Unfalsified control design using a generalized cost function for a quadrotor

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Azam Hokmabadi ◽  
Mahdi Khodabandeh
Keyword(s):  
Adaptive Control ◽  
Cost Function ◽  
Sliding Mode ◽  
Control Design ◽  
Robust Adaptive Control ◽  
Operating Conditions ◽  
System Model ◽  
Reference Trajectory ◽  
Content Type ◽  
Generalized Cost

Purpose The purpose of this paper is to design a controller for a quadrotor only by using input–output data without a need for the system model. Design/methodology/approach Tracking control for the quadrotor is considered by using unfalsified control, which is one of the most recent strategies of robust adaptive control. The main assumption in unfalsified control design is that there is no access to the system model. Also, ideal path tracking and controlling the quadrotor are been paid attention to in the presence of external disturbances and uncertainties. First, unfalsified control method is introduced which is a data-driven and model-free approach in the field of adaptive control. Next, model of the quadrotor and unfalsified control design for the quadrotor are presented. Second, design of a control bank consisting of four proportional integral derivative controllers and a sliding mode controller is carried out. Findings A particular innovation on an unfalsified control algorithm in this paper is use of a generalized cost function in the hysteresis switching algorithm to find the best controller. Originality/value Finally, the performance and robustness of the designed controllers are investigated by simulation studies in various operating conditions including reference trajectory changes, facing to wind disturbance, uncertainty of the system and changes in payload, which show acceptable performances.

Part 1: robust adaptive control of quadrotor with disturbance observer

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nigar Ahmed ◽  
Abid Raza ◽  
Rameez Khan
Keyword(s):  
Adaptive Control ◽  
Disturbance Observer ◽  
Control Method ◽  
Sliding Mode ◽  
External Disturbance ◽  
Robust Adaptive Control ◽  
External Disturbances ◽  
Content Type ◽  
Control Objective ◽  
Robust Adaptive

Purpose The aim of this paper is to design a nonlinear disturbance observer-based control (DOBC) method obtained by patching a control method developed using a robust adaptive technique and a DO. Design/methodology/approach For designing a DOBC, initially a class of nonlinear system is considered with an external disturbance. First, a DO is designed to estimate the external disturbances. This estimate is combined with the controller to reject the disturbances and obtain the desired control objective. For designing a controller, the robust sliding mode control theory is used. Furthermore, instead of using a constant switching gain, an adaptive gain tuning criterion is designed using Lyapunov candidate function. To investigate the stability and effectiveness of the developed DOBC, stability analysis and simulation study are presented. Findings The major findings of this paper include the criteria of designing the robust adaptive control parameters and investigating the disturbance rejection when robust adaptive control based DOBC is developed. Practical implications In practice, the flight of quadrotor is affected by different kind of external disturbances, thus leading to the change in dynamics. Hence, it is necessary to design DOBCs based on robust adaptive controllers such that the quadrotor model adapts to the change in dynamics, as well as nullify the effect of disturbances. Originality/value Designing DOBCs based on robust control method is a common practice; however, the robust adaptive control method is rarely developed. This paper contributes in the domain of DOBC based on robust adaptive control methods such that the behavior of controller varies with the change in dynamics occurring due to external disturbances.

Robust adaptive control and observer for a robot with pneumatic actuators

Robotica ◽  
2002 ◽  
Vol 20 (2) ◽  
pp. 167-173 ◽  
Author(s):  
F. Errahimi ◽  
H. Cherrid ◽  
N. K. M'Sirdi ◽  
H. Abarkane
Keyword(s):  
Adaptive Control ◽  
Sliding Mode ◽  
Upper Bounds ◽  
Robust Adaptive Control ◽  
Physical Parameters ◽  
Convergence Conditions ◽  
Pneumatic Actuators ◽  
Precise Knowledge ◽  
Robot Leg ◽  
Robust Adaptive

In this paper, the robust adaptive control and observer are considered for a pneumatic robot leg. This approach does not require a precise knowledge of the robot model physical parameters, only the adaptive upper bounds on the norm of the matrices model are used, which with the sliding mode guarantee the robustness of system. Convergence conditions and simulation results for the adaptive control and observer are presented.

