Transactions of the Institute of Measurement and Control

Wang, Yao; Guo, Jun; Liu, Guobao; Lu, Junwei; Li, Fangyuan

doi: 10.1177/01423312211046510pmid: N/A

The problem of finite-time filtering for nonlinear Markovian jump systems subject to extended dissipativity with unknown transition rates and time-varying delays is investigated in this paper. Firstly, by constructing novel Lyapunov-Krasovskii functionals and utilizing delay partitioning method, the error system is proved to be stochastically finite-time bounded and extended dissipative. Secondly, in virtue of linear matrix inequalities approach, the desired mode-dependent filter is obtained. Finally, two simulations are illustrated for the purpose of demonstrating the less conservativeness and effectiveness of the proposed method.

Lamouchi, Rihab; Raissi, Tarek; Amairi, Messaoud; Aoun, Mohamed

doi: 10.1177/01423312211040370pmid: N/A

The paper deals with passive fault tolerant control for linear parameter varying systems subject to component faults. Under the assumption that the faults magnitudes are considered unknown but bounded, a novel methodology is proposed using interval observer with an L∞ formalism to attenuate the effects of the uncertainties and to improve the accuracy of the proposed observer. The necessary and sufficient conditions of the control system stability are developed in terms of matrix inequalities constraints using Lyapunov stability theory. Based on a linear state feedback, a fault tolerant control strategy is designed to handle component faults effect as well as external disturbances and preserve the system closed-loop stability for both fault-free and component faulty cases. Two simulation examples are presented to demonstrate the effectiveness of the proposed method.

Yang, Xiaohe; Lv, Weijie; Hu, Chaofang; Hu, Yongtai

doi: 10.1177/01423312211046504pmid: N/A

In this paper, tube-model predictive control based on the sum of squares technique is developed for hypersonic vehicles with state-dependent input constraints. Firstly, the longitudinal non-linear model in the presence of uncertain parameters is transformed into the polytopic linear parameter varying model with bounded disturbance by feedback linearization. Then the actual input constraints are converted to the virtual state-dependent input constraints in linear multivariable polynomial. A composite feedback control law based on tube-model predictive control is designed into a convex combination of unconstrained and constrained control. The real control law can be obtained by inversion. The sum of squares technique is used to transform the polynomial constraints into the convex matrix sum of squares condition via linear matrix inequality. Finally, simulation results verify the effectiveness of the proposed controller.

Mohammadi Moghadam, Hooman; Mohammadzadeh, Ardashir; Hadjiaghaie Vafaie, Reza; Tavoosi, Jafar; Khooban, Mohammad- Hassan

doi: 10.1177/01423312211048038pmid: N/A

This paper presents a new type-2 fuzzy logic control (T2FLC) for active/reactive power (AP/RP) regulation and energy storage management of an independent microgrid (MG). The case-study MG includes sporadic renewable sources that lead to significant frequency and voltage fluctuations in the network. The rules of suggested T2FLCs are tuned such that a fractional-order sliding condition can be satisfied. Also a new approach using square-root-cubature Kalman filter is designed to optimize the membership parameters of T2FLCs. Beside AP/RP power regulation, an electrical storage system (battery energy storage system (BESS)) is managed to produce the rated power, rather than a conventional generator. It makes the device frequency separate from the synchronous generator’s mechanical inertia. Nevertheless, a BESS has a power limit – it uses a synchronous generator to sustain the BESS charge state at a certain value. Sustainable energies achieve a voltage-damping impact by supplementing an AP/RP droop strategy procedure that considerably reduces voltage oscillation created by variation of its own output power. In various disturbed scenarios the good performance of the suggested controller and energy management system is shown.

Cheng, Dingding; Liu, Lijun; Yu, Zhen

doi: 10.1177/01423312211039641pmid: N/A

Traditional steady-state control methods are applied to turbofan engines operating in the small region near certain operating conditions, which need to switch controllers for operating in the large region and then may lead to instability and performance degradation of the closed-loop system. In this paper, a novel multivariable nonlinear robust control method for turbofan engines is proposed to improve the control performance within the large region. To enlarge the controllable region, a polynomial state-space model describes the nonlinear characteristics of turbofan engines. Based on the analysis of the closed-loop control system, by using the Lyapunov function theorems, a polynomial robust controller is designed to ensure the stability and desired nonlinear control performance of turbofan engines. Compared with the classical PI, mixed sensitivity, and H∞ control, simulation results show that the proposed method has better transient responses, disturbance rejection, and other control performance for the turbofan engine within the large region.

