PD Controller With Self Adaptive Gains for Quadrotor Waypoint Navigation

2020 ◽  
Author(s):  
Madhavan Sudakar ◽  
Siddharth Sridhar ◽  
Manish Kumar
Keyword(s):  
Control Algorithm ◽  
Degrees Of Freedom ◽  
Simple Structure ◽  
Reference Model ◽  
Pd Controller ◽  
Lyapunov Stability Analysis ◽  
Waypoint Navigation ◽  
Novel Method ◽  
Model Reference Adaptive ◽  
Random Gain

Abstract Proportional-Derivative (PD) controllers are commonly used in quadrotors due to their simple structure. Tuning of the gains of the PD controller is often cumbersome due to strong coupling of the dynamics between three linear and three angular degrees of freedom. This paper presents a novel method of auto adjusting the proportional and derivative gains of the quadrotor without the use of any stable reference model (unlike model reference adaptive control). The gains are automatically adjusted throughout the flight based on just the state errors. Lyapunov stability analysis and adaptive gain law is used to formulate the control algorithm to achieve way point navigation. It is shown that our proposed controller achieves effective way point navigation even when started off from random gain values.

Modeling and Controlling the Dynamic Behavior of an Aerial Manipulator

2021 ◽  
pp. 2150044
Author(s):  
Zain Anwar Ali ◽  
Li Xinde
Keyword(s):  
Dynamic Behavior ◽  
Control Algorithm ◽  
Degrees Of Freedom ◽  
Control Mechanism ◽  
Hybrid Control ◽  
External Noise ◽  
Pole Placement ◽  
Aerial Manipulator ◽  
Aerial Vehicle ◽  
Model Reference Adaptive

Unmanned Aerial Vehicles (UAVs) installed with a gripper is an effective and robust way to grab the wanted object from inaccessible locations. In this study, we develop a novel control mechanism to regulate the nonlinear dynamics of the aerial manipulator. In this research, hex-rotor UAV is chosen in order to fulfill the mission requirement in terms of size and weight of the object. It is equipped with a manipulator and the gimbal-based camera that will help to see the desired object and then transport it. The aerial vehicle has six-degrees-of-freedom (6-DOF) and the installed manipulator has 4-DOF which in total makes the 10-DOF aerial manipulator vehicle. At the time of clutching the desired object to eliminate or reduce the external noise, and stabilize the dynamic behavior of the aerial manipulator, we need a robust and efficient controller. To solve the aforementioned problems, this study develops a hybrid control mechanism that tracks and controls the altitude and attitude of UAV after clutching the desired object. The main contribution of this study is to design a control mechanism that includes Model Reference Adaptive Control with an Integrator (MRACI) in conjunction with regulation, pole-placement and tracking (RST) control algorithm. On one hand, the simulation results using MATLAB demonstrate the efficiency of the proposed control mechanism. On the other hand, to cross verify the validity of the proposed control algorithm, we perform the experiment by clutching the desired object at hovering and normal flight operation.

Model-Reference Based Adaptive Control for Enhancing Lateral Stability of Car-Trailer Systems

2016 ◽  
Author(s):  
Smitha Vempaty ◽  
Eungkil Lee ◽  
Yuping He
Keyword(s):  
Adaptive Control ◽  
Degrees Of Freedom ◽  
Reference Model ◽  
Model Reference Adaptive Control ◽  
Operating Conditions ◽  
Model Parameters ◽  
Lateral Stability ◽  
Model Reference ◽  
Control Approach ◽  
Model Reference Adaptive

This paper presents a model reference adaptive control (MRAC) approach to enhance the lateral stability of car-trailer systems. To this end, a 3 degrees of freedom (DOF) linear yaw-plane car-trailer model was developed as a “reference model”. The yaw rate of leading and trailing units of the reference model were used as the target states to control and stabilize a virtual vehicle plant represented by a 5 DOF linear yaw-roll car-trailer model. A Lyapunov-based controller was designed to handle the lateral stability of the car-trailer dynamical system. The model parameters and operating conditions of the system were predefined while designing the controller. The effectiveness of the adaptive controller for improving the lateral stability of car-trailer systems was demonstrated under a simulated multiple cycle sine-wave steering input maneuver. It was observed that the lateral stability of car-trailer system was improved by controlling respective yaw rates of the car and the trailer, using model reference adaptive control approach in conjunction with Lyapunov stability criterion.

