Asian Journal of Control最新文献

This paper studies the controllability of multi-agent systems with directed and matrix-valued weighted networks. Almost equitable partition theory is increasingly being chosen by researchers as a framework for controllability of multi-agent systems from graph-theoretic perspective. Based on the matrix-valued almost equitable partition, we propose a graph-theoretic characterization of the upper bounds of dimension of controllable subspace. Then, we provide graph-theoretic necessary conditions for controllability and methods of constructing uncontrollable topologies. Several examples are given to illustrate these results.

This research focuses on the stability of discrete-time Markovian jump neural networks with time-varying delays. To this aim, a nonorthogonal free-matrix-based summation inequality (NFMSI) is proposed by constructing nonorthogonal polynomials with auxiliary scalars as well as auxiliary vectors. The NFMSI can avoid time-varying delays in the denominator and prevent the loss of some coupling information compared to exiting summation inequalities. Then, an ameliorative stability criterion is derived by utilizing the NFMSI and other estimation method. Finally, the advantage of the obtained stability criterion is demonstrated by a few numerical examples.

This article focuses on the topic of practical fixed-time prescribed performance control schemes for flexible-joint manipulators with unmodeled dynamics and dead-zones. The computational complexity problem is avoided using dynamic surface control and the command filter technology, which can eliminate filtering errors with compensation mechanism. The influence of dynamical uncertainties is mitigated by an auxiliary signal generated by a first-order system. The input dead-zone is linearized, and prescribed performance is managed using nonlinear mapping. Using the introducing the compact set in stability analysis, all the signals in the closed-loop system are proved to be semiglobally practically fixed-time stable. Finally, the simulation results verify the feasibility of the adaptive control approach.

This paper contributes to the design of a robust control strategy for the trajectory tracking problem in constrained and perturbed unicycle mobile robots. The proposed robust control strategy is composed of two controllers: a linear and a nonlinear. The linear control design is based on the barrier Lyapunov function and the attractive ellipsoid method, and it considers the input saturation, the state constraints, and some parameter uncertainties. On the other hand, the nonlinear part is based on an integral sliding-mode control approach that deals with the effect of some matched disturbances and the input saturation constraints. The proposed scheme guarantees asymptotic convergence to zero of the tracking error coping with the system constraints and disturbances. Simulation results are presented in order to show the advantage of the proposed algorithm with respect to an MPC-based robust controller. Some experimental results, using the QBot2 unicycle mobile robot, validate the effectiveness of the proposed robust control strategy.

This paper investigates the distributed optimization filtering problem for nonlinear systems under resource constraints in wireless sensor networks based on T-S fuzzy model. First, Sigma-Delta dynamic quantizers are introduced to dual-quantize the state estimation and measurement signals, decreasing bandwidth consumption. Second, a novel distributed fuzzy estimator with heterogeneous double-subscript gains is constructed using a non-PDC method to solve the problems of immeasurable premise variables and fuzzy asynchronous signals in fuzzy models. Distributed robust estimation method is applied to manage immeasurable premise variables, analyzing the mean-square exponential stability and $��{�H�}_{�\infty �}�$ performance of the estimation error system. Third, the heterogeneous membership functions are optimally selected online using the gradient descent method within the feasible domain to reduce estimation error and improve interference attenuation performance. Finally, a tunnel diode circuit system and a numerical example are utilized to verify the effectiveness and superiority of the proposed method.

We study the practical stability of the integrator switched systems with the constant period time under the cyclic switching laws, of which the switching sequence is cyclic and each cycle's period time is constant. Our aim is to establish significant switching laws which allow us to obtain the individual switching duration sequence for each cycle such that the integrator switched system is practically stable. We develop a new decomposition expression of the switching duration sequences, and show that a switching duration sequence can be divided into two parts: one part contributes to the change of state during the cycle and another one is about the nonnegativity of the duration sequence. Based on the decomposition expression, a sufficient condition for the existence of the switching duration sequences are induced. We propose a switching law which ensures the practical stability of the nominal integrator switched systems with the constant period time. Also, we propose another switching law which ensures the practical stability of the uncertain integrator switched systems and provide an upper bound of the uncertainties. The applicability of two proposed switching laws is illustrated by numerical simulations.

This paper investigates the synchronization of a drive-response system formed by coupling two periodically time-varying Boolean networks (PTVBNs) under state-flipping control. Both synchronous and asynchronous update PTVBNs are taken into consideration. First, sufficient and necessary conditions for synchronization are proposed. Second, two algorithms are provided to find the flip sequence with minimum cardinality, enabling the response system to track the state trajectory of the drive system based on synchronous and asynchronous update schemes. However, the obtained flip sequence is only applicable to the given initial states. Therefore, another algorithm is presented to find the minimum flip set, which is suitable for all initial states. Finally, an example is given to illustrate the effectiveness of the obtained results.

The trajectory tracking control for wheeled mobile robots (WMRs) with unknown longitudinal slipping is studied in this paper. Firstly, the slipping ratios are introduced to describe the slippage and the kinematic model of WMRs is established, which takes the displacement between the center of mass of the WMR and the midpoint of the driving wheels axis into consideration. Then an adaptive control law is proposed based on a new Lyapunov function, and the asymptotic stability of the tracking error system is derived directly by the Barbalat's lemma. Finally, some numerical examples are given to show the advantages and effectiveness of the proposed method.

This paper investigates the predefined-time synchronization of coupled inertial complex-valued neural networks. By employing variable transformation and real-imaginary separation methods, the coupled inertial complex-valued neural networks are transformed equivalently to higher dimensional systems containing only first-order derivatives. An effective controller with a time-dependent variant of the exponential function is designed and sufficient conditions for achieving predefined-time synchronization of coupled inertial complex-valued neural networks are derived. This paper successfully extends existing research on predefined-time synchronization from driven-response inertial complex-valued neural networks to a general class of coupled inertial complex-valued neural networks. Moreover, unlike the sign functions or power functions commonly used in existing studies of predefined-time synchronization, this paper introduces a new time-dependent variant of the exponential function in the controller design. Finally, the validity of the proposed results is verified through a numerical example.

This paper addresses the problem of using aperiodically intermittent control (AIC) to stabilize hybrid stochastic differential equations with pantograph delay (HSDEwPDs). The AIC, which is based on the average control rate, makes the obtained results less conservative. It is noteworthy that the delay type considered in most existing literature, which focuses on delay systems with AIC, is constant delay or bounded time-varying delay, which renders the existing methods ineffective in studying HSDEwPDs with AIC. Thus, a novel Halanay-type inequality lemma is developed to serve HSDEwPDs with AIC. By utilizing the Lyapunov functions and $��M�$-matrix, two sufficient criteria are derived to ensure the exponential stability of HSDEwPDs with AIC. Moreover, the theoretical findings are applied to stochastic pantograph oscillators with Markovian switching. Eventually, a numerical example and associated simulations are offered to check the validity of our theory.