Modelling and Adaptive Control of Tendon-Driven Micromanipulators in the Presence of Van-der-Waals Forces

2004 ◽  
Author(s):  
Athanasios Tsoukalas ◽  
Anthony Tzes
Keyword(s):  
Adaptive Control ◽  
Design Problem ◽  
Van Der Waals ◽  
Adaptive Controller ◽  
Simulation Studies ◽  
Unknown Parameters ◽  
Actuation Mechanism ◽  
Control Scheme ◽  
Driven System ◽  
Adaptive Control Scheme

In this article, the design problem of an adaptive controller for a robotic micromanipulator, including the effects of the applied Van der Waals (VdW) forces is considered. The micro-manipulator’s dynamic model is appropriately modified in order to include the interaction of the attractive VdW-forces. Inhere, every link is decomposed into a series of elementary particles (e.g. spheres), each one interacting with the robot’s neighboring objects during its motion. This interaction induces nonlinear additive terms in the model, attributed to the overall effect of the VdW-forces. The actuation is achieved by a tendon-driven system. At each joint, a pair of tendons is attached and act in an almost passive antagonistic manner. The kinematic and dynamic analysis of the tendon-driven actuation mechanism is offered. Consequently, the microrobot’s model is shown to be linearly parameterizable. Subject to this observation, a globally stabilizable adaptive control scheme is derived, estimating the unknown parameters (masses, generalized VdW-forces) and compensating any variations of those. Simulation studies on a 2-DOF micro-manipulator are offered to highlight the effectiveness of the proposed scheme.

Adaptive Control Scheme for Coupled Tank Process

2018 ◽  
pp. 89-95
Author(s):  
Vinodhini M.
Keyword(s):  
Adaptive Control ◽  
Nonlinear Behaviour ◽  
Simulation Studies ◽  
Input Output ◽  
Control Scheme ◽  
Direct Model ◽  
Multivariable Process ◽  
Model Reference Adaptive ◽  
Siso System ◽  
Adaptive Control Scheme

The objective of this paper is to develop a Direct Model Reference Adaptive Control (DMRAC) algorithm for a MIMO process by extending the MIT rule adopted for a SISO system. The controller thus developed is implemented on Laboratory interacting coupled tank process through simulation. This can be regarded as the relevant process control in petrol and chemical industries. These industries involve controlling the liquid level and the flow rate in the presence of nonlinearity and disturbance which justifies the use of adaptive techniques such as DMRAC control scheme. For this purpose, mathematical models are obtained for each of the input-output combinations using white box approach and the respective controllers are developed. A detailed analysis on the performance of the chosen process with these controllers is carried out. Simulation studies reveal the effectiveness of proposed controller for multivariable process that exhibits nonlinear behaviour.

A SIMPLE SYNCHRONIZATION SCHEME OF COULLET SYSTEMS WITH UNKNOWN PARAMETERS

2014 ◽  
Vol 28 (06) ◽  
pp. 1450021
Author(s):  
ZUO-LEI WANG ◽  
XUE-RONG SHI ◽  
YAOLIN JIANG
Keyword(s):  
Adaptive Control ◽  
Numerical Simulations ◽  
Sufficient Conditions ◽  
Unknown Parameters ◽  
Control Scheme ◽  
Single Controller ◽  
Synchronization Scheme ◽  
Adaptive Control Scheme

Synchronization of Coullet systems is investigated via back stepping method when parameters are unknown. A novel adaptive control scheme is presented, which contains a single controller. To achieve the synchronization of Coullet systems, sufficient conditions are derived and the unknown parameters are estimated. Finally, some numerical simulations are employed to verify the effectiveness of the proposed scheme.

An Adaptive Control Scheme for Mechanical Manipulators—Compensation of Nonlinearity and Decoupling Control

1986 ◽  
Vol 108 (2) ◽  
pp. 127-135 ◽  
Author(s):  
Roberto Horowitz ◽  
Masayoshi Tomizuka
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
Adaptive Controller ◽  
Fundamental Properties ◽  
Integral Action ◽  
Control Scheme ◽  
Mechanical Manipulators ◽  
Nonlinear Compensator ◽  
Manipulator Control ◽  
Adaptive Control Scheme

This paper presents a new adaptive control scheme for mechanical manipulators. Making use of the fundamental properties of the manipulator equations, an adaptive algorithm is developed for compensating a nonlinear term in the dynamic equations and for decoupling the dynamic interaction among the joints. A computer simulation study is conducted to evaluate the performance of a manipulator control system composed of the manipulator, adaptive nonlinear compensator/decoupling controller and state feedback controller with integral action. Simulation results show that the manipulator control system with adaptive controller is insensitive to variations of manipulator configurations and payload.

