Improved cuckoo search approach based optimal proportional-derivative parameters for quadcopter flight control

2022 ◽  
pp. 1-14
Author(s):  
Nada El Gmili ◽  
Mostafa Mjahed ◽  
Abdeljalil Elkari ◽  
Hassan Ayad
Keyword(s):  
Flight Control ◽  
Cuckoo Search ◽  
Search Approach

scholarly journals Quadrotor Identification through the Cooperative Particle Swarm Optimization-Cuckoo Search Approach

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Nada El gmili ◽  
Mostafa Mjahed ◽  
Abdeljalil El kari ◽  
Hassan Ayad
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Dynamic Modelling ◽  
Cuckoo Search ◽  
Parameters Estimation ◽  
Model Parameters ◽  
Swarm Optimization ◽  
Social Thinking ◽  
Quadrotor Uav ◽  
Search Approach

This paper explores the model parameters estimation of a quadrotor UAV by exploiting the cooperative particle swarm optimization-cuckoo search (PSO-CS). The PSO-CS regulates the convergence velocity benefiting from the capabilities of social thinking and local search in PSO and CS. To evaluate the efficiency of the proposed methods, it is regarded as important to apply these approaches for identifying the autonomous complex and nonlinear dynamics of the quadrotor. After defining the quadrotor dynamic modelling using Newton–Euler formalism, the quadrotor model’s parameters are extracted by using intelligent PSO, CS, PSO-CS, and the statistical least squares (LS) methods. Finally, simulation results prove that PSO and PSO-CS are more efficient in optimal tuning of parameters values for the quadrotor identification.

Optimal chiller loading for energy conservation using a new differential cuckoo search approach

Energy ◽  
2014 ◽  
Vol 75 ◽  
pp. 237-243 ◽  
Author(s):  
Leandro dos Santos Coelho ◽  
Carlos Eduardo Klein ◽  
Samrat L. Sabat ◽  
Viviana Cocco Mariani
Keyword(s):  
Energy Conservation ◽  
Cuckoo Search ◽  
Search Approach

scholarly journals Optimised Tuning of a PID-Based Flight Controller for a Medium-Scale Rotorcraft

Algorithms ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 178
Author(s):  
Lindokuhle J. Mpanza ◽  
Jimoh Olarewaju Pedro
Keyword(s):  
Objective Function ◽  
Flight Control ◽  
Degrees Of Freedom ◽  
Cuckoo Search ◽  
Pid Controllers ◽  
Flight Control System ◽  
Forward Flight ◽  
Six Degrees Of Freedom ◽  
Medium Scale ◽  
Better Than

This paper presents the parameter optimisation of the flight control system of a singlerotor medium-scale rotorcraft. The six degrees-of-freedom (DOF) nonlinear mathematical model of the rotorcraft is developed. This model is then used to develop proportional–integral–derivative (PID)-based controllers. Since the majority of PID controllers installed in industry are poorly tuned, this paper presents a comparison of the optimised tuning of the flight controller parameters using particle swarm optimisation (PSO), genetic algorithm (GA), ant colony optimisation (ACO) and cuckoo search (CS) optimisation algorithms. The aim is to find the best PID parameters that minimise the specified objective function. Two trim conditions are investigated, i.e., hover and 10 m/s forward flight. The four algorithms performed better than manual tuning of the PID controllers. It was found, through numerical simulation, that the ACO algorithm converges the fastest and finds the best gains for the selected objective function in hover trim conditions. However, for 10 m/s forward flight trim, the GA algorithm was found to be the best. Both the tuned flight controllers managed to reject a gust wind of up to 5 m/s in the lateral axis in hover and in forward flight.

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