Minimal Control Synthesis-Skyhook Mixed Control for Magneto-Rheological Semi-Active Suspension

2014 ◽  
Vol 1044-1045 ◽  
pp. 811-817
Author(s):  
Jin Qiu Zhang ◽  
Da Shan Huang ◽  
Zhi Zhao Peng ◽  
Guang Lei Zhang
Keyword(s):  
Control Algorithm ◽  
Ride Comfort ◽  
Reference Model ◽  
Active Suspension ◽  
Control Synthesis ◽  
Control Law ◽  
Suspension Parameters ◽  
Mixed Control ◽  
Magneto Rheological ◽  
Model Reference Adaptive

Standard skyhook control algorithm is inefficient in controlling of the parameter-varying magneto-rheological semi-active suspension system. Based on model reference adaptive control theory, a minimal control synthesis-skyhook (MCS-SH) mixed control algorithm was designed. Ideal skyhook control was taken as the reference model; the feedback control law of MCS algorithm was improved based on the feature of magneto-rheological damper (MRD). The results illustrate that the sprung mass acceleration and suspension deflection are decreased through MCS-SH algorithm, the ride comfort of vehicles can be improved significantly, and the MCS-SH algorithm can adapt to the variation of suspension parameters.

Optimal Model Reference Control Scheme Design for Nonlinear Strict-Feedback Systems

2020 ◽  
Vol 38 (9A) ◽  
pp. 1342-1351
Author(s):  
Musadaq A. Hadi ◽  
Hazem I. Ali
Keyword(s):  
Reference Model ◽  
Feedback System ◽  
Optimization Method ◽  
Feedback Systems ◽  
Model Reference ◽  
Scheme Design ◽  
Model Reference Control ◽  
Control Scheme ◽  
Lyapunov Stability Analysis ◽  
Strict Feedback

In this paper, a new design of the model reference control scheme is proposed in a class of nonlinear strict-feedback system. First, the system is analyzed using Lyapunov stability analysis. Next, a model reference is used to improve system performance. Then, the Integral Square Error (ISE) is considered as a cost function to drive the error between the reference model and the system to zero. After that, a powerful metaheuristic optimization method is used to optimize the parameters of the proposed controller. Finally, the results show that the proposed controller can effectively compensate for the strictly-feedback nonlinear system with more desirable performance.

Multimode Adaptive Control for Tank Gun Control System Based on Tracking Differentiator

2011 ◽  
Vol 383-390 ◽  
pp. 79-85
Author(s):  
Dong Yuan ◽  
Xiao Jun Ma ◽  
Wei Wei
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
High Speed ◽  
Control Method ◽  
Reference Model ◽  
Gun Control ◽  
Math Model ◽  
Tracking Differentiator ◽  
Switch Control ◽  
Model Reference Adaptive

Aiming at the problems such as switch impulsion, insurmountability for influence caused by nonlinearity in one tank gun control system which adopts double PID controller to realize the multimode switch control between high speed and low speed movement, the system math model is built up; And then, Model Reference Adaptive Control (MRAC) method based on nonroutine reference model is brought in and the adaptive gun controller is designed. Consequently, the compensation of nonlinearity and multimode control are implemented. Furthermore, the Tracking Differentiator (TD) is affiliated to the front of controller in order to restrain the impulsion caused by mode switch. Finally, the validity of control method in this paper is verified by simulation.

