Browsing by Author "Afonso, Paulo Alexandre Ferreira"
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- Evolutionary based on selfish and altruism strategies - an approach to path planning problemsPublication . Salgado, Paulo; Igrejas, Getúlio; Afonso, Paulo Alexandre FerreiraThis paper presents a novel hybrid optimization appproach based on a genetic algoritm that combines selfish gene and altruism view of evolution.
- Hybrid PSO-cubic spline for autonomous robots optimal trajectory planningPublication . Salgado, Paulo; Igrejas, Getúlio; Afonso, Paulo Alexandre FerreiraThis paper presents a new version of the Particle Swarm Optimization algorithm where the particles are replaced by spline functions. The developed algorithm generates smooth motion trajectories with two times continuously differentiable curvature avoiding obstacles placed in the workspace. It can be used for autonomous robot path planning or transport problems. The spline based trajectory generation gives us continuous, smooth and optimized path trajectories. Simulation and experimental results demonstrate the effectiveness of the proposed method.
- Long-term memory structure by hierarchized SOMPublication . Salgado, Paulo; Igrejas, Getúlio; Afonso, Paulo Alexandre FerreiraThe most evolved living organisms are characterized by having a sophisticated central nervous system with memorizing capabilities.
- Multi-kalman filter to wind power forecastingPublication . Salgado, Paulo; Igrejas, Getúlio; Afonso, Paulo Alexandre FerreiraWind power forecasting methods are important for the safety of wind renewable energy utilization. However, because wind power is weather dependent and, thus, can be variable and intermittent over different time-scales, it’s difficult to build accurate and robust predictive models. In this context, an accurate model is a relevant contribution for a reliable large-scale wind power integration. This paper explores a new approach using a multi-model Kalman filter to provide an estimate of the average hourly wind speed, in a 24 hours horizon. The K-means algorithm is used to obtain the characteristics curves of wind speed each time the sub-model is used for forecasting. The accuracy of the proposed forecasting model is compared with other statistical methods, namely some that are usually considered suitable, robust and accurate.