The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Aerial Robot Formation Control via Pigeon-Inspired Optimization
Abstract
Formation flight for aerial robots is a rather complicated global optimum problem. Three formation flight control problems are introduced in this chapter, respectively, underlying controller parameter optimization, basic formation control and formation reconfiguration control. Two methods, Model Prediction Control (MPC) and Control Parameterization and Time Discretization (CPTD), are applied to solve the above problems. However, the selection of appropriate control parameters is still a barrier. Pigeon-Inspired Optimization (PIO) is a new swarm intelligence optimization algorithm, which is inspired by the behavior of homing pigeons. Owning to its better performance of global exploration than others, the thoughts of PIO are applied to the control field to optimize the control parameters in the three aerial robot formation problems, to minimize the value of the cost function. Furthermore, comparative experimental results with a popular population-based algorithm called Particle Swarm Optimization (PSO) are given to show the feasibility, validity and superiority of PIO.
Related Content
|
Rashmi Rani Samantaray, Zahira Tabassum, Abdul Azeez.
© 2024.
32 pages.
|
|
Sanjana Prasad, Deepashree Rajendra Prasad.
© 2024.
25 pages.
|
|
Deepak Varadam, Sahana P. Shankar, Aryan Bharadwaj, Tanvi Saxena, Sarthak Agrawal, Shraddha Dayananda.
© 2024.
24 pages.
|
|
Tarun Kumar Vashishth, Vikas Sharma, Kewal Krishan Sharma, Bhupendra Kumar, Sachin Chaudhary, Rajneesh Panwar.
© 2024.
29 pages.
|
|
Mrutyunjaya S. Hiremath, Rajashekhar C. Biradar.
© 2024.
30 pages.
|
|
C. L. Chayalakshmi, Mahabaleshwar S. Kakkasageri, Rajani S. Pujar, Nayana Hegde.
© 2024.
30 pages.
|
|
Amit Kumar Tyagi.
© 2024.
29 pages.
|
|
|