Adaptive Control of Nanowires Motion Using Electric Fields in Fluid Suspension

2019 ◽  
Author(s):  
Juan Wu ◽  
Kaiyan Yu
Keyword(s):  
Adaptive Control ◽  
Electric Fields ◽  
Adaptive Controller ◽  
Experimental Results ◽  
Parametric Uncertainties ◽  
Control Scheme ◽  
Complex Characterization ◽  
Adaptive Control Scheme

Abstract Automated, highly precise manipulation of nanowires and nanotubes is essential to achieve scalable nanomanufacturing. However, nanowires exhibit uncontrolled variations in their structures or compositions that can limit their functions and properties. In this paper, we present an adaptive controller for the simultaneous manipulation of multiple nanowires using electric fields. We then prove its stability in the presence of parametric uncertainties. Without complex characterization of each nanowire’s mobility, the nanowires can be steered to achieve precisely controlled positions. Simulation and experimental results confirm the proposed adaptive control scheme precisely, independently, and simultaneously manipulates the motion of multiple nanowires.

An Robust Adaptive Control Scheme for Hydraulic Servo Systems

2006 ◽  
Author(s):  
Torben Ole Andersen ◽  
Michael Ryygaard Hansen
Keyword(s):  
Adaptive Control ◽  
Tracking Error ◽  
Adaptive Controller ◽  
Robust Adaptive Control ◽  
Region Of Attraction ◽  
Control Scheme ◽  
Whole Space ◽  
Bounded Disturbances ◽  
Robust Adaptive ◽  
Adaptive Control Scheme

The paper looks into Model Reference Adaptive Control (MRAC) based on a linear plant model with constant or slowly varying parameters. The actual plant is non-linear, of a higher model order, subjected to time-varying bounded disturbances, and the measured values may be corrupted by noise. These problems are explored and the adaptive algorithms are modified to counteract instability mechanisms and for improved robustness with respect to bounded disturbances and non-modeled dynamics. The adaptive controller identifies the dominant dynamics and uses feedforward to provide anticipative actions in tracing task while an adaptive feedback part stabilizes the tracking error dynamics. Also the effects of non-modeled high frequency dynamics and bounded disturbances on stability and performance are analyzed. The adaptive control scheme is robust in the sense that it guarantees the existence of a large region of attraction from which all the trajectories remain bounded. The size of the region of attraction depends on the non-modeled dynamics in such a way that if the non-modeled dynamics is infinitely fast, the region of attraction becomes the whole space. Simulation and experimental results are presented and discussed to demonstrate the strength of the proposed algorithm.

scholarly journals A L1 Adaptive Control Scheme for UAV Carrier Landing Using Nonlinear Dynamic Inversion

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Ke Lu ◽  
Chunsheng Liu
Keyword(s):  
Adaptive Control ◽  
Nonlinear Dynamic ◽  
Adaptive Controller ◽  
Dynamic Inversion ◽  
Model Inversion ◽  
L1 Adaptive Control ◽  
Control Scheme ◽  
Glide Slope ◽  
Adaptive Control Scheme ◽  
Nonlinear Dynamic Inversion

This paper presents a L1 adaptive controller augmenting a dynamic inversion controller for UAV (unmanned aerial vehicle) carrier landing. A three axis and a power compensator NDI (nonlinear dynamic inversion) controller serves as the baseline controller for this architecture. The inner-loop command inputs are roll-rate, pitch-rate, yaw-rate, and thrust commands. The outer-loop command inputs come from the guidance law to correct the glide slope. However, imperfect model inversion and nonaccurate aerodynamic data may cause degradation of performance and may lead to the failure of the carrier landing. The L1 adaptive controller is designed as augmentation controller to account for matched and unmatched system uncertainties. The performance of the controller is examined through a Monte Carlo simulation which shows the effectiveness of the developed L1 adaptive control scheme based on nonlinear dynamic inversion.

L1 adaptive control design of a helicopter in vertical flight

2020 ◽  
Vol 234 (14) ◽  
pp. 2089-2099
Author(s):  
Song Tian ◽  
Jiang Wang ◽  
Defu Lin ◽  
Pei Pei
Keyword(s):  
Adaptive Control ◽  
Flight Control ◽  
Control Design ◽  
Adaptive Controller ◽  
Piecewise Constant ◽  
L1 Adaptive Control ◽  
Control Scheme ◽  
Practical Engineering ◽  
Adaptation Law ◽  
Adaptive Control Scheme

This article presents L1 adaptive control scheme for vertical flight control of helicopter. Linear controller is designed as baseline controller to provide preliminary improvement in performance and robustness. Considering the existence of uncertainties and disturbances, we propose L1 adaptive controller with modified piecewise constant adaptation law to augment the baseline controllers. Further, the proposed L1 adaptive controller can be implemented without any modification of the baseline controller. Benefit from this, the design of the entire control system is significantly simplified, and the designed controller is easy to apply to practical engineering. The simulation results indicate that the proposed controllers have good performance for helicopter vertical flight in the presence of uncertainties and disturbances.

