Transactions of the Institute of Measurement and Control

Zadkarami, Morteza; Safavi, Ali Akbar; Taheri, Mohammad; Salimi, Fabienne Fariba

doi: 10.1177/0142331220928145pmid: N/A

This paper proposes a novel data-based leakage diagnosis method for big datasets, which identifies the leak occurrence, its size, and its location. Different statistical features are used to express the changes in flow and pressure signals at different leakage scenarios. To improve the performances of the leakage diagnosis approach, factor analysis (FA) is employed for dimension reduction purposes. The optimal features of both pressure and flow signals are then fed as input vectors to a deep neural network (DNN) classifier. The proposed leakage diagnosis method has been applied to the first 20 km of the Golkhari-Binak oil pipeline, located in Iran. The leakage isolation accuracy has been compared with some related works. Simulation results show that the proposed method significantly outperforms others with the average correct classification rate (CCR) of about 98%.

Xue, Bingxin; Wang, Ruihua; Fei, Shumin

doi: 10.1177/0142331220928889pmid: N/A

This paper addresses the H∞ filtering problem for a class of discrete-time switched systems by using an admissible edge-dependent average dwell time (AED-ADT) method. By means of a convex combination of positive definite matrices, a novel multiple piecewise convex Lyapunov function (MPCLF) is constructed, which can loosen the restrictions of Lyapunov function at switching points and interval interior points. Based on the MPCLF approach, sufficient conditions are established such that the filtering error system is globally uniformly exponentially stable (GUES) and a prescribed noise attenuation level in an H∞ sense is achieved. Moreover, the corresponding time-varying H∞ filters are given as well. Finally, the results of the simulation illustrate the feasibility and effectiveness of the proposed approaches.

Tang, Jiqiang; Wei, Tongkun; Lv, Qichao; Cui, Xu

doi: 10.1177/0142331220929808pmid: N/A

For a magnetically suspended control moment gyro (MSCMG), which is an ideal attitude actuator for its large outputting control moment and fast response, the moving-gimbal effects due to the coupling between the moving gimbal and high-speeding rotor will make the magnetically suspended rotor (MSR) unstable. To improve control precision, both the dynamic model of MSR and the feedback linearization control are done to decouple tilting motion, and poles of the system are reconfigured to reduce control error. To suppress the varying disturbance moments caused by moving-gimbal effects, an extended state observer (ESO) is originally designed to estimate and compensate them timely and accurately. To improve system robustness, a two-degree freedom internal model control (2-DOF IMC) is researched to suppress model error. Compared with existing proportional integral derivative (PID) control method, simulations done on a single gimbal MSCMG with 200 N.m.s angular momentum indicated that this presented control method with ESO and 2-DOF IMC can suppress the moving-gimbal effects more effectively and make the rotor suspension more stable.

Abbas, Zameer; Nazir, Hafiz Zafar; Abid, Muhammad; Akhtar, Noureen; Riaz, Muhammad

doi: 10.1177/0142331220931977pmid: N/A

Investigation and removal of unnatural variation in the processes of manufacturing, production and services require application of statistical process control. Control charts are the most famous and commonly used statistical process control tools to trace changes in the manufacturing and nonmanufacturing processes parameter(s). The nonparametric control charts become necessary when the distribution of underlying process is unknown or questionable. The nonparametric charts are robust alternative along with holding property of quick shift detection ability in process parameter(s). In this article, we have proposed nonparametric double exponentially weighted moving average chart based on Wilcoxon signed rank test under simple and ranked set sampling schemes for efficient monitoring of the process location. The proposed control charts are compared with classical exponentially weighted moving average, double exponentially weighted moving average, nonparametric exponentially weighted moving average sign, nonparametric exponentially weighted moving average signed rank, nonparametric cumulative sum signed rank charts using average run length and some other characteristics of run length distribution as performance measures. Comparison reveals that the proposed control charts performs better to detect all kinds of shifts in the process location than existing counterparts. A real-life application related to manufacturing process (the variable of interest is the diameter of piston ring) is also provided for the practical implementation of the proposed chart.

Hu, Jiaming; Zhu, Xiaojin; Fang, Yubin; Gao, Zhiyuan; Zhou, Yijia

doi: 10.1177/0142331220932398pmid: N/A

Piezoelectric stacks (PS) are wildly used as actuator mechanism for precise instrument in practical engineering. Nevertheless, hysteretic effect that is carried by the piezoelectric materials can degrade the control performance dramatically. For the purpose of improving the control precision, the problem of hysteresis compensation control for PS system is investigated in this paper. First, in order to compensate the hysteretic effect, two kinds of observers are proposed. The design of the observers has considered external disturbance and the creep effect in PS system. By utilizing Lyapunov function and linear matrix inequalities (LMI) technique, the observers can asymptotically estimate the hysteretic output with H∞ performance. Second, a hysteresis-compensation based back-stepping controller is established. The design of the controller has considered the observation error, and it has a certain robustness. At last, numerical and experimental simulations are carried out to verify the effectiveness of the proposed methods.

