IET Control Theory & Applications
Volume 15, Issue 12
[https://ietresearch.onlinelibrary.wiley.com/toc/17518652/2021/15/12](https://ietresearch.onlinelibrary.wiley.com/toc/17518652/2021/15/12
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Finite-time synchronization and identification of the Markovian switching delayed network with multiple weights
Xie, Qian; Guo, Duo; Wang, Tong; Yang, Xiaoping
https://doi.org/10.1049/cth2.12104
Abstract: This paper focuses on finite-time synchronization and parameters identification in the Markovian switching complex delayed network with multiple weights. Considering the control cost required for network synchronization, finite-time control technique and pinning control strategy are adopted. Based on these methods, when finite-time synchronization of the network is achieved, the unknown parameters of the system can also be identified in finite time. In addition, in order to solve the problem of the network performance change caused by network topology switching, an Optimal Nodes Selection Control Strategy (ONSCS) is proposed. On the one hand, finite-time synchronization and identification of the network can be realized faster, on the other hand, it also further reduces the energy consumption and control cost of the network. Finally, two sets of comparative numerical simulations are given to prove the superiority and applicability of the proposed ONSCS.
Distributed gradient descent method with edge-based event-driven communication for non-convex optimization
Adachi, T.; Hayashi, N.; Takai, S.
https://doi.org/10.1049/cth2.12127
Abstract: This paper considers an event-driven distributed non-convex optimization algorithm for a multi-agent system, where each agent has a non-convex cost function. The goal of the multi-agent system is to minimize the global objective function, which is the sum of these local cost functions, in a distributed manner. To this end, each agent updates the own state by a consensus-based gradient descent algorithm. The local information exchange among neighbor agents is carried out with an event-triggered scheme to achieve consensus with less inter-agent communication. Convergence to a critical point of the objective function and the validity of the proposed algorithm in numerical examples are shown.
Model identification and parametric adaptive control of hydraulic manipulator with neighborhood field optimization
Guo, Qing; Chen, Zhenlei; Shi, Yan; Liu, Gan
https://doi.org/10.1049/cth2.12145
Abstract: The model identification and uncertain parameters estimation are common control problems in multi-DOF manipulator system, since both model parametric uncertainties and unknown external disturbance often degrade the output performance and the close-loop system stability. In this study, by using the joint angle and the torque information, a neighborhood field optimization is adopted to identify the Lagrange model parameters of two-DOF hydraulic manipulator. The fitness function of the neighborhood field optimization is designed to optimize the minimal squared error of the torque estimation and to obtain the lumped estimated parameters with high accuracy. Then based on the identification model, a parametric adaptive controller is designed to address uncertain electro-hydraulic parameters and external disturbances. Furthermore, a new stable control variable is redesigned to avoid the redundant input saturation of electro-hydraulic actuator. The effectiveness of the proposed controller is verified by the comparative experimental results with the general backstepping controller.
Quasi-bipartite synchronisation of multiple inertial signed delayed neural networks under distributed event-triggered impulsive control strategy
Udhayakumar, K.; Rihan, Fathalla A.; Li, Xiaodi; Rakkiyappan, R.
https://doi.org/10.1049/cth2.12146
Abstract: The central concern of this paper is to study leader-following quasi-bipartite synchronisation of a multiple inertial signed neural networks with varying time-delay by utilising distributed event-triggered impulsive control scheme, where connections between adjacent nodes of the neural networks either positive or negative. The second-order neural networks, called inertial neural networks, can be transformed into differential equations of first-order by implementing suitable variable substitution. Under certain hypothesis about the node dynamics, signed graph theory and balanced topology of networks, some conditions are derived in terms of lower-dimensional linear matrix inequalities (LMIs) to achieve leader-following quasi-bipartite synchronisation. In addition, a basic algebraic condition is derived to estimate the theoretical upper bound for the error node. Finally, some numerical simulations are provided to illustrate the correctness of the theoretical results.
