Adaptive Integral Base Sliding Mode Tracking Control of Piezoelectric Actuators

2009 ◽  
Author(s):  
Mohammad Sheikh Sofla ◽  
Seyed Mehdi Rezaei ◽  
Mohammad Zareinejad
Keyword(s):  
Sliding Mode ◽  
Piezoelectric Actuators ◽  
Uncertain System ◽  
Hysteretic Behavior ◽  
Control Approach ◽  
Practical Applications ◽  
Hysteresis Nonlinearity ◽  
Control Scheme ◽  
Integral Sliding Surface ◽  
Control Methodology

This paper presents an adaptive integral sliding mode control scheme for precise trajectory tracking of piezoelectric actuators (PEAs). This control methodology is proposed considering the problems of unknown or uncertain system parameters, hysteresis nonlinearity, and external load disturbances. The hysteretic behavior is represented by Bouc–Wen hysteresis model. It is shown that the nonlinear response of the model due to the hysteresis effect, acts as a bounded disturbance. Then base on this fact an adaptive robust controller is proposed, where an integral sliding surface is utilized to achieve the desired tracking performance. By using the proposed control approach the asymptotical stability in displacement tracking and robustness to the dynamic load disturbance can be provided. Finally, Experimental results are illustrated to verify the efficiency of the proposed method for tracking in various range of frequency and load which are common in practical applications.

Adaptive Trajectory Tracking Control of Nanopositioning Stage Under Dynamic Load Condition

2009 ◽  
Author(s):  
Mohammad Sheikh Sofla ◽  
Seyed Mehdi Rezaei ◽  
Mohammad Zareinejad
Keyword(s):  
Trajectory Tracking ◽  
Dynamic Load ◽  
Tracking Control ◽  
Nonlinear Function ◽  
Load Condition ◽  
Piezoelectric Actuators ◽  
Trajectory Tracking Control ◽  
Control Approach ◽  
Practical Applications ◽  
Hysteresis Nonlinearity

Piezoelectric actuators (PEAs) are frequently used in a wide variety of micromanipulation systems. However their accuracy is limited due to hysteresis nonlinearity. Also investigation of the fundamental properties of the piezoceramics depicts that external mechanical loads cause inclination in hysteresis loop which can deteriorate tracking performance furthermore. A novel modeling and control approach is proposed in this paper, for precision trajectory tracking control of piezoelectric actuators under dynamic load condition. First the hysteresis nonlinear function based on Bouc-Wen hysteresis model is approximated by a Taylor series expansion. Then an adaptive trajectory tracking control is proposed based on the backstepping method using the developed mathematical model. The asymptotical stability in displacement tracking and robustness to the dynamic load disturbance can be provided using the proposed control approach. Experimental results are illustrated to verify the efficiency of the proposed method for practical applications.

scholarly journals Neural Network Self-Tuning Control for a Piezoelectric Actuator

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3342 ◽  
Author(s):  
Wenjun Li ◽  
Chen Zhang ◽  
Wei Gao ◽  
Miaolei Zhou
Keyword(s):  
Neural Network ◽  
Control Method ◽  
Input Voltage ◽  
Rate Dependency ◽  
Output Displacement ◽  
Control Approach ◽  
Adaptive Parameter ◽  
Hysteresis Nonlinearity ◽  
Self Tuning ◽  
Control Methodology

Piezoelectric actuators (PEA) have been widely used in the ultra-precision manufacturing fields. However, the hysteresis nonlinearity between the input voltage and the output displacement, which possesses the properties of rate dependency and multivalued mapping, seriously impedes the positioning accuracy of the PEA. This paper investigates a control methodology without the hysteresis model for PEA actuated nanopositioning systems, in which the inherent drawback generated by the hysteresis nonlinearity aggregates the control accuracy of the PEA. To address this problem, a neural network self-tuning control approach is proposed to realize the high accuracy tracking with respect to the system uncertainties and hysteresis nonlinearity of the PEA. First, the PEA is described as a nonlinear equation with two variables, which are unknown. Then, using the capabilities of super approximation and adaptive parameter adjustment, the neural network identifiers are used to approximate the two unknown variables automatically updated without any off-line identification, respectively. To verify the validity and effectiveness of the proposed control methodology, a series of experiments is executed on a commercial PEA product. The experimental results illustrate that the established neural network self-tuning control method is efficient in damping the hysteresis nonlinearity and enhancing the trajectory tracking property.

scholarly journals A Biologically Inspired Framework for the Intelligent Control of Mechatronic Systems and Its Application to a Micro Diving Agent

