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.

scholarly journals Minimization of Machine Idle Time and Penalty Cost in Flexible Manufacturing System Scheduling

2019 ◽  
Vol 8 (6) ◽  
pp. 483-487
Keyword(s):  
Objective Function ◽  
Flexible Manufacturing ◽  
Manufacturing System ◽  
Flexible Manufacturing System ◽  
Cuckoo Search ◽  
Scheduling Problem ◽  
Jaya Algorithm ◽  
Penalty Cost ◽  
Paper Address ◽  
Better Than

This paper address the application of Jaya algorithm to solve Multi objective scheduling problem in Flexible Manufacturing System(FMS) to Minimize the Combined Objective Function(COF) Value. The effectiveness of this algorithm is tested on the problem of 43 jobs processed on 16 machines taken from literature. The MATLAB code is written to find best sequence and Combined Objective Function value by implementing Jaya Algorithm. Results obtained by Jaya Algorithm are compared with different algorithms such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Shortest Processing Time (SPT), Cuckoo Search (CS) and Modified Cuckoos Search (MCS) for the problem considered. It is observed from the results that COF value for the sequence obtained by Jaya Algorithm is better than other algorithms. It is concluded that the Jaya algorithm is best suitable for solving the Scheduling problem considered in Flexible Manufacturing System.

scholarly journals Optimization of water productivity in Bhagwanpur distributary command of India employing TLBO and cuckoo search algorithms

Water Policy ◽  
2021 ◽  
Author(s):  
Ashruti Upadhyaya ◽  
Ashutosh Upadhyaya
Keyword(s):  
Objective Function ◽  
Water Productivity ◽  
Cuckoo Search ◽  
Cropping Pattern ◽  
Net Return ◽  
Teaching Learning Based Optimization ◽  
Optimum Productivity ◽  
Teaching Learning ◽  
Optimum Water ◽  
Better Than

Abstract Efficient and judicious use of land and water is the need of the hour. In other words, evolving a cropping pattern, which optimizes productivity or net return considering prevailing constraints is quite useful to farmers, because such a cropping pattern is expected to be better than the existing cropping pattern in terms of yielding optimum productivity or net return. A single objective problem consisting of an objective function of optimization of water productivity with prevailing constraints was formulated and three optimization algorithms, namely (i) LINPROG, (ii) teaching learning based optimization (TLBO) and (iii) cuckoo search (CS) were employed to compute optimum water productivity corresponding to various affinity levels. It was observed that all three approaches yielded exactly the same values of water productivity at different affinity levels. TLBO showed better convergence capability as it reached the optimum value of objective function at a lower number of iterations than CS technique. Optimum water productivity at 20% affinity level seems quite practical and reasonable to be recommended in this distributary command for adoption because water productivity value is 2.57 times higher with 98.25 ha less cropped area as compared to the value of water productivity for the existing cropping pattern.

scholarly journals Modified shuffled frog leaping algorithm optimized control for air-breathing hypersonic flight vehicle

2016 ◽  
Vol 13 (6) ◽  
pp. 172988141667813 ◽  
Author(s):  
Bingbing Liang ◽  
Ziyang Zhen ◽  
Ju Jiang
Keyword(s):  
Control System ◽  
Flight Control ◽  
Control Method ◽  
Hypersonic Vehicle ◽  
Pid Controllers ◽  
Flight Control System ◽  
Shuffled Frog Leaping Algorithm ◽  
Air Breathing ◽  
Nature Inspired Algorithm ◽  
Shuffled Frog Leaping

This article addresses the flight control problem of air-breathing hypersonic vehicles and proposes a novel intelligent algorithm optimized control method. To achieve the climbing, cruising and descending flight control of the air-breathing hypersonic vehicle, an engineering-oriented flight control system based on a Proportional Integral Derivative (PID) method is designed for the hypersonic vehicle, which including the height loop, the pitch angle loop and the velocity loop. Moreover, as a variant of nature-inspired algorithm, modified shuffled frog leaping algorithm is presented to optimize the flight control parameters and is characterized by better exploration and exploitation than the standard shuffled frog leaping algorithm. A nonlinear model of air-breathing hypersonic vehicle is used to verify the dynamic characteristics achieved by the intelligent flight control system. Simulation results demonstrate that the proposed swarm intelligence optimized PID controllers are effective in achieving better flight trajectory and velocity control performance than the traditional controllers.

