Measurement and Control

Wang, Peiyao; Yu, Mingxin; Yan, Guang; Xia, Jiabin; Liu, Jiawei; Zhu, Lianqing

doi: 10.1177/00202940221145971pmid: N/A

The purpose of this paper is to propose a novel aircraft wing loads calculation model, called long short-term memory residual network (LSTM-ResNet), which can evaluate the loads based on the strain distribution. To achieve this goal, firstly, the data acquisition experiment is designed and performed with a real aircraft wing. In this experiment, we used the Fiber Bragg Grating (FBG) technology as the measurement method to collect strain-load data from the aircraft wing. Then, we propose the LSTM-ResNet model with the one-dimensional convolutional(1D-CNN) architecture. This model is capable of extracting the temporal and spatial representational information from the strain-load data of the aircraft wing. Experimental results demonstrate that the proposed method effectively evaluate the loads of the aircraft wing. To prove the superiority of LSTM-ResNet model, we compared the proposed model with existing loads calculation methods on our experimental dataset. The results show it has a competitive average relative error (0.08%). Moreover, those promising results may pave the way to use the deep learning algorithm in aircraft wing loads calculation.

Li, Luyun; Zhang, Ruijun; Cheng, Gang; Zhang, Po; Jia, Xiucheng

doi: 10.1177/00202940221144476pmid: N/A

In this paper, an optimal sliding mode control method for trajectory tracking of discrete-time systems based on linear quadratic regulator is proposed to improve the trajectory tracking control accuracy and robustness of upper limb rehabilitation robot under the condition of highly nonlinearities, external disturbances, and unmodeled dynamics. Firstly, considering the uncertainty of the mass and moment of inertia of the connecting rod arm of the upper limb rehabilitation robot and the uncertainty of external interference, the dynamic model of the upper limb rehabilitation robot is established by using the Euler Lagrange method, and the linear time-varying state equation of the rehabilitation robot system under the influence of both nonlinear and uncertain factors is derived. Secondly, directing at the chattering problem in sliding mode control, a sliding mode control method based on a new discrete time reaching law is designed to reduce the amplitude of chattering in the control input signal of the upper limb rehabilitation robot system and improve the tracking speed. Furthermore, combined with linear quadratic optimal control, the optimal discrete integral sliding mode control law (LQRSMC) is finally obtained. Meanwhile, for the sake of reducing the influence of the uncertain signal on the system, a robust control law is adopted to estimate and compensate the uncertain interference. The stability of the upper limb rehabilitation robot system is verified by the sliding mode approach condition of the discrete system. Finally, the genetic algorithm is used to further optimize the weighted value, and MATLAB/Simulink is used to simulate the state trajectory of the upper limb rehabilitation robot under various weighted values. The control strategy can not only effectively weaken the trajectory tracking oscillation problem of the upper limb rehabilitation robot, but also overcome the external disturbance and modeling uncertainty, while ensuring the robustness of the rehabilitation robot system.

Zaheer, Muhammad Hamad; Yoon, Se Young; Higginson, Brian K

doi: 10.1177/00202940221149062pmid: N/A

This work presents an integrated solution for head orientation estimation, which is a critical component for applications of virtual and augmented reality systems. The proposed solution builds upon the measurements from the inertial sensors and magnetometer added to an instrumented helmet, and an orientation estimation algorithm is developed to mitigate the effect of bias introduced by noise in the gyroscope signal. Convolutional Neural Network (CNN) techniques are introduced to develop a dynamic orientation estimation algorithm with a structure motivated by complementary filters and trained on data collected to represent a wide range of head motion profiles. The proposed orientation estimation method is evaluated experimentally and compared to both learning and non-learning-based orientation estimation algorithms found in the literature for comparable applications. Test results support the advantage of the proposed CNN-based solution, particularly for motion profiles with high acceleration disturbance that are characteristic of head motion.

Aramesh, Morteza; Sohraiee, Sevan; Hosseinzadeh Lotfi, Farhad

doi: 10.1177/00202940221149084pmid: N/A

As an important concept in data envelopment analysis (DEA), elasticity measure has wide theoretical and practical applications in formulating various economic concepts. Anchor points also appear to be particularly interesting and highly useful in DEA, especially for recognizing a decision making unit (DMU) as a benchmark. This paper is an attempt to use left-and right-hand elasticity measures to present a novel definition (characterization) for anchor points. The study results reveal that if there exists an increase in a bundle of input with no rate of change in a bundle of output or if there is a decrease in a bundle of output, but a bundle of input has no rate of change, then such an extreme point is the anchor point.

Dai, Bowen; He, Zhongbo; Yang, Zhaoshu; Xue, Guangming; Zhou, Jingtao; Liu, Guoping

doi: 10.1177/00202940221082960pmid: N/A

Magnetostrictive transducer, as a kind of high-efficiency transducer, has a broad application in the field of energy harvesting and sensor. However, the voltage generating performance of the transducer limits its application. This paper will endeavor to quantify the load-induced voltage of magnetostrictive transducer by developing a holistic theoretical model and deriving the corresponding analytical solution. On this basis, this paper proposed the concept of voltage sensitivity in transducer optimization, which could quantitatively analyze the normalized voltage generated by a unit excitation. Based on the theoretical simulation and experimental validation, the voltage sensitivities of magnetostrictive transducer under different mechanical loads are investigated. The parametric analysis will be conducted to further optimize the transducer structure to enhance its open-circuit and load voltage. The works of this paper could be instructive to guide magnetostrictive transducer design in sensing and energy harvesting applications.