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Wallace M. Bessa ◽  
Gerrit Brinkmann ◽  
Daniel A. Duecker ◽  
Edwin Kreuzer ◽  
Eugen Solowjow
Keyword(s):  
Neural Network ◽  
Sliding Mode ◽  
Weight Vector ◽  
Mechatronic Systems ◽  
Biologically Inspired ◽  
Control Approach ◽  
The Neural Network ◽  
Control Scheme ◽  
Intelligent Behavior ◽  
Intelligent Controllers

Mechatronic systems are becoming an intrinsic part of our daily life, and the adopted control approach in turn plays an essential role in the emulation of the intelligent behavior. In this paper, a framework for the development of intelligent controllers is proposed. We highlight that robustness, prediction, adaptation, and learning, which may be considered the most fundamental traits of all intelligent biological systems, should be taken into account within the project of the control scheme. Hence, the proposed framework is based on the fusion of a nonlinear control scheme with computational intelligence and also allows mechatronic systems to be able to make reasonable predictions about its dynamic behavior, adapt itself to changes in the plant, learn by interacting with the environment, and be robust to both structured and unstructured uncertainties. In order to illustrate the implementation of the control law within the proposed framework, a new intelligent depth controller is designed for a microdiving agent. On this basis, sliding mode control is combined with an adaptive neural network to provide the basic intelligent features. Online learning by minimizing a composite error signal, instead of supervised off-line training, is adopted to update the weight vector of the neural network. The boundedness and convergence properties of all closed-loop signals are proved using a Lyapunov-like stability analysis. Numerical simulations and experimental results obtained with the microdiving agent demonstrate the efficacy of the proposed approach and its suitableness for both stabilization and trajectory tracking problems.

Operator-based experimental studies on nonlinear vibration control for an aircraft vertical tail with considering low-order modes

2016 ◽  
Vol 38 (12) ◽  
pp. 1421-1433 ◽  
Author(s):  
Yuta Katsurayama ◽  
Mingcong Deng ◽  
Changan Jiang
Keyword(s):  
Vibration Control ◽  
Experimental Studies ◽  
Control Design ◽  
Piezoelectric Actuators ◽  
Nonlinear Feedback ◽  
Coprime Factorization ◽  
Hysteresis Nonlinearity ◽  
Control Scheme ◽  
Piezoelectric Elements ◽  
Low Order

In this paper, a robust nonlinear control design using an operator-based robust right coprime factorization approach is considered for vibration control on an aircraft vertical tail with piezoelectric elements. First, a model of the aircraft vertical tail is derived to describe vibration response using the operator-based approach, where, to stabilize vibration of the tail, piezoelectric elements are used as actuators and a hysteresis nonlinear property of piezoelectric actuators is considered. Simultaneously, positions of the piezoelectric actuators that are stuck on the plate are arranged by using a finite element method. Then based on the obtained operator-based model, a robust nonlinear feedback control design is given by using robust right coprime factorization for the aircraft vertical tail with considering the effect of hysteresis nonlinearity from piezoelectric actuators. In particular, low-order modes are employed to design the control scheme even though vibration is configured by high-order modes. In other words, robustness is considered, and the desired performance of tracking is discussed. Finally, both simulation and experimental results are shown to verify the effectiveness of the proposed control scheme.

High Precision Tracking Control Using Piezoelectric Actuator Network

2005 ◽  
Author(s):  
X. Xue ◽  
J. Tang
Keyword(s):  
Sliding Mode Control ◽  
High Precision ◽  
Piezoelectric Actuator ◽  
Tracking Control ◽  
Sliding Mode ◽  
The State ◽  
Control Action ◽  
Minimum Phase ◽  
Hysteresis Nonlinearity ◽  
Control Scheme

Although piezoelectric actuators have been widely used in active control, the hysteresis nonlinearity and the non-minimum phase characteristic could potentially deteriorate the system performance, especially in high precision control applications under disturbance. In this study, a resistance/inductance circuit is connected to the piezoelectric actuator to form an actuator network. With the actuator dynamics, the system model can be directly cast into the state-space whereas the system nonlinearity appears as explicit functions of the state variables. We then develop an integral continuous sliding mode control scheme to tackle the hysteresis nonlinearity and the disturbance issues. Instead of inverse hysteresis cancellation which might not be reliable due to the measurement noise, a direct piezoelectric hysteresis compensation can be achieved using this control strategy. The newly developed control scheme combines the advantages of both integral control and continuous sliding mode control with cubic state feedback. Not only can the control action react efficiently and effectively for the non-minimum phase response, but also, a zero steady state tracking error is guaranteed. Detailed analysis and case studies demonstrate that this new methodology can lead to improved tracking control precision, enhanced control robustness, and smoother control action.