Novel design of an optimized synergetic control for dual stator induction motor

2019 ◽  
Vol 38 (6) ◽  
pp. 1828-1845
Author(s):  
Hossine Guermit ◽  
Katia Kouzi ◽  
Sid Ahmed Bessedik
Keyword(s):  
Induction Motor ◽  
Sliding Mode ◽  
Optimal Parameter ◽  
Control Strategies ◽  
Pso Algorithm ◽  
Operating Conditions ◽  
Content Type ◽  
Control Approach ◽  
Simulation Results ◽  
Synergetic Control

Purpose This paper aims to present a contribution to improve the performance of vector control scheme of double star induction motor drive (DSIM) by using an optimized synergetic control approach. The main advantage of synergetic control is that it supports all parametric and nonparametric uncertainties, which is not the case in several control strategies. Design/methodology/approach The suggested controller is developed based on the synergistic control theory and the particle swarm optimization (PSO) algorithm which allow to obtain the optimal parameter of suggested controller to improve the performance of control system. Findings To show the benefits of proposed controller, a comparative simulation results between conventional PI controller, sliding mode controller and suggested controller were carried out. Originality/value The obtained simulation results illustrate clearly that synergetic controller ensures a rapid response, asymptotic stability of the closed-loop system in the all range operating condition and system robustness in presence of parameter variation in all range of operating conditions.

Special Issue on 2nd International Conference on Recent Advances in Mechatronics (ICRAM'99)

2000 ◽  
Vol 12 (3) ◽  
pp. 193-193
Author(s):  
Toshiro Noritsugu ◽  
Keyword(s):  
Adaptive Control ◽  
Mobile Robots ◽  
Motion Control ◽  
Control Design ◽  
Robust Adaptive Control ◽  
Magnetic Suspension ◽  
Special Issue ◽  
Mechatronic Systems ◽  
Recent Advances ◽  
Systems Control

ICRAM'99 has been organized by UNESCO Chair on Mechatronics and Mechatronics Research and Application Center of Bogazici University, Istanbul in Turkey, during 24-26 May 1999, co-sponsored by IEEE (Institute of Electrical and Electronics Engineers) Industrial Electronics Society and IEEE Robotics and Automation Society. The purpose of this conference is to provide an international forum for the discussion on the most recent advances in the field of mechatronics. The program of the conference contains three kinds of papers, 4 plenary papers, 44 long papers and 90 regular papers. The long papers have been published by Springer-Verlag (ISBN 981-4021-34-2), under the name Recent Advances in Mechatronics (Eds. Okyay Kaynak, Sabri Tosunoglu and Marcelo Ang Jr.). The long papers have been presented in the following 12 sessions: Advances in Robotics, Motion control 1, Intelligent Techniques in Mechatronics 1, Virtual Techniques and Telecommanding, Robust Adaptive Control, Design of Mechanical System 1, Fault Detection and Inspection 1, Motion Control 2, Intelligent Techniques in Mechatronics 2, Analysis of Mechatronic Systems, Mobile Robots 1 and Biomedical Applications. For the regular papers, Modeling and Simulation, Trajectory Planning and Control, Variable-Structure Control Systems, Control of Mechatronic Systems, Production Automation, Machine Vision, Adaptive Control, Design of Mechatronic Systems 2, Measurement Technology, Intelligent Systems, Control of Robot Manipulators, Flexible Manufacturing Systems, Education and Training in Mechatronics, Neural Networks and Applications, Fuzzy Systems, Hydraulic and Pneumatic Applications, Mobile Robots 2, Control Applications and Sensors and Actuators. The papers have been submitted to the conference from 30 countries in the world. From Japan 14 papers have been presented, one plenary paper, S long papers and 8 regular papers. This special issue comprises 10 papers edited from the conference papers contributed from Japan. Each paper has been revised and updated for this issue from the original conference paper to describe the recent status of research and development of mechatronics in Japan. The included papers are concerned with some important and attractive subjects such as mobile robot, robot behavior evolution, nanoelectromechanical system, magnetic suspension, human symbiotic robot, stereovision, force control of robot, soft pneumatic actuator and so on. I would like to thank all the authors for their valuable contributions to this issue.

Nonlinear adaptive sliding mode tracking control of an airplane with wing damage

2017 ◽  
Vol 232 (8) ◽  
pp. 1405-1420 ◽  
Author(s):  
D Asadi ◽  
SA Bagherzadeh
Keyword(s):  
Adaptive Control ◽  
Flight Control ◽  
Control Strategy ◽  
Sliding Mode ◽  
Robust Adaptive Control ◽  
Adaptive Sliding Mode Control ◽  
Damage Effect ◽  
Outer Loop ◽  
Adaptive Sliding Mode ◽  
Wing Damage

This paper investigates a dual-timescale autopilot for a wing-damaged airplane applying nonlinear adaptive sliding mode approach. The adaptive flight control strategy is used to track outer-loop angle commands while accommodating wing damage effect. Two distinct adaptive sliding mode control strategies are designed for the inner- and outer-loop dynamics. The airplane nonlinear model is developed considering center of gravity shift and aerodynamic changes due to the asymmetric wing damage. The performance of the proposed nonlinear adaptive sliding mode controller is evaluated through numerical simulation on NASA generic transport model and is compared with two adaptive algorithms: model reference adaptive control and a robust adaptive control strategy. The results demonstrate that the proposed control law achieves closed-loop stability in the presence of wing damage and accelerometers bias, and also provides satisfactory tracking performance.

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