Optimal Control Applications & Methods

Papers
(The H4-Index of Optimal Control Applications & Methods is 15. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-03-01 to 2025-03-01.)
ArticleCitations
Issue Information47
Issue Information34
Nonlinear optimal control for multi‐DOF robotic manipulators with flexible joints31
Sparse optimal control problems with intermediate constraints: Necessary conditions25
Reactive power management by using a modified differential evolution algorithm25
A New Observer‐Based Resilient Switching LPV Control Method for Spacecraft Fault‐Tolerant Attitude Tracking With Optimal L∞ Performance24
Observer‐Based Preview Sliding Mode Tracking Control of Discrete‐Time T‐S Fuzzy System With Input Saturation24
Quantized optimal output feedback control and optimal triggering signal co‐design for unknown discrete‐time nonlinear systems22
Lagrangian relaxation for continuous‐time optimal control of coupled hydrothermal power systems including storage capacity and a cascade of hydropower systems with time delays20
A novel predictive optimal control strategy for renewable penetrated interconnected power system18
Model‐free inversion‐based iterative learning control algorithm with adaptive gain: Achieving superior robustness and convergence18
Numerical analysis of optimal control problems governed by fourth‐order linear elliptic equations using the Hessian discretization method18
A numerical method for consensus control of leader‐following multi‐agent systems with the input delay16
Observer‐based dynamic ETC optimized tracking of nonlinear systems with stochastic disturbances15
Optimization of time‐varying feedback controller parameters for freeway networks15
A stochastic averaging gradient algorithm with multi‐step communication for distributed optimization15
Optimization of electric power prediction of a combined cycle power plant using innovative machine learning technique15
Robust data‐driven dynamic optimization using a set‐based gradient estimator15
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