Bidikli, Baris

doi: 10.1177/0142331220932396pmid: N/A

In this study, a nonlinear adaptive controller that can be used to control a magnetic levitation (maglev) is designed. The designed controller is equipped with a nonlinear velocity observer to provide the control without measuring velocity. Its capability to adaptively compensate all parametric uncertainties during the control process is one of the main advantages of this controller. Utilizing this capability, control of the maglev system can be realized without using any knowledge about system parameters. Due to the fast convergence capability of the designed observer and the desired model dependent structure of the adaptation rules, the proposed control design provides better performance than most of the robust and adaptive controllers that have been frequently used to control maglev system. The observer dynamics are analyzed via a Lyapunov–like preliminary analysis. Then, convergence of the observation and the tracking errors under the closed–loop operation and stability of the closed–loop error dynamics are proven via a Lyapunov–based stability analysis where the result obtained in the mentioned preliminary analysis is used. Performance of the designed observer–controller couple is demonstrated via experimental results. The efficiency of the designed controller is tested against a robust proportional–integral–derivative (PID) controller and an another Lyapunov–based nonlinear robust controller called as robust integral of sign of error (RISE) controller. Experimental results show that the designed controller performs the best tracking performance with the least control effort among these three controllers.

Chong, Zhi Lin; Huang, Shuo; Mukherjee, Amitava; Yang, Jun

doi: 10.1177/0142331220932466pmid: N/A

In recent years, researchers introduced several distribution-free schemes for simultaneously monitoring the location and scale parameters of distribution in the literature related to process monitoring and control. To this end, the Shewhart-Lepage (SL) and Shewhart-Cucconi (SC) schemes are two fundamental distribution-free schemes. These schemes are primarily designed to monitor the location-scale family of densities. In practice, apart from the location and scale parameters, we often encounter the presence of a shape (or skewness) parameter. In this article, we investigate the performance of the SL and SC schemes in monitoring such models. We consider some skewed distributions in the location-scale family with one or two additional parameters, some three-parameter time-to-event processes, such as three-parameter Weibull and Gamma, which are very common in various measurement and control literature. First, we present the in-control performance of the two competing schemes and then carry out a comprehensive out-of-control performance study by considering different combinations of shifts. Several recent investigations showed that the SC scheme performs just as well or better than the SL scheme in joint monitoring of the location and scale parameters for a large number of process distributions. The current study shows that in the presence of an additional parameter, especially when the shift in the shape parameter is substantial, the SL scheme is better; for a small change in shape, the SC scheme is more competitive. In general, the SL scheme performs better in monitoring the three-parameter distributions for time-to-event processes. Finally, a real application and some concluding remarks are presented.

Rauf, Arshad; Li, Shihua; Madonski, Rafal; Yang, Jun

doi: 10.1177/0142331220933415pmid: N/A

The combination of DC-DC buck power converters with DC motors for generating the so-called smooth start of drives has many advantages in engineering practice. Achieving high performance of such systems is, however, limited by the influence of disturbances/uncertainties of multiple sources. Some of the disturbances are mismatched, which makes them even more difficult to handle. Furthermore, the relatively high order of system dynamics makes the control design challenging. In this paper, a control structure with continuous dynamic sliding mode controller with a finite-time disturbance observer is proposed to address these practical issues. First, a special state transformation is applied, aggregating the acting disturbances/uncertainties in a sole perturbing term of the system expressed in new coordinates. Then, the observer estimates in real time the information about the lumped disturbances based on already available input/output signals and the obtained estimated signals (and their high order time-derivatives) are used to construct a sliding surface. Finally, the sliding mode controller is applied to achieve high performance of the resultant plant dynamics and to robustify the governing scheme against modelling discrepancies. The stability of the closed-loop system is proved here using Lyapunov stability theory and the efficiency of the proposed control method is validated through a multi-criteria numerical simulation.

Xu, Kexin; Wu, Xianqing; Ma, Miao; Zhang, Yibo

doi: 10.1177/0142331220933475pmid: N/A

In this paper, we consider the control issues of the two-dimensional translational oscillator with rotational actuator (2DTORA) system, which has two translational carts and one rotational rotor. An output feedback controller for the 2DTORA system is proposed, which can prevent the unwinding behaviour. In addition, the velocity signal unavailability and actuator saturation are taken into account, simultaneously. In particular, the dynamics of the 2DTORA system are given first. On the basis of the passivity and control objectives of the 2DTORA system, an elaborate Lyapunov function is constructed. Then, based on the introduced Lyapunov function, a novel output feedback control method is proposed straightforwardly for the 2DTORA system. Lyapunov theory and LaSalle’s invariance principle are utilized to analyse the stability of the closed-loop system and the convergence of the states. Finally, simulation results are provided to illustrate the excellent control performance of the proposed controller in comparison with the existing method.