Adaptive Control of Mechanical Gas Face Seals With Rotor Runout and Static Stator Misalignment

2010 ◽  
Vol 132 (4) ◽  
Author(s):  
Haojiong Zhang ◽  
Robert G. Landers ◽  
Brad A. Miller
Keyword(s):  
Adaptive Control ◽  
Degrees Of Freedom ◽  
Equations Of Motion ◽  
Control Technique ◽  
Estimation Errors ◽  
Adaptive Controllers ◽  
Gas Leakage ◽  
Robust Model ◽  
Robust Adaptive ◽  
Model Reference Adaptive

This paper presents a control methodology that utilizes a robust model reference adaptive control technique to regulate the dynamic behavior of a coned mechanical gas face seal system in a flexibly mounted stator configuration. Individual adaptive controllers are designed for the three stator rigid body degrees of freedom based on the linear portions of their respective equations of motion. The force and moments generated within the gas film are estimated using Kalman filter-based estimators and directly cancelled in the control algorithm using offset control signals. The estimation errors are considered as bounded disturbances to the seal system and are taken into account by the robust adaptive controllers. Simulation results show that the controllers effectively stabilize the stator motion and control the stator tilts to synchronously track the rotor runout with near-zero relative misalignment magnitude and phase shift, thus, minimizing gas leakage.

High-Sideslip Model Reference Adaptive Flight Control for Aileron Locked Aircraft

2014 ◽  
Vol 651-653 ◽  
pp. 751-756
Author(s):  
Peng Fei Cheng ◽  
Cheng Fu Wu ◽  
Yue Guo
Keyword(s):  
Flight Control ◽  
Control Method ◽  
Reference Model ◽  
Sideslip Angle ◽  
Model Reference ◽  
Control Scheme ◽  
Adaptive Flight Control ◽  
Random Initialization ◽  
Model Reference Adaptive ◽  
The Given

This paper develops a high-sideslip flight control scheme based on model reference adaptive control (MRAC) to stabilize aircraft under aileron deadlock of one side. Firstly, the cascaded flight control scheme for high-sideslip straight flight is presented and how the control signals transfer is also analyzed. After that, the control structure and laws of MRAC for attitude inner-loop connected with sideslip command are designed. Finally, the control scheme is verified under a nonlinear aircraft model in conditions of no fault and one side aileron deadlock respectively. The simulation results show that when one side aileron deadlock occurs in accompany with the plant’s aerodynamic data perturbation and random initialization of controller parameters, this control method could utilize operation points of no-fault aircraft to force the faulty aircraft following the given reference model responses and finally tracking given sideslip angle command without static error robustly.

scholarly journals Fuzzy rule: Based model reference adaptive control for PMSM drives

2007 ◽  
Vol 4 (1) ◽  
pp. 13-22 ◽  
Author(s):  
Mohamed Kadjoudj ◽  
Noureddine Golea ◽  
Hachemi Benbouzid
Keyword(s):  
Knowledge Base ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Reference Model ◽  
Adaptive Fuzzy Control ◽  
Rule Base ◽  
Motor Speed ◽  
Model Reference ◽  
Adaptive Fuzzy ◽  
Model Reference Adaptive

The objective of the model reference adaptive fuzzy control (MRAFC) is to change the rules definition in the direct fuzzy logic controller (FLC) and rule base table according to the comparison between the reference model output signal and system output. The MRAFC is composed by the fuzzy inverse model and a knowledge base modifier. Because of its improved algorithm, the MRAFC has fast learning features and good tracking characteristics even under severe variations of system parameters. The learning mechanism observes the plant outputs and adjusts the rules in a direct fuzzy controller, so that the overall system behaves like a reference model, which characterizes the desired behavior. In the proposed scheme, the error and error change measured between the motor speed and output of the reference model are applied to the MRAFC. The latter will force the system to behave like the signal reference by modifying the knowledge base of the FLC or by adding an adaptation signal to the fuzzy controller output. In this paper, the MRAFC is applied to a permanent magnet synchronous motor drive (PMSM). High performances and robustness have been achieved by using the MRAFC. This will be illustrated by simulation results and comparisons with other controllers such as PI classical and adaptive fuzzy controller based on gradient method controllers.

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