Cable-suspended load lifting by a quadrotor UAV: hybrid model, trajectory generation, and control

This work is intended to give an overview of technologies, developed from an artificial intelligence standpoint, devised to face the different planning and control problems involved in trajectory generation for mobile robots. The purpose of this analysis is to give a current context to present the Evolutionary Robotics approach to the problem, which is now being considered as a feasible methodology to develop mobile robots for solving real life problems. This chapter also show the authors’ experiences on related case studies, which are briefly described (a fuzzy logic based path planner for a terrestrial mobile robot, and a knowledge-based system for desired trajectory generation in the Geosub underwater autonomous vehicle). The development of different behaviours within a path generator, built with Evolutionary Robotics concepts, is tested in a Khepera© robot and analyzed in detail. Finally, behaviour coordination based on the artificial immune system metaphor is evaluated for the same application.

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Integrated Planning and Control for Collision-free Trajectory Generation in 3D Environment with Obstacles

2019 19th International Conference on Control, Automation and Systems (ICCAS) ◽

10.23919/iccas47443.2019.8971490 ◽

2019 ◽

Cited By ~ 2

Author(s):

Xiaoxue Zhang ◽

Jun Ma ◽

Sunan Huang ◽

Zilong Cheng ◽

Tong Heng Lee

Keyword(s):

Trajectory Generation ◽

Integrated Planning ◽

Planning And Control ◽

3D Environment ◽

And Control

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Hybrid modelling and predictive control of utility-scale variable-speed variable-pitch wind turbines

Transactions of the Institute of Measurement and Control ◽

10.1177/0142331219895117 ◽

2020 ◽

Vol 42 (9) ◽

pp. 1724-1739 ◽

Cited By ~ 1

Author(s):

Mohammed Moness ◽

Ahmed Mahmoud Moustafa

Keyword(s):

Hybrid Model ◽

Predictive Control ◽

Mixed Integer ◽

Innovative Methods ◽

Complex Design ◽

Reliable Source ◽

Scale Variable ◽

And Control ◽

Utility Scale ◽

Systems Framework

Wind energy has proven to be the highest reliable source of renewables due to the maturity of the technology. Wind turbine (WT) systems are complex systems with undergoing development process that requires innovative methods of design and control. In this paper, WTs are studied through hybrid systems framework. Hybrid models of WT are extracted with representable dynamics from nonlinear complex design code. The WT model is formulated into a mixed-logical dynamical model (MLD) and a piecewise affine (PWA) model. Then, a receding horizon control strategy is applied to WT hybrid model resulting in a hybrid model predictive control (HMPC) with mixed-integer programming (MIP) problem. The performance of the proposed controller is compared against the baseline controller within a simulation environment for the National Renewable Energy Laboratory (NREL) 5MW benchmark WT as a case study. The analysis and investigation of HMPC highlight its capability as a potential tool for exploiting the control objectives of WT systems.

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