scholarly journals Disturbance compensation-based output feedback adaptive control for shape memory alloy actuator system

2021 ◽  
Vol 18 (1) ◽  
pp. 172988142199399
Author(s):  
Xiaoguang Li ◽  
Bi Zhang ◽  
Daohui Zhang ◽  
Xingang Zhao ◽  
Jianda Han
Keyword(s):  
Adaptive Control ◽  
Shape Memory Alloy ◽  
Shape Memory ◽  
Control Method ◽  
Control Law ◽  
Reference Trajectory ◽  
Disturbance Compensation ◽  
Comparison Results ◽  
Control Scheme ◽  
Actuator System

Shape memory alloy (SMA) has been utilized as the material of smart actuators due to the miniaturization and lightweight. However, the nonlinearity and hysteresis of SMA material seriously affect the precise control. In this article, a novel disturbance compensation-based adaptive control scheme is developed to improve the control performance of SMA actuator system. Firstly, the nominal model is constructed based on the physical process. Next, an estimator is developed to online update not only the unmeasured system states but also the total disturbance. Then, the novel adaptive controller, which is composed of the nominal control law and the compensation control law, is designed. Finally, the proposed scheme is evaluated in the SMA experimental setup. The comparison results have demonstrated that the proposed control method can track reference trajectory accurately, reject load variations and stochastic disturbances timely, and exhibit satisfactory robust stability. The proposed control scheme is system independent and has some potential in other types of SMA-actuated systems.

Model Reference Adaptive Control Based on KP Model for Magnetically Controlled Shape Memory Alloy Actuators

2017 ◽  
Vol 15 (1_suppl) ◽  
pp. 31-37 ◽  
Author(s):  
Miaolei Zhou ◽  
Yannan Zhang ◽  
Kun Ji ◽  
Dong Zhu
Keyword(s):  
Adaptive Control ◽  
Shape Memory Alloy ◽  
Shape Memory ◽  
Control Method ◽  
Model Reference Adaptive Control ◽  
Positioning Accuracy ◽  
Model Reference ◽  
Hysteresis Nonlinearity ◽  
Adopted Model ◽  
Model Reference Adaptive

Introduction Magnetically controlled shape memory alloy (MSMA) actuators take advantages of their large deformation and high controllability. However, the intricate hysteresis nonlinearity often results in low positioning accuracy and slow actuator response. Methods In this paper, a modified Krasnosel'skii-Pokrovskii model was adopted to describe the complicated hysteresis phenomenon in the MSMA actuators. Adaptive recursive algorithm was employed to identify the density parameters of the adopted model. Subsequently, to further eliminate the hysteresis nonlinearity and improve the positioning accuracy, the model reference adaptive control method was proposed to optimize the model and inverse model compensation. Results The simulation experiments show that the model reference adaptive control adopted in the paper significantly improves the control precision of the actuators, with a maximum tracking error of 0.0072 mm. Conclusions The results prove that the model reference adaptive control method is efficient to eliminate hysteresis nonlinearity and achieves a higher positioning accuracy of the MSMA actuators.

scholarly journals Adaptive control scheme based on the least squares support vector machine network

2011 ◽  
Vol 21 (4) ◽  
pp. 685-696 ◽  
Author(s):  
Tarek Mahmoud
Keyword(s):  
Neural Networks ◽  
Support Vector Machine ◽  
Adaptive Control ◽  
Least Squares ◽  
Nonlinear System Identification ◽  
Support Vector ◽  
Reference Trajectory ◽  
Control Scheme ◽  
Support Vector Machine Network ◽  
Adaptive Control Scheme

Adaptive control scheme based on the least squares support vector machine networkRecently, a new type of neural networks called Least Squares Support Vector Machines (LS-SVMs) has been receiving increasing attention in nonlinear system identification and control due to its generalization performance. This paper develops a stable adaptive control scheme using the LS-SVM network. The developed control scheme includes two parts: the identification part that uses a modified structure of LS-SVM neural networks called the multi-resolution wavelet least squares support vector machine network (MRWLS-SVM) as a predictor model, and the controller part that is developed to track a reference trajectory. By means of the Lyapunov stability criterion, stability analysis for the tracking errors is performed. Finally, simulation studies are performed to demonstrate the capability of the developed approach in controlling a pH process.

Design of a 2 DOF Shape Memory Alloy Actuator Using SMA Springs

2021 ◽  
Author(s):  
Hussein F. M. Ali ◽  
Youngshik Kim
Keyword(s):  
Shape Memory Alloy ◽  
Shape Memory ◽  
Open Loop ◽  
Degree Of Freedom ◽  
Biologically Inspired ◽  
Loop Control ◽  
Actuator System ◽  
Sma Actuator ◽  
Sma Spring ◽  
Two Degree Of Freedom

Abstract In this paper, we developed two degree of freedom shape memory alloy (SMA) actuator using SMA springs. This module can be applied easily to various applications: device holder, artificial finger, grippes, fish robot, and many other biologically inspired applications, where small size and small wight of the actuator are very critical. This actuator is composed of two sets of SMA springs: one set is for the rotation around the X axis (roll angle) and the other set is for the rotation around the Y axis (pitch angle). Each set contains two elements: one SMA spring and one antagonistic SMA spring. We used an inertia sensor (IMU) and two potentiometers for angles feedback. The SMA actuator system is modeled mathematically and then tested experimentally in open-loop and closed-loop control. We designed and experimentally tuned a proportional integrator derivative (PID) controller to follow the set points and to track the desired trajectories. The main goal of the presented controller is to control roll and pitch angles simultaneously in order to satisfy set points and trajectories within the work space. The experimental results show that the two degree of freedom SMA actuator system follows the desired setpoints with acceptable rise time and overshoot.

