Accurate estimation of the state of health (SOH) and remaining useful life (RUL) of lithium-ion batteries (LiBs) is critical for ensuring battery reliability and safety in applications such as electric vehicles and energy storage systems. However, existing methods developed for estimating the SOH and RUL of LiBs often rely on full-cycle charging data, which are difficult to obtain in engineering practice. To bridge this gap, this paper proposes a novel data-driven method to estimate the SOH and RUL of LiBs only using partial charging curve features. Key health features are extracted from the constant voltage (CV) charging process and voltage relaxation, validated through Pearson correlation analysis and SHapley Additive exPlanations (SHAP) interpretability. A hybrid framework combining CatBoost for SOH estimation and particle swarm optimization-support vector regression (PSO-SVR) for RUL estimation is developed. Experimental validation on public datasets demonstrates superior performance of the methodology described above, with an SOH estimation root mean square error (RMSE) and mean absolute error (MAE) below 1.42% and 0.52% and RUL estimation relative error (RE) under 1.87%. The proposed methodology also exhibits robustness and computational efficiency, making it suitable for battery management systems (BMSs) of LiBs.

Rendezvous problem of nonholonomic unicycles has been considered in this paper and nonlinear distributed controllers based on backstepping are constructed to guarantee the consensus of both position and direction simultaneously. Cascaded theory of nonlinear system is utilised to reduce the rendezvous problem of nonholonomic unicycles to consensus problem of moving direction and consensus problem of position, respectively. The uncontrollable challenge of position system after consensus of moving direction has been successfully removed through dilated coordinate transformation. Then, a modified backstepping methodology based on the coupling structure of position system is derived to guarantee the consensus of each unicycle's position. In the end, not only consensus of position but also consensus of direction has been realised for multiple nonholonomic unicycles using the controllers proposed in this paper. Simulation results using Matlab illustrate the effectiveness of the results of this paper.

In complex environments, many distributed networked systems can only be illustrated with fractional-order dynamics. When multi-agent systems show individual diversity with difference agents, heterogeneous (integer-order and fractional-order) dynamics are used to illustrate the agent systems and compose integerfractional compounded-order systems. Applying Laplace transform and frequency domain theory of the fractional-order operator, the consensus of delayed multi-agent systems with directed weighted topologies is studied. Since an integer-order model is the special case of a fractional-order model, the results in this paper can be extended to systems with integer-order models. Finally, numerical examples are used to verify our results.

This letter considers the problem of globally finite-time stabilizing a planar nonlinear system with a mismatched unknown disturbance. First, a nonlinear integral dynamic is constructed to compensate the disturbance. For finite-time convergence, we use the system states and integral state to construct a new controller which not only is homogeneous with a negative degree but also contains a linear combination of states to handle the unmatched disturbance. The finite-time integral controller originally obtained for a linear planar system is appropriately scaled to regulate a nonlinear planar system within the framework of homogeneous domination. In addition, for a faster convergence speed for any initial condition, a dual-mode integral controller is introduced with better performances demonstrated by simulation studies.