Nonlinear Control of the Reaction Wheel Pendulum Using Passivity-based control And Backstepping Control

2020 ◽  
Author(s):  
Gajje Phani Teja ◽  
Ashwin Dhabale ◽  
Tushar Waghmare
Keyword(s):  
Nonlinear Control ◽  
Backstepping Control ◽  
Reaction Wheel ◽  
Passivity Based Control

scholarly journals Discrete-time inverse optimal control for a reaction wheel pendulum: a passivity-based control approach

2020 ◽  
Vol 19 (4) ◽  
pp. 123-132 ◽  
Author(s):  
Oscar Danilo Montoya ◽  
Walter Gil-González ◽  
Federico Martin Serra
Keyword(s):  
Optimal Control ◽  
Discrete Time ◽  
Point Of View ◽  
Control Analysis ◽  
Inverse Optimal Control ◽  
Reaction Wheel ◽  
Control Approach ◽  
Control Functions ◽  
Passivity Based Control ◽  
The Time Domain

In this paper it is presented the design of a controller for a reaction wheel pendulum using a discrete-time representation via optimal control from the point of view of passivity-based control analysis. The main advantage of the proposed approach is that it allows to guarantee asymptotic stability convergence using a quadratic candidate Lyapunovfunction. Numerical simulations show that the proposed inverse optimal control design permits to reach superiornumerical performance reported by continuous approaches such as Lyapunov control functions and interconnection,and damping assignment passivity-based controllers. An additional advantageof the proposed inverse optimal controlmethod is its easy implementation since it does not employ additional states. It is only required a basic discretizationof the time-domain dynamical model based on the backward representation. All the simulations are carried out inMATLAB/OCTAVE software using a codification on the script environment.

A New Nonlinear Control Strategy for DC/AC Inverter

2012 ◽  
Vol 466-467 ◽  
pp. 829-833 ◽  
Author(s):  
Kun Mu ◽  
Xiao Bin Mu ◽  
Xue Yu Bao
Keyword(s):  
Nonlinear Control ◽  
Control Strategy ◽  
High Performance ◽  
Control Method ◽  
Assembly Language ◽  
Single Chip ◽  
Two Phase ◽  
Three Phase ◽  
Passivity Based Control ◽  
The Mathematical Model

The mathematical model of Three-phase VoltagePulse Width Modulation (PWM) DC/AC inverter is non-linear, in view of the traditional linear control strategy can not meet the requirements of designing high-performance DC/AC inverter, this paper propose a new nonlinear control strategy for Three-phase Voltage PWM DC/AC inverter called Passivity-based Control. We can alter the inverter model in three-phase abc coordinate to two-phase synchronous rotating dq coordinate for establishing the Euler – Lagrange (EL) energy model for this system, then we also proof this system is strictly passive. We can control the output energy of the system, and we use the approaches of injecting damping and decoupling to improve system performance. Usually, we can use Single Chip Microcomputer or other kinds of computer with this algorithm for our design, this algorithm can be programmed with the computer language, such as C/C++ and assembly language, etc. Simulation results show that passivity-based control method can make this system possess the high-performance of robustness and dynamic.

Passivity-Based Control of Motor for Reaction Wheel

2014 ◽  
Vol 989-994 ◽  
pp. 2865-2868
Author(s):  
Ren Long Yu ◽  
Jing Jin
Keyword(s):  
Control Method ◽  
Buck Converter ◽  
Motor Speed ◽  
Tracking Accuracy ◽  
Reaction Wheel ◽  
Brushless Dc ◽  
Model Combining ◽  
Passivity Based Control ◽  
Permanent Magnet Brushless Dc ◽  
Speed Mode

To achieve high-precision tracking control of motor speed for magnetically suspended reaction wheel, mathematical model combining BUCK converter with permanent magnet brushless DC motor system is established, and a MSRFW speed mode Passivity-based control method is presented. A passivity-based controller of speed tracking is designed in order to enhance the speed of tracking performance. Experiments on MSRW platform show that passivity-based control method can improve the speed of the dynamic response and tracking accuracy, from which the validity is verified.

Nonlinear control of the Reaction Wheel Pendulum

Automatica ◽  
2001 ◽  
Vol 37 (11) ◽  
pp. 1845-1851 ◽  
Author(s):  
Mark W. Spong ◽  
Peter Corke ◽  
Rogelio Lozano
Keyword(s):  
Nonlinear Control ◽  
Reaction Wheel

scholarly journals Passivity-Based Control Design for Magnetic Levitation System

2020 ◽  
Vol 10 (7) ◽  
pp. 2392 ◽  
Author(s):  
Wang Yang ◽  
Fanwei Meng ◽  
Man Sun ◽  
Kai Liu
Keyword(s):  
Nonlinear Control ◽  
Qualitative Method ◽  
Magnetic Levitation ◽  
Design Method ◽  
Electromagnetic Levitation ◽  
Design Tool ◽  
Control Law ◽  
Levitation System ◽  
Magnetic Levitation System ◽  
Passivity Based Control

The passivity-based control (PBC) is a new direction of nonlinear control, but the method is basically a qualitative method. A quantifiable design method in combination with PBC is provided in this paper. To solve the partial differential equation (PDE) for PBC, the nonlinear system must first be transformed into a Hamiltonian model. The PDE for the Hamiltonian system is then quantifiably solved with an electromagnetic levitation example. The resulting control law is presented and discussed. The proposed method provides a practical design tool for nonlinear control.

BACKSTEPPING CONTROL STRATEGY FOR AN UNDERACTUATED X4-AUV

2015 ◽  
Vol 74 (9) ◽  
Author(s):  
Zainah Md. Zain ◽  
Nur Fadzillah Harun
Keyword(s):  
Nonlinear Control ◽  
Lyapunov Stability ◽  
Control Strategy ◽  
Stability Theory ◽  
Degrees Of Freedom ◽  
Control Method ◽  
Lyapunov Stability Theory ◽  
Backstepping Control ◽  
Six Degrees Of Freedom ◽  
Nonlinear Control Method

A nonlinear control method is considered for stabilizing all attitudes and positions (x, y or z) of an underactuated X4-AUV with four thrusters and six degrees-of-freedom (DOFs), in which the positions are stabilized according to the Lyapunov stability theory and angles are stabilized using backstepping control method. A dynamical model is first derived, and then a sequential nonlinear control strategy is implemented for the X4-AUV, composed of translational and rotational subsystems. A controller for the translational subsystem stabilizes one position out of x-, y-, and z-coordinates, whereas controllers for the rotational subsystems generate the desired roll, pitch and yaw angles. Thus, the rotational controllers stabilize all the attitudes of the X4-AUV at a desired (x-, y- or z-) position of the vehicle. Some numerical simulations are conducted to demonstrate the effectiveness of the proposed controllers.

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