Cao, Ning; Yi, Guodong; Zhang, Shuyou; Qiu, Lemiao

doi: 10.1177/00202940221139327pmid: N/A

Presently, mobile robots experience problems of time consumption, poor security, and high computational complexity in global path-smoothing algorithms. This study presents a multiobjective path-smoothing algorithm, including a path point adjustment algorithm and a turn-smoothing method called the point adjustment algorithm and smoothing. First, the proposed path point adjustment algorithm filters and moves the nodes in an original path to decrease the length of the path and increase the angle of the turns in the path. Second, the proposed turn-smoothing method inserts the B-spline curve into the processed path to smooth the discontinuous turns in the path. Subsequently, the positions of the control points are adjusted based on the property of the B-spline to ensure that the smoothed path can avoid obstacles and satisfy the maximum curvature constraint. Simulation results show that the proposed algorithm can quickly calculate the path satisfying the robot dynamic constraints in various environments combined with different global path planning algorithms. Compared with other mainstream path-smoothing algorithms, this algorithm makes a substantial improvement in path length.

Liang, Shi; Long, Zhiqiang; Wang, Ping; Zeng, Jiewei

doi: 10.1177/00202940221105095pmid: N/A

Based on the research background of shallow-ground metal detection under the environment with the interference of steeling structure,a metal detection method based on the transient electromagnetic method is studied. The test platform is built and verified by experiments. Firstly, the loos model of the coil system is established, and the transfer function with the excitation voltage source as the input signal and the induced voltage of the metal conductor as the output signal is derived. The system design of metal detection based on pulse electromagnetic induction is carried out, and a simple and feasible experimental platform is built according to the demand. Aiming at the signal processing problem of metal detection in a complex environment such as steel structure, a detection algorithm based on a hypersphere model and confidence interval is applied. Finally, the experimental verification is carried out. The results show that the designed system is feasible for metal detection, and the applied signal processing algorithm is effective although interfering by steeling structure inthe environment.

Wang, Tianlei; Tan, Nanlin; Qiu, Jiongzhi; Zheng, Zhaoming; Lin, Chengmin; Wang, Hongmin

doi: 10.1177/00202940221143851pmid: N/A

To achieve stabilisation control of an underactuated bridge crane system, a new robust control strategy for the sliding mode is proposed in this paper. It can realise finite-time-convergent stabilisation control under the conditions of model uncertainty, parameter perturbation and external interference. In contrast to the existing methods, our method does not need prior information of the dynamic characteristics of the bridge crane system, and can make the system converge to the equilibrium state at the preset time. Specifically, the nonlinear model of the bridge crane system is linearised with partial feedback, and adaptive signals are introduced. Then, according to the form of the transformed system, a fast terminal sliding mode surface is constructed, and an adaptive terminal sliding mode controller is designed. According to strict analysis, the proposed control law ensures that the system converges to the equilibrium point in finite time and provides the convergence time. Finally, the effectiveness and robustness of the proposed control method are verified by comparing the simulation and experimental results with existing methods.

Luo, Qiuwen; Wu, Sheng; Bai, Jianjun; Wu, Feng; Zhang, Ridong

doi: 10.1177/00202940221149069pmid: N/A

A novel design of robust constrained model predictive tracking control is proposed for systems with polytopic description. Unlike the conventional robust model predictive tracking control, the proposed method adopts an improved state space model in which the process state variables and tracking error are combined such that they can be tuned in the cost function optimization separately. Based on the proposed new model, more degrees of freedom are provided for the subsequent controller design, which leads to improved control performance. The relevant feasibility and robust stability issues are further discussed, and the effectiveness of the proposed approach is tested on the control of a system which is open-loop unstable with dead time and reverse responses.

Salwa, Yahia; Saida, Bedoui; Abderrahim, Kamel

doi: 10.1177/00202940221143584pmid: N/A

Over the past few decades, there have been increasing research activities in fault diagnosis (FD) and fault-tolerant control (FTC) for switched hybrid systems. This paper addresses the problem of active-fault tolerant control (AFTC) for switched hybrid systems subject to actuator faults to enhance system security and keep system stability. The proposed FTC is designed by adding the state feedback control with integral action to an additive control law which requires accurate fault estimation to compensate for the fault effect. Thus, a data-based projection method (DPM) is extended (EDPM) based on inputs and outputs measures to estimate the fault without using mathematical models. The synthesis of the state feedback control with integral action is proposed for recovering the desired performances. It integrates a set of controllers corresponding to a set of partial models to design a set of switching control laws. Indeed, new linear matrix inequalities (LMIs) using Lyapunov stability analysis are proposed to find the optimal values of the control gains matrices and keeping system stability. A comparative study of the proposed FTC with existing work is given to show the effectiveness of the proposed technique.