Model reference adaptive impedance control in Cartesian coordinates for physical human–robot interaction

In this paper, a nonlinear model reference adaptive impedance controller is proposed and tested. The controller provides asymptotic tracking of a reference impedance model for the robot end-effector in Cartesian coordinates applicable to rehabilitation robotics or any other human–robot interactions such as haptic systems. The controller uses the parameters of a desired stable reference model which is the target impedance for the robot’s end-effector. It also considers uncertainties in the model parameters of the robot. The asymptotic tracking is proven using Lyapunov stability theorem. Moreover, the adaptation law is proposed in joint space for reducing the complexity of its calculations; however, the controller and the stability proof are all presented in Cartesian coordinates. Using simulations and experiments on a two DOFs robot, the effectiveness of the proposed controller is investigated.     

Perception of own and robot engagement in human–robot interactions and their dependence on robotics knowledge

Communication between socially assistive robots and humans might be facilitated by intuitively understandable mechanisms. To investigate the effects of some key nonverbal gestures on a human’s own engagement and robot engagement experienced by humans, participants read a series of instructions to a robot that responded with nods, blinks, changes in gaze direction, or a combination of these. Unbeknown to the participants, the robot had no form of speech processing or gesture recognition, but simply measured speech volume levels, responding with gestures whenever a lull in sound was detected. As measured by visual analogue scales, engagement of participants was not differentially affected by the different responses of the robot. However, their perception of the robot’s engagement in the task, its likability and its understanding of the instructions depended on the gesture presented, with nodding being the most effective response. Participants who self-reported greater robotics knowledge reported higher overall engagement and greater success at developing a relationship with the robot. However, self-reported robotics knowledge did not differentially affect the impact of robot gestures. This suggests that greater familiarity with robotics may help to maximise positive experiences for humans involved in human–robot interactions without affecting the impact of the type of signal sent by the robot.     

Classification of cardiac sound signals using constrained tunable-Q wavelet transform

The features extracted from the cardiac sound signals are commonly used for detection and identification of heart valve disorders. In this paper, we present a new method for classification of cardiac sound signals using constrained tunable-Q wavelet transform (TQWT). The proposed method begins with a constrained TQWT based segmentation of cardiac sound signals into heart beat cycles. The features obtained from heart beat cycles of separately reconstructed heart sounds and murmur can better represent the various types of cardiac sound signals than that from containing both. Therefore, heart sounds and murmur have been separated using constrained TQWT. Then the proposed novel raw feature set has been created by the parameters that have been optimized while constraining the output of TQWT together with that of extracted by using time-domain representation and Fourier–Bessel (FB) expansion of separated heart sounds and murmur. However, the adaptively selected features have been used to obtain the final feature set for subsequent classification of cardiac sound signals using least squares support vector machine (LS-SVM) with various kernel functions. The performance of the proposed method has been validated with publicly available datasets and the results have been compared with the existing short-time Fourier transform (STFT) based method. The proposed method shows higher percentage classification accuracy of 94.01 as compared to 93.53 of STFT based method. In comparison with STFT based method, it is noteworthy that the proposed method uses well defined and lower dimensionality of feature vector that can reduce the computational complexity.     

Isothermal crystallization and spherulite structure of partially miscible polypropylene–linear low-density polyethylene blends

Polypropylene (PP) was blended with a linear low-density polyethylene (LLDPE, containing 5% hexene comonomer) over a composition range of 10–90% of PP. The crystallization and morphology of the PP–LLDPE blends were studied by differential scanning calorimetry (DSC), polarized optical microscopy with a hot stage (HSOM), and scanning electron microscopy (SEM). In particular, the isothermal crystallization of PP in molten LLDPE was investigated. It was observed that the crystallization and melting behavior of PP and LLDPE changed in the blends, indicating that there was some degree of miscibility between the PP and the LLDPE. A depression of the equilibrium melting temperature (T) of PP in the blends with no more than 15% of PP confirmed that PP was miscible with LLDPE at and below 15% of PP. In addition, a drastic decrease in T from the 25% PP blend to the 20% blend led us to conclude that the miscible behavior between PP and LLDPE became favorable at a PP concentration of 20%. The optical microscopic images showed that, in the blends with 10 and 15% of PP, the PP crystallized as open-armed diffuse spherulites, similar to those in the miscible blends. In contrast, the PP crystallized in a phase-separated matrix or droplets with more than 25% of PP, when obvious phase separation occurred. The SEM image revealed that the PP lamella was able to penetrate the PP and LLDPE phase boundary and grow in the LLDPE phase. The above results displayed that the PP dissolved in the LLDPE, and, particularly, when the PP concentration was below 20%, the dissolution was substantial. © 2001 John Wiley & Sons, Inc. J Appl Polym Sci 82: 628–639, 2001     

L2 disturbance attenuation for highly dissipative nonlinear spatially distributed processes via HJI approach

