This paper proposes a coordinated energy management framework for plug-in electric vehicle (EV) charging and discharging that minimizes operational cost while preserving grid stability under uncertain user behavior. The uncertainty of charging demand is represented through stochastic initial state-of-charge (SOC) levels, which capture the variability of EV energy requirements upon arrival. Based on this uncertainty representation, an optimization model incorporating battery dynamics, time-of-use (TOU) pricing, vehicle-to-grid capability, mobility constraints, and peak demand limits is formulated. To solve the resulting nonlinear optimization problem, the Grey Wolf Optimization (GWO) algorithm is employed and benchmarked against Genetic Algorithm (GA), Non-dominated Sorting Genetic Algorithm-II (NSGA-II), and Particle Swarm Optimization (PSO) Algorithm. Simulation studies conducted on a fleet of EVs over a 24-hour scheduling horizon demonstrate that the proposed framework maintains SOC within the safe operating range while ensuring that all vehicles satisfy the departure SOC target.
D. C. Huynh, Loc D. Ho, M. Dunnigan· 2026 6th International Confe...· 0 citations
Contact-based industrial inspection requires aerial platforms to maintain stable interaction while rejecting disturbances. Underactuated aerial manipulators present control challenges due to the dynamic coupling between vehicle attitude and force generation. This paper proposes a robust control framework for an underactuated hexarotor equipped with a 1-DoF manipulator to perform sustained contact inspection. The architecture integrates integral-augmented Sliding Mode Control (SMC) for trajectory tracking with an admittance control law for force regulation. The contact force is mapped to a feedforward attitude term, while the 1-DoF arm actively compensates for the tilt to maintain surface alignment. Software-in-the-loop simulations demonstrate that the SMC-based approach achieves superior tracking and coupling rejection compared to traditional PID. Furthermore, the interaction strategy achieved precise force regulation with an RMSE of 0.12N and was able to stably exert up to 20N force, confirming the system's efficacy for stable, reliable contact-based inspection.
Tareq Aziz Hasan Alqutami, Yvan R. Pétillot, M. Dunnigan et al.· 0 citations