Motion Control of an Omni-Directional Walker for Walking Support

2013 ◽  
pp. 20-28
Author(s):  
Renpeng Tan ◽  
Shuoyu Wang ◽  
Yinlai Jiang ◽  
Kenji Ishida ◽  
Masakatsu G. Fujie
Keyword(s):  
Adaptive Control ◽  
Motion Control ◽  
Control Method ◽  
Center Of Gravity ◽  
Path Tracking ◽  
Reference Trajectory ◽  
Tracking Errors ◽  
Directed Movement ◽  
Load Change

With the increase in the percentage of the population defined as elderly, increasing numbers of people suffer from walking disabilities due to illness or accidents. An omni-directional walker (ODW) has been developed that can support people with walking disabilities and allow them to perform indoor walking. The ODW can identify the user’s directional intention based on the user’s forearm pressures and then supports movement in the intended direction. In this chapter, a reference trajectory is generated based on the intended direction in order to support directed movement. The ODW needs to follow the generated path. However, path tracking errors occur because the center of gravity (COG) of the system shifts and the load changes due to user`s pressure. An adaptive control method is proposed to deal with this issue. The results of simulations indicate that the ODW can accurately follow the user’s intended direction by inhibiting the influence of COG shifts and the resulting load change. The proposed scheme is feasible for supporting indoor movement.

B-Spline Based Adaptive Control of Shape Memory Alloy Actuated Robotic Systems

2002 ◽  
Author(s):  
Yavuz Eren ◽  
Constantinos Mavroidis ◽  
Jason Nikitczuk
Keyword(s):  
Adaptive Control ◽  
Shape Memory Alloy ◽  
Shape Memory ◽  
Large Scale ◽  
Full Range ◽  
Spline Approximation ◽  
Variable Structure ◽  
Robotic Systems ◽  
Integral Control ◽  
B Spline

In this paper we present a novel controller for Shape Memory Alloy (SMA) actuated robotic systems. The new controller, called BAC (B-spline based Adaptive Control), is based on a hybrid combination of gain scheduling, B-spline approximation, variable structure control and integral control. The proposed controller shows excellent positioning accuracy and speed throughout the full range of motion of a SMA actuated robotic system in large-scale applications. To demonstrate the validity of BAC, a novel anthropomorphic SMA Actuated forearm/wrist mechanism is utilized in real-time PC based control experiments. BAC is experimentally compared to PID and integral variable structure controllers and it is shown that its performance is superior.

QUASIPASSIVITY-BASED ROBUST NONLINEAR FLAP POSITIONING CONTROL USING SHAPE MEMORY ALLOY MICRO-ACTUATORS

2005 ◽  
Vol 29 (2) ◽  
pp. 143-161
Author(s):  
Nicolas Léchevin ◽  
Camille Alain Rabbath ◽  
Frank Wong ◽  
O. Boissonneault
Keyword(s):  
Shape Memory Alloy ◽  
Nonlinear Control ◽  
Numerical Simulations ◽  
Shape Memory ◽  
Position Control ◽  
Tracking Error ◽  
Constitutive Law ◽  
Control Law ◽  
Ultimate Boundedness ◽  
Feedback Connection

This paper proposes a quasipassivity-based robust nonlinear control law ensuring position control of a rotary flap by means of an antagonist-type shape memory alloy microactuator. The control system employs variable-structure control to obtain robust performance, phase-lead compensation to quasipassivate the shape memory alloy dynamics and quasipassivity-based analysis to warrant robust ultimate boundedness of system trajectories. The feedback connection of the two paths leads to ultimate boundedness of tracking error trajectories of the plant despite uncertainties in the dynamic loads affecting the leading edge flap and in the friction found in the actuator. Since accurate numerical simulations and development of new concepts of microactuators based on shape memory alloys require a tractable, constitutive law accurately describing the relationship between force, displacement and temperature in the material, the paper also presents a hybrid micro-macro-mechanical shape memory alloy constitutive model. This model is based on a combination of structural modeling on a microscopic scale and transformation kinetics modeling on a macroscopic scale. The proposed control law and hybrid micro-macro-mechanical model are placed in closed-loop by means of numerical simulations that demonstrate the validity of the nonlinear control scheme.

scholarly journals Adaptive PD Control Based on RBF Neural Network for a Wire-Driven Parallel Robot and Prototype Experiments

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Yuqi Wang ◽  
Qi Lin ◽  
Xiaoguang Wang ◽  
Fangui Zhou
Keyword(s):  
Neural Network ◽  
Adaptive Control ◽  
Control Method ◽  
Rbf Neural Network ◽  
Approximation Error ◽  
Wind Tunnel Test ◽  
Parallel Robot ◽  
Network Control ◽  
Pd Control ◽  
Control Scheme

An adaptive PD control scheme is proposed for the support system of a wire-driven parallel robot (WDPR) used in a wind tunnel test. The control scheme combines a PD control and an adaptive control based on a radial basis function (RBF) neural network. The PD control is used to track the trajectory of the end effector of the WDPR. The experimental environment, the external disturbances, and other factors result in uncertainties of some parameters for the WDPR; therefore, the RBF neural network control method is used to approximate the parameters. An adaptive control algorithm is developed to reduce the approximation error and improve the robustness and control precision of the WDPR. It is demonstrated that the closed-loop system is stable based on the Lyapunov stability theory. The simulation results show that the proposed control scheme results in a good performance of the WDPR. The experimental results of the prototype experiments show that the WDPR operates on the desired trajectory; the proposed control method is correct and effective, and the experimental error is small and meets the requirements.

Sign in / Sign up

Export Citation Format

Share Document