A Self-Repairing Control for the Uncertain System of a Helicopter Using Adaptive Sliding Mode Technology

2012 ◽  
Vol 468-471 ◽  
pp. 529-533 ◽  
Author(s):  
Fu Yang Chen ◽  
Wen Li Luan ◽  
Rui Hou
Keyword(s):  
Control System ◽  
Flight Control ◽  
Sliding Mode ◽  
Nonlinear Function ◽  
Uncertain System ◽  
Flight Control System ◽  
Adaptive Technology ◽  
Helicopter Flight ◽  
Control Scheme ◽  
Adaptive Control Scheme

In this paper, an adaptive control scheme is proposed for the uncertain flight control system of the helicopter with fault in vertical flight. The controller is designed using sliding mode theory and adaptive technology. In the controller, the nonlinear function is brought in, which can enlarge the small errors, and saturate the large errors. And it can make sure the good transient performances and stability of the helicopter flight control system. Finally, the simulation results of the nonlinear helicopter flight system illustrate the effectiveness and feasibility of the proposed scheme in the paper.

Robust predictive sliding mode control for input rate-constrained discrete-time system

2018 ◽  
Vol 36 (3) ◽  
pp. 901-919 ◽  
Author(s):  
Rong Li ◽  
Qingxian Wu
Keyword(s):  
Sliding Mode Control ◽  
Discrete Time ◽  
Sliding Mode ◽  
Input Rate ◽  
Discrete Time System ◽  
Control Approach ◽  
Mode Control ◽  
Discrete Time Systems ◽  
Control Scheme ◽  
Time Systems

Abstract This paper investigates a class of uncertain linear discrete-time systems subject to input rate saturation. A predictive sliding mode control approach is proposed which guarantees the control inputs remain bounded in the input rate saturation. Furthermore, the disturbance observer is developed to compensate for the system uncertainty and disturbance. Finally, the simulations demonstrate the effectiveness of the proposed predictive sliding mode control scheme.

A novel nonsingular integral terminal sliding mode control scheme in epilepsy treatment

2021 ◽  
pp. 014233122110507
Author(s):  
Moshu Qian ◽  
Zhen Zhang ◽  
Guanghua Zhong ◽  
Cuimei Bo
Keyword(s):  
Closed Loop ◽  
Controller Design ◽  
Sliding Mode ◽  
Tracking Error ◽  
Lyapunov Theory ◽  
Terminal Sliding Mode ◽  
Loop Control ◽  
Control Approach ◽  
Control Scheme ◽  
Loop Control System

In this paper, a closed-loop brain stimulation control problem is investigated using the nonsingular integral terminal sliding mode (NITSM) control approach. First, the thalamocortical model of epilepsy seizure is given, which is composed of the cortical PY-IN subnetwork and the subcortical RE-TC subsystem. Then, a nonsingular integral terminal sliding mode surface is designed utilizing the derived output tracking error, and the stability of the sliding mode dynamics is proved by Lyapunov approach. Furthermore, a disturbance observer (DOB) based NITSM controller design approach is proposed for the established thalamocortical model, and the reachability of the closed-loop control system under the designed controller is analyzed using Lyapunov theory. Finally, simulation results are given to illustrate the effectiveness and superiority of the designed control scheme.

Fuzzy impedance-based control with fast terminal sliding mode force control loop for a series elastic actuator system

2021 ◽  
pp. 014233122110436
Author(s):  
Seyed Ali Moafi ◽  
Farid Najafi
Keyword(s):  
Force Control ◽  
Fuzzy Logic Controller ◽  
Sliding Mode ◽  
Control Loop ◽  
Terminal Sliding Mode ◽  
Control Approach ◽  
Series Elastic Actuator ◽  
Control Scheme ◽  
Fast Terminal Sliding Mode ◽  
Series Elastic

This paper proposes a robust control scheme to accomplish the interaction control problem between a series elastic actuator (SEA) and a flexible environment. The adaptability of the controller to unknown variations and robustness of the controller during interaction of the system with environment are the main aims. The control scheme is based on a fuzzy impedance control approach and consists of an inner fast terminal sliding mode force control loop. An experimental setup is designed to prove the efficiency of the developed controller. The experimental results confirm that the proposed fuzzy logic controller guarantees the sensitivity of the controlled system to unpredictable variations. Moreover, by applying the fast terminal sliding mode algorithm for the inner force control loop, the system has faster convergence to the reference path compared with similar control methods found in the literature.

scholarly journals Finite-