For many practical industrial spatially distributed processes (SDPs), their dynamics are usually described by highly dissipative nonlinear partial differential equations (PDEs). In this paper, we address the L₂ disturbance attenuation problem of nonlinear SDPs using the Hamilton–Jacobi–Isaacs (HJI) approach. Firstly, by collecting an ensemble of PDE states, Karhunen–Loève decomposition (KLD) is employed to compute empirical eigenfunctions (EEFs) of the SDP based on the method of snapshots. Subsequently, these EEFs together with singular perturbation (SP) technique are used to obtain a finite-dimensional slow subsystem of ordinary differential equation (ODE) that accurately describes the dominant dynamics of the PDE system. Secondly, based on the slow subsystem, the L₂ disturbance attenuation problem is reformulated and a finite-dimensional H_∞ controller is synthesized in terms of the HJI equation. Moreover, the stability and L₂-gain performance of the closed-loop PDE system are analyzed. Thirdly, since the HJI equation is a nonlinear PDE that has proven to be impossible to solve analytically, we combine the method of weighted residuals (MWR) and simultaneous policy update algorithm (SPUA) to obtain its approximate solution. Finally, the simulation studies are conducted on a nonlinear diffusion-reaction process and a temperature cooling fin of high-speed aerospace vehicle, and the achieved results demonstrate the effectiveness of the developed control method.     

A Dantzig–Wolfe decomposition algorithm for linear economic model predictive control of dynamically decoupled subsystems

This paper presents a warm-started Dantzig–Wolfe decomposition algorithm tailored to economic model predictive control of dynamically decoupled subsystems. We formulate the constrained optimal control problem solved at each sampling instant as a linear program with state space constraints, input limits, input rate limits, and soft output limits. The objective function of the linear program is related directly to the cost of operating the subsystems, and the cost of violating the soft output constraints. Simulations for large-scale economic power dispatch problems show that the proposed algorithm is significantly faster than both state-of-the-art linear programming solvers, and a structure exploiting implementation of the alternating direction method of multipliers. It is also demonstrated that the control strategy presented in this paper can be tuned using a weighted ℓ₁-regularization term. In the presence of process and measurement noise, such a regularization term is critical for achieving a well-behaved closed-loop performance.     

邻乙氧基苯甲酸合成方法的改进

采用两种新方法合成了邻乙氧基苯甲酸：以水杨酸甲酯和溴乙烷为原料在碘化钾催化下先制得邻乙氧基苯甲酸甲酯，再经水解、酸化得邻乙氧基苯甲酸；由水杨酸和硫酸二乙酯经碱性下取代、酸化制得了邻乙氧基苯甲酸。两种方法的收率分别为89．2％和92．2％。     

Investigation of the effect of surface phosphate ester dispersant on viscosity by coarse-grain modeling of BaTiO slurry

To understand the role of phosphate ester dispersant, we investigated the rheology of a BaTiO slurry. For the model case, a coarse-grain molecular dynamics (CGMD) simulation was performed with the butyral polymer didodecyl hydrogen phosphate (DHP) in the toluene/ethanol solvent. By systematically analyzing the effect of DHP from an atomic-scale first principle and from all-atom MD to microscale CGMD simulation, we investigated how the adsorption of a DHP dispersant on a BaTiO surface affects the microstructure rheology of a BaTiO slurry. The first-principle and all-atom MD simulation suggests that DHP molecules prefer to locate near the BaTiO surface. CGMD simulation shows a reduction in viscosity with an increase in dispersants, suggesting that the dispersant population near the BaTiO surface plays a key role in controlling the rheology of the BaTiO slurry. In this study, we propose an approach for understanding the BaTiO slurry with molecular-level simulations, which would be a useful tool for efficient optimization of slurry preparation.     

基于改进符号化度量方法的机场噪声异常检测

机场噪声中的异常情况拥有很大价值,利用它能够及时完善飞机和机场的设备。结合机场噪声数据的特点,对上述问题进行研究并提出一种基于改进的符号化聚集近似(Symbolic Aggregate Approximation,SAX)相似性度量的单监测点的时间序列异常检测方法。其运用相似性度量方法计算出度量结果,再运用k近邻异常检测方法进行异常发现,最后发现异常时间段。该方法在理论验证可行性之后在某机场的实测数据中进行应用,取得了良好的效果。     

不确定视角下改进TOPSIS法的工程评标模型研究

评标质量决定中标者与招标项目的契合程度,但受经验知识和主观判断等影响,定性指标的量化过程易带有主观模糊性,从而影响结果准确度。为减少模糊因素对评标结果的负作用,引入Z-number模糊数识别定性指标的不确定性,依据熵值原理客观确定评标指标及评标专家权重,TOPSIS法集成指标值,构建基于Z-number理论的改进TOPSIS法评标模型。结果表明,提议方法不仅能明晰度量定性指标值本身的模糊程度,还实现了指标值不确定性的针对化削减。同时,在有效避免主观赋权带来的不确定性基础上,该方法也克服了指标间的不可公度性。通过示例分析与敏感性分析验证了模型的实效性与稳定性。