Speed Control of Hydraulic Press via Adaptive Back-Stepping

2010 ◽  
Vol 40-41 ◽  
pp. 46-51
Author(s):  
Chang Bin Li ◽  
Ai Guo Wu ◽  
Chun Yan Du
Keyword(s):  
Mathematical Model ◽  
Adaptive Control ◽  
Speed Control ◽  
Adaptive Controller ◽  
Hydraulic Press ◽  
Speed Controller ◽  
Control Scheme ◽  
Simulation Results ◽  
The Mathematical Model ◽  
Adaptive Control Scheme

This paper is concerned with speed control of hydraulic press system. First, the mathematical model of hydraulic press is derived from its physical characteristics. Then, based on this model, the so-called back-stepping approach is used to design a speed controller. Moreover, in order to overcome the unknown deformation resistance and some other resistance, an adaptive control scheme is introduced to this controller. Finally, a real hydraulic press model is used to validate the proposed method. Simulation results show that the adaptive controller deals with the nonlinearity effectively, and the tracking performance of the system is good.

Cross-coupling synchronous velocity control using model reference adaptive control scheme in an unsymmetrical biaxial winding system

2018 ◽  
Vol 232 (9) ◽  
pp. 1245-1259
Author(s):  
Huy Hung Nguyen ◽  
Van Tu Duong ◽  
Dae Hwan Kim ◽  
Hak Kyeong Kim ◽  
Sang Bong Kim
Keyword(s):  
Adaptive Control ◽  
Cross Coupling ◽  
Model Reference Adaptive Control ◽  
Coupling Mechanism ◽  
Unknown Parameters ◽  
Model Reference ◽  
Motion Error ◽  
Control Scheme ◽  
Model Reference Adaptive ◽  
Adaptive Control Scheme

Motion control with high accuracy for each axial system is the fundamental requirement to reduce a synchronous motion error of a multi-axis system. Especially, designing a model-based controller for an uncertainty system with unknown parameters is not easy without using system identification. To overcome the mentioned issue, this article proposes a cross-coupling synchronous velocity controller using a backstepping-based model reference adaptive control scheme in an unsymmetrical biaxial winding system called a transformer winding system. The proposed controller deals not only with the uncertainty but also with the recursive structure of the system. The backstepping technique for the recursive structural system and the model reference adaptive control method for the uncertainty of the system are designed to stabilize two axial systems with unknown parameters. An auxiliary system is added to build the proposed controller for coping with input constraints of physical actuators. To improve the proposed controller’s ability to cope with external disturbances, a dead-zone modification is utilized to modify the adaptation laws to avoid the drift phenomenon. Moreover, a cross-coupling mechanism is integrated into the proposed controller to reduce the synchronous velocity error between the velocities of the biaxial winding system. The proposed controller is also transformed into discrete time to be run on a digital signal processor alone chip. The experimental results are shown to verify the high performance and efficiency of the proposed controller for practical applications.

Adaptive Virtual Autobalancing for a Magnetic Rotor With Unknown Mass Imbalance: Part I — Static Balancing

1995 ◽  
Author(s):  
Kai-Yew Lum ◽  
Sanjay P. Bhat ◽  
Dennis S. Bernstein ◽  
Vincent T. Coppola
Keyword(s):  
Adaptive Control ◽  
Control Strategy ◽  
Control Algorithm ◽  
Equations Of Motion ◽  
Adaptive Controller ◽  
Magnetic Bearing ◽  
Static Balancing ◽  
Mass Imbalance ◽  
Control Scheme ◽  
Adaptive Control Scheme

Abstract An adaptive control scheme is proposed for stabilizing a planar rotor mounted on a magnetic bearing. The control strategy involves the concept of virtual autobalancing, where the control algorithm emulates the dynamics of a mechanical autobalancer by applying forces that are equivalent to the action of the autobalancer on the rotor. Equations of motion for a planar, torque-free, elastically suspended rotor equipped with an autobalancer are derived. Based on these equations, an adaptive controller for the magnetic rotor is formulated. The results are demonstrated in simulation.

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