Position and Force Control of Micromanipulatorwith Six Degrees of Freedom Using Piezoelectric Actuators

1991 ◽  
Vol 3 (1) ◽  
pp. 34-40 ◽  
Author(s):  
Toshio Fukuda ◽  
◽  
Motohiro Fujiyoshi ◽  
Fumihito Arai ◽  
Hideo Matsuura ◽  
...  
Keyword(s):  
Force Control ◽  
Fuzzy System ◽  
Degrees Of Freedom ◽  
Force Feedback ◽  
Piezoelectric Actuators ◽  
Feedback System ◽  
Six Degrees Of Freedom ◽  
Variable Gain ◽  
And Control ◽  
Better Than

This paper deals with the mechanism and control of a micromanipulator with six degrees of freedom (6 D.O.F.) aimed at applications in biotechnology and microsurgery. Since operations in these fields develop rapidly and are complicated, a dexterous micromanipulation system has long been desired. This paper proposes a 6 D.O.F micromanipulator to make such work easier. The manipulator has the following features: (1) The manipulator has 6 D.O.F. The tip of this manipulator can move along three axes, and also can rotate along each axis. (2) This micromanipulator is very small and light, since it is made of PZT actuators. (3) Since it has a position and force feedback system, it can control desired poses and forces. (4) A variable gain feedback system, similar to a fuzzy system, is employed here, and hence the system performs better than a fixed gain feedback system. These technical merits will make it possible to operate the micromanipulator in much more complicated environments under a microscope.

scholarly journals Smart aerosonde UAV longitudinal flight control system based on genetic algorithm

2021 ◽  
Vol 10 (5) ◽  
pp. 2433-2441
Author(s):  
Ahmed Elbatal ◽  
Ahmed Medhat Youssef ◽  
Mohamed M. Elkhatib
Keyword(s):  
Genetic Algorithm ◽  
Control System ◽  
Flight Control ◽  
Pid Controller ◽  
Parameters Optimization ◽  
Flight Control System ◽  
Pid Algorithm ◽  
Controller Performance ◽  
Self Tuning ◽  
Better Than

Synthesis of a flight control system for such an aircraft that achieves stable and acceptable performance across a specified flying envelope in the presence of uncertainties represents an attractive and challenging design problem. This study uses the genetic self-tuning PID algorithm to develop an intelligent flight control system for the aerosonde UAV model. To improve the system's transient responses, the gains of the PID controller are improved using a genetic algorithm (GA). Simulink/MATLAB software is used to model and simulate the proposed system. The proposed PID controller integrated with the GA is compared with the classical one. Three simulation scenarios are carried out. In the first scenario, and at normal conditions, the proposed controller performance is better than the classical one. While in the second scenario, identical results are achieved from both controllers. Finally, in the third scenario, the PID controller with GA shows the robustness and durability of the system compared with the classical PID in presence of external wind disturbance. The simulation results prove the system parameters optimization.

Design and Evaluation of a Damage-Tolerant Flight Control System

2005 ◽  
Vol 219 (4) ◽  
pp. 341-359 ◽  
Author(s):  
R A Hess ◽  
T K Vetter ◽  
S R Wells
Keyword(s):  
Control System ◽  
Mach Number ◽  
Flight Control ◽  
Degrees Of Freedom ◽  
Sliding Mode ◽  
Control Law ◽  
Flight Control System ◽  
Design Challenge ◽  
Robust Flight Control ◽  
Damage Tolerant

The performance and stability requirements for a robust flight control system design are presented in the form of a ‘design challenge.’ The challenge includes description of specific vehicle failures that are to be accommodated by the flight control system. The vehicle chosen for the design is the innovative control effector vehicle, and both longitudinal and lateral/directional degrees of freedom are included. Two flight conditions are considered: Mach number 0.3 and altitude 15 000 ft; Mach number 0.9 and altitude 35 000 ft. No scheduling of the flight control law is permitted in the design. After the performance and stability requirements are described, a solution to the design challenge is presented in the form of a sliding-mode control system offered as an alternative to reconfigurable designs. The performance of this system is then evaluated through analysis and computer simulation, including significant failures and damage.

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