages of low cost and can be applied on large scale. Experiment shows that a soft probe can efficiently obtain terminal network data. With this method, the quality of service of LTE networks can be determined from acquired wireless data. This work contributes to efficient network optimization, and the analysis of abnormal network events.
Random time delay may cause instability in the internet based teleoperation system. Transparency and intuitiveness are also very important for operator to control the system to accurately perform the desired action, especially for the gripper teleoperation system. This paper presents a new grip force control method of gripper teleoperation system with haptic feedback. The system employs the SEMG signal as the control parameter in order to enhance the intuitive control experience for operator. In order to eliminate the impacts on the system stability caused by random time delay, a non-time based teleoperation method is applied to the control process. Besides, neural network and designed fuzzy logic controller is also utilized to improve this control method. The effectiveness of the proposed method is demonstrated by experiment results.
Posture recognition is a very important Human-Robot Interaction (HRI) way. To segment effective posture from an image, we propose an improved region grow algorithm which combining with the Single Gauss Color Model. The experiment shows that the improved region grow algorithm can get the complete and accurate posture than traditional Single Gauss Model and region grow algorithm, and it can eliminate the similar region from the background at the same time. In the posture recognition part, and in order to improve the recognition rate, we propose a CNN ensemble classifier, and in order to reduce the misjudgments during a continuous gesture control, a vote filter is proposed and applied to the sequence of recognition results. Comparing with CNN classifier, the CNN ensemble classifier we proposed can yield a 96.27% recognition rate, which is better than that of CNN classifier, and the proposed vote filter can improve the recognition result and reduce the misjudgments during the consecutive gesture switch.
As the sensitivity of the fractional differential algorithm for detail image texture extraction and the difficulty of the best fractional differential order fingding, a novel adaptive fractional differential method is proposed, which can adaptively select the fractional differential order according to the mask window size, definition of fractional differential equations, the composite sub-band gradient vector (CSGV) obtained from the sub-images through a wavelet decomposition of a texture image, and human visual property. The fractional differential operator mask based on G-L formula is designed and realized by employing the adaptive order. The evaluation parameters of image texture feature extraction such as the image information entropy and multi-scale structural similarity (MS-SSIM) are used for quantitative analysis of the extraction method in experiment The experiment results show that for grey texture image this method is able to extract image texture and edge details completely, which approximate the results of optimal fractional differential order and more satisfies human visual sense. It is an effective approach to extract fine texture features of images.
The Chang’E-1 Laser Altimeter(LAM), as one of the scientific instruments onboard the Chinese Chang’E-1 orbiter, has successfully gained the massive lunar elevation scientific data of global topography of the moon. Uncertainty evaluation of the lunar elevation detection error based on LAM scientific data is developed in this paper. Firstly, the data are selected from the flat terrain region in all the lunar elevation detection data; Secondly, after the pseudo elevation data are removed in the selected region, regional elevation mean and standard deviation are calculated. Making use of the calculations and taking into account all kinds of uncertainty contributors of LAM orbiting exploring, the uncertainty evaluation methods of the LAM in-orbit elevation exploring are proposed on the basis of the guide to Monte Carlo Methods. Finally, the uncertainty evaluation results of different regions of lunar surface are given. The evaluation results not only can provide the basis for further analysis laser altimeter measurement error sources, but also give the reference for making the high precision moon digital elevation graph and provide theoretical guidance for the accuracy requirement of design of payload on lunar orbiter.
The paper develops a control system based on DSP28334 for lunar sampling, and provides the
main structure of it. The critical hardware and software design of the system are introduced in detail. The
emphasis is placed on the design and realization of the vibration control of the coiling-type sampler in the
process of lunar sampling. A control strategy which combines manual-control and local autonomous
control is applied for the lunar sampling control. And the sampling mechanism being controlled can
realizes multi-motor units working at time-sharing, which reduces the power comsumption and
increases the stability of the sampling system greatly. The practical application of the control strategy
used for the coiling-type sampler is verified by the finite element analysis. The experiments results show
that the system works with low power consumption and high efficiency, and the proposed strategy
enables greater depth and better efficiency during sampling.
High force update rate is a key factor for achieving high performance haptic rendering, which imposes a stringent real
time requirement upon the execution environment of the haptic system. This requirement confines the haptic system to
simplified environment for reducing the computation cost of haptic rendering algorithms. In this paper, we present a
novel "hyper-threading" architecture consisting of several threads for haptic rendering. The high force update rate is
achieved with relatively large computation time interval for each haptic loop. The proposed method was testified and
proved to be effective with experiments on virtual wall prototype haptic system via Delta Haptic Device.
Virtual reality is an effective method to solve the time-delay problem in force-reflecting teleoperation, but it
depends on the accuracy of the virtual model. So we consider the online error compensate of the predictive virtual
model, for acquiring accurate interaction information. Firstly, the sliding average least square (SALS) method is adopted
to identify the mass, damp and stiffness of the remote environment, in order to build and amend the virtual environment
dynamic model in real time. Secondly, we consider the predictive virtual model as a time forward observer, and design
our error compensate observer. Through constructing the dynamics equation of the system, we also analyzed the
condition of stability and transparency. Experimental results are shown that these methods can reduce the influence of
time delay with guarantee of stability, and promote the operability of the system.
Sampled-data system nature is the main factor for a haptic system to exhibit non-passive behaviors or instabilities through "energy leaks", particularly for stiff objects rendering. An energy-compensating method is presented aiming to improve the haptic system's performance based on the concept of doing work. Using ideal continuous-time haptic system as a reference, we define an energy-compensating controller (ECC controller) which compensates the energy leaks caused by zero-order-hold and asynchronous switching during entering and leaving contacts. The ECC controller not only removes the unwanted over-work from the virtual environment during leaving contacts to eliminate the system's potential non-passive behaviors, but also enlarges the work that should be done by the operator according to the reference system's value when new contacts arise. The proposed method was tested and verified with the implementation of a "virtual stiff-wall" via Delta 6-DOF haptic device.
This paper describes a virtual environment system, which can produce dynamic force simulation during the control of objects in virtual environment. A 5 degrees-of-freedom haptic interface master arm with the capability to generate kinesthetic effect is combined in this system. In this system, the human operator manipulates an object in virtual environment by using the 5-DOF master arm. When virtual manipulator contacting with the virtual object, the contact force can be calculated and shown in the graphic interface. The collision response and deformation of the virtual object, which is usually called haptic rendering, also can be exhibited in graph. The experience presents an approach to improve the operator's immersion and can be used in many telerobot control fields.