This article investigates the quasi-synchronization for fractional multiweighted coupled neural networks (FMCNNs) with discontinuous activation functions and mismatched parameters. First, under the generalized Caputo fractional-order derivative operator, a novel piecewise fractional differential inequality is established to study the convergence of fractional systems, which significantly extends some related published results. Subsequently, by exploiting the new inequality and Lyapunov stability theory, some sufficient quasi-synchronization conditions of FMCNNs are presented by aperiodic intermittent control. Meanwhile, the exponential convergence rate and synchronization error’s bound are given explicitly. Finally, the validity of theoretical analysis is confirmed by numerical examples and simulations.

This article focuses on achieving the finite-time synchronization (FTS) for fractional complex dynamical networks (FCDNs) using hybrid impulsive control. Initially, a novel framework for local FTS is developed, building upon the relaxed inequality ${}_{t_{k}}^{C}D_{t}^{\alpha }V(t) \le \chi V(t) - \eta $ . To expand the attraction domain within the local FTS framework, a piecewise fractional-order differential inequality based on impulsive control systems is proposed. Subsequently, a new hybrid control strategy is designed by integrating a simple feedback controller with an impulsive controller involving a finite number of impulses, which can be accurately calculated using the proposed impulsive degree. Additionally, a set of local/global FTS criteria is formulated, and the settling time can be explicitly estimated. Lastly, an illustrative example is presented to demonstrate the effectiveness of the derived results.

For the sake of realizing dynamic switch among three steering modes for the four wheel independent steering (4WIS) rescue vehicle in the non-stop state, the switch control strategy and the optimized wheel switch trajectory are studied in this paper. Aiming at ensuring the constant turning radius of the 4WIS rescue vehicle in the switch process of steering modes, the steering angle relationships between the driving wheel and driven wheels are derived, and the desired driving wheel angle of the target steering mode is calculated. The B-spline curve is proposed to design the switch trajectory of the driving wheel. Two objectives including minimizing the sudden change of vehicle dynamic parameters and minimizing the energy consumption in the switch process are discussed. A multi-objective genetic algorithm (MOGA) based on non-dominated sorting genetic algorithm II (NSGA-II) is proposed to deal with the optimization problem of the wheel switch trajectory. The numerical simu-lations based on Matlab/Simulink indicate that the presented algorithm can generate the Pareto optimal solutions and is suitable for the optimization of the wheel switch trajectory. In addition, the proposed switch control strategy of steering modes for the 4WIS rescue vehicle in the non-stop state is validated to be reasonable and effective.

In this contribution, the problem of fixed-time stabilization in multi-weighted complex networks via the novel adaptive pinning nonchattering control based on the linear matrix inequality (LMI) method, as well as its application to image protection is addressed. Different from the traditional methods, a novel fixed-time stable form is proposed and the convergence time is estimated based on beta function. Next, utilizing the designed continuous adaptive control strategy, a sufficient LMI condition is presented to ensure the fixed-time stabilization of multi-weighted complex networks. Furthermore, the novel nonchattering adaptive pinning control protocol is given to guarantee the fixed-time stabilization of the system only by controlling a small number of nodes. Note that a scheme of how to select the number of control nodes is put forward accordingly. Finally, the effectiveness of the proposed method is verified by the actual financial model. Meanwhile, a number of encryption experiments are carried out based on three networks, and the mean and variance of the encryption performance are calculated to show the stability and robustness of image encryption different from the existing research works.