Yang, Xiaowei; Deng, Wenxiang; Liu, Long; Yao, Jianyong

doi: 10.1177/01423312211043676pmid: N/A

This article focuses on the asymptotic tracking control problem for uncertain nonlinear systems subject to both multiple disturbances and parametric uncertainties. To address this issue, a parameter adaptation law is synthesized to deal with the parametric uncertainties, and an adaptive-gain disturbance estimator (ADE) is constructed to estimate the mismatched and matched disturbances, and compensate them in feedforward channels, which eliminates the impact of disturbances on tracking performance. Meanwhile, an updated law for estimator gain driven by the estimation errors is utilized in the ADE when facing unknown upper bounds of disturbances, which reduces the conservatism of estimator gain selection and is beneficial to practical implementation. Based on the parameter adaption technique and the presented ADE approach, a composite controller is proposed to ensure an excellent asymptotic output tracking performance. The stability analysis shows the proposed controller can attain asymptotic tracking performance in the presence of both time-variant disturbances and parametric uncertainties. Comparative simulation results of the application to a robot manipulator reveal the validity of the developed approach.

Vijay Anand, J; Manoharan, PS

doi: 10.1177/01423312211049237pmid: N/A

The fuzzy logic controller (FLC) makes it possible to control a system using IF-THEN rules through human intellect. It tackles parameter uncertainty using imprecise reasoning. The fuzzy logic controller is usually tuned using offline methods. An online evolving adaptation of fuzzy controller design is a recent trend in fuzzy rule-based systems. The robust evolving cloud-based controller (RECCo) is one such controller implemented for single-input-single-output (SISO) systems. The membership functions and consequent rules are automatically updated in real time based on the input data. In this paper, a decentralized robust evolving cloud-based controller (DRECCo) is proposed for two-input-two-output (TITO) systems. It consists of two independent loops with RECCos having a nonparametric premise facet and an adaptive proportional-integral-derivative (PID) model consequent facet. The effectiveness of the proposed method is validated for the benchmark interacting two-tank process (ITTP) and quadruple-tank process (QTP) by simulation and in real time. The results indicate that with the information of loop pairing and the forward-acting/reverse-acting nature of the process, the proposed controller can adapt itself to ensure set-point tracking and disturbance rejection.

Chi, Chuanguo; Liu, Guo-Ping; Hu, Wenshan

doi: 10.1177/01423312211049214pmid: N/A

This paper investigates the design and implementation of a mobile terminal cloud supervisory control (MTCSC) platform based on networked control systems (NCSs). The platform relying on mobile programming and C/S architecture provides real-time data transmission and supervisory for the cloud control system (CCS). Users can deploy the platform in smart phones, tablet computers and other mobile devices, which solves the problem of the dependence on PC for networked supervisory system. Both asynchronous data receiving and synchronous real-time monitoring of different cloud nodes are supported on mobile terminal. Additionally, through data cloud transmission, users can realize remote cloud monitoring. Moreover, to overcome the data delay during users’ monitoring and to improve the reliability of the system, a multi-threaded communication and real-time communication scheme are proposed. The virtual instruments and function modules of the system can be customized by users, which not only increase the flexibility of operation but also enhance the customization and expansion of functions. Finally, the feasibility of the MTCSC platform is verified by online simulation and experiment.

Zhao, Meijiao; Peng, Yan; Wang, Yueying; Zhang, Dan; Luo, Jun; Pu, Huayan

doi: 10.1177/01423312211047104pmid: N/A

In this paper, a concise leader-follower formation control approach is presented for a group of underactuated unmanned surface vehicle with dynamic system uncertainties and external environment disturbances, where the output errors are required to be within constraints. To settle the output error constraints, a standard barrier Lyapunov function (BLF) is incorporated into the backstepping control method. Furthermore, the “differential explosion” problem of virtual control laws is avoided by introducing the dynamic surface control. To estimate the unknown dynamic terms, an adaptive neural network is designed and a nonlinear disturbance observer is adopted to compensate for the approximation errors of neural network and ocean environment disturbances. Under the constraint of output error, the presented controller based on standard BLF has simpler structure and better control performance than depended on tan-type BLF. The presented controller can ensure that the formation errors converge to a small range around zero, while the output error constraint requirements are met. All signals in the closed-loop system are bounded, and the numerical simulation further shows the effectiveness of the presented control scheme.

Parvizian, Majid; Khandani, Khosro

doi: 10.1177/01423312211049003pmid: N/A

We investigate the fractional-order systems that are perturbed by stochastic input to achieve stabilization via sliding mode control (SMC) approach. It is assumed that the system states are unknown and there is uncertainty and time-delay in the system. We utilize the diffusive representation of the stochastic fractional-order dynamics to transform the system into an integer-order system perturbed by Brownian motion. Provided that some linear matrix inequalities (LMIs) are feasible, it is proven that the estimation error system is stochastically stabilized and the overall closed-loop system is stable in probability. A numerical simulation shows the effectiveness of the results.