Model Predictive Control Based On Spider monkey optimization Algorithm of Interleaved Parallel Bidirectional DC-DC Converter

Lan, Yueyang; Chen, Qihong; Zhang, Liyan; Long, Rong

doi:10.1109/icarcv50220.2020.9305361

Cited by 3 publications

(1 citation statement)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It involves spider monkeys exploring and exploiting search spaces to find the best solution. SMO is comparable to other advanced algorithms, such as particle swarm optimisation and genetic algorithms, in terms of solution quality and convergence time [28]. However, it requires refinement and validation to ensure its reliability and efficiency for specific optimisation problems.…”

Section: Spider Monkey Optimisation (Smo)mentioning

confidence: 99%

Spider Monkey Metaheuristic Tuning of Model Predictive Control with Perched Landing Stabilities for Novel Auxetic Landing Foot in Drones

Jawahar,

S.N.

et al. 2024

ELEKTRON ELEKTROTECH

View full text Add to dashboard Cite

The study focuses on improving drone landing gear dynamics through an innovative auxetic foot design, leveraging Spider Monkey Optimization for Model Predictive Control adjustment, facilitated by an Arduino-MATLAB interface. The auxetic foot design incorporates materials with a negative Poisson ratio, which allows the foot to expand and enhance energy absorption during landings. This design improves stability and safety during the perched landing process. The SMO-MPC approach is used to optimise the control of the perched landing gear. SMO, inspired by spider monkey search behaviour, optimises auxetic foot control input sequences with the limits of rotational displacement (theta = 30 deg to -30 deg) on the prediction horizon to improve landing gear performance. The real-time implementation of SMO-MPC is achieved through an Arduino-MATLAB interface on quadcopter drone. A comparative analysis is conducted to evaluate the benefits of SMO-MPC compared to conventional MPC methods. The results show that the SMO-MPC approach with auxetic foot design surpasses conventional MPC methods in terms of landing performance with 14.6 % improvement in damping force control and control of aerodynamic stability with pitch of 34.16 %, yaw of 16.87 %, and roll of 31.74 %.

show abstract

Section: Spider Monkey Optimisation (Smo)mentioning

confidence: 99%