Results 51 to 60 of about 584 (163)
IET Intelligent Transport Systems, Volume 20, Issue 1, January/December 2026.ABSTRACT Off‐road path planning and navigation often struggle with complex challenges, such as diverse surface conditions that demand adaptability, stability‐sensitive vehicle dynamics on low‐adhesion terrain, and the persistent trade‐off between real‐time performance and path quality.
Jiang Song +3 more
wiley +1 more source
BrodogradnjaA novel hybrid adaptive control method is presented for trajectory tracking of remotely operated underwater vehicles (ROVs) that addresses unknown disturbances and model uncertainties in this paper.
Yi Zhang +4 more
doaj +1 more source
Nonlinear Model Predictive Control for Series-Parallel Hybrid Electric Buses
IEEE Access, 2019 In the trend of urgent demand of energy saving for public transportation, the series-parallel plug-in hybrid electric bus (SPPHEB) with energy saving potential is proposed.
Biao Liu +3 more
doaj +1 more source
A Survey: Energy Optimisation Approaches in Urban Rail Systems (AI‐Based and Non‐AI‐Based)
IET Intelligent Transport Systems, Volume 20, Issue 1, January/December 2026.This article presents a systematic review of energy optimisation strategies for urban rail systems, covering speed profile, timetable, regenerative braking, energy storage and power‐supply optimisation. We synthesise methodological trends and reported energy‐saving performance across AI‐based and non‐AI approaches.
Cakra Adipura Wicaksana +2 more
wiley +1 more source
International Transactions on Electrical Energy Systems, Volume 2026, Issue 1, 2026.Residential microgrids that couple photovoltaic generation with lithium‐ion storage must curtail electricity expenditure while preserving battery health. Economic model predictive control (EMPC) is widely used for this task, yet a fixed formulation forces an unsatisfactory compromise: high‐fidelity models shrink linearization error but breach real‐time
Pavel Vedel, Lukas Hubka, Santi A. Rizzo
wiley +1 more source
Practical Nonlinear Model Predictive Control With Kolmogorov–Arnold Network Models
IEEE AccessThis paper presents a novel approach to practical nonlinear model predictive control (PNMPC) using Kolmogorov–Arnold networks (KANs) as prediction models.
Bernardo Barancelli Schwedersky +1 more
doaj +1 more source
IEEE Access, 2019 This paper investigates a nonlinear-model-predictive-control (NMPC)-strategy-based distributed leader-follower consensus multi-robot formation system. The control objective of this system is to design a group of nonholonomic robots to converge into the ...
Hanzhen Xiao, C. L. P. Chen
doaj +1 more source
International Journal of Aerospace Engineering, Volume 2026, Issue 1, 2026.This paper presents an optimal trajectory‐following guidance law for a gliding aerial vehicle, which integrates a receding horizon scheme with an indirect Gauss pseudospectral approach. By formulating the error dynamics of the trajectory‐following problem, an optimal guidance control framework is established.
Qi Chen +3 more
wiley +1 more source
Journal of Control Science and Engineering, Volume 2026, Issue 1, 2026.To address adaptive trajectory control under external disturbances and state constraints, this paper proposes a PSO–FAS–MPC control framework that integrates a fully actuated system, model predictive control, and particle swarm optimization. FAS is used to linearize the system and simplify the MPC design; MPC optimizes the tracking performance under ...
Shijie Zhang +6 more
wiley +1 more source
Advances in Mechanical EngineeringTo address the issue that traditional Nonlinear Model Predictive Control (NMPC), which employs a fixed prediction horizon, struggles to simultaneously satisfy the requirements for both tracking accuracy and real-time performance, this study proposes a ...
Mingjun Liu +3 more
doaj +1 more source