Exponential stability of discrete-time delayed neural networks with saturated impulsive control
He, Zhilong; Li, Chuandong; Cao, Zhengran; Li, Hongfei
https://doi.org/10.1049/cth2.12147
Abstract: This paper examines the problem of the locally exponentially stability for impulsive discrete-time delayed neural networks (IDDNNs) with actuator saturation. By fully considering the delay information of the state of the considered system, a new delay-dependent polytopic representation within a discrete-time framework is obtained. Based on the delay-independent polytopic representation approach, the saturation term is expressed as a delay-dependent convex combination. In order to obtain some less conservative stability conditions and estimate a larger of the domain of attraction, a novel type of Lyapunov?Krasovskii function (LKF) dependent on the delay information and the impulses instant is proposed, which is called time-dependent LKF. Then, by combining with the proposed LKF, a discrete Wirtinger-based inequality, an extended reciprocally convex matrix inequality and some novel analysis techniques, several new exponential stability criteria dependent on the bounds of the delay are presented. Moreover, when saturation constraints are not considered in the impulsive controller, the stability of the system is also discussed. Finally, two examples are given to confirm the applicability of the proposed results.
Distributed event-triggered output feedback H∞ control for multi-agent systems with transmission delays
Li, Yanjin; Yu, Hui; Xia, Xiaohua
https://doi.org/10.1049/cth2.12148
Abstract: The output feedback H∞ consensus control problem of multi-agent systems is studied using an event-triggered control strategy. Two types of transmission delays, one from the system output to the output feedback controller (OFC) and the other from the OFC to the zero-order holder, are considered. This causes the OFC and the system not to be updated in the same time intervals. An interval dividing approach is applied to such that the whole system can be updated in the same time intervals. An event-triggered OFC with H∞ performance is proposed for multi-agent systems to achieve consensus. By constructing an appropriate Lyapunov?Krasovskii functional, sufficient conditions based on linear matrix inequality are derived to guarantee the consensus achievement. Finally, the theoretical results are validated using computer simulation.
Predefined formation-containment control of high-order multi-agent systems under communication delays and switching topologies
Zhou, Shiyu; Dong, Xiwang; Hua, Yongzhao; Yu, Jianglong; Ren, Zhang
https://doi.org/10.1049/cth2.12150
Abstract: This paper concerns the problem of formation-containment control for general-linear multi-agent systems (MASs) with both communication delays and switching interaction topologies. On the one hand, the leaders can communicate with each other to form the desired formation and on the other, the followers need to enter the convex envelope spanned by the multiple leaders. Firstly, by using the neighbouring relative information, formation-containment protocols are designed for each leader and follower, where an edge-based state observer is incorporated into the formation-containment controller to evaluate the whole leaders' state. Secondly, according to the linear matrix inequality technology, an algorithm is given to determine the unknown feedback matrixes in the protocol. Then, based on Lyapunov theory, the formation-containment error is proved to be convergent and formation feasibility conditions are also presented for the MASs to achieve formation-containment. Finally, a simulation on several MASs is provided to demonstrate the theoretical results.
Event-triggered scheduling for pinning networks of coupled dynamical systems under stochastically fast switching
Han, Yujuan; Lu, Wenlian; Chen, Tianping
https://doi.org/10.1049/cth2.12151
Abstract: This paper studies the stability of linearly coupled dynamical systems with feedback pinning algorithms. Here, both the coupling matrix and the set of pinned-nodes are time-varying, induced by stochastic processes. Event-triggered rules are employed in both diffusion coupling and feedback pinning terms, which can reduce the actuation and communication loads. Two event-triggered rules are proposed and it is proved that if the system with time-average couplings and pinning gains is stable and the switching of coupling matrices and pinned nodes is sufficiently fast, the proposed event-triggered strategies can stabilize the system. Moreover, Zeno behaviour can be excluded for all nodes. Numerical examples of networks of mobile agents are presented to illustrate the theoretical results.
Composite control for trajectory tracking of wheeled mobile robots with NLESO and NTSMC
Wang, Haoyu; Zuo, Zhiqiang; Wang, Yijing; Yang, Hongjiu
https://doi.org/10.1049/cth2.12144
Abstract: This paper proposes a control strategy integrating the non-linear extended state observer (NLESO) and the non-singular terminal sliding mode control (NTSMC) for the trajectory tracking of wheeled mobile robots subject to bounded disturbances. A new transformation method of chained model in terms of Lie derivative is presented to simplify the controller design. A specific NLESO combining linear term and non-linear term is designed to estimate the disturbances with a faster convergence performance. A scheme for determining the gain range of NLESO is explicitly given to facilitate the tuning of experimental parameters. Meanwhile, the NTSMC achieves finite time convergence of the tracking error system and the chattering phenomenon in NTSMC is dramatically alleviated with the compensation from NLESO. The experimental results validate the strong robustness and good performance of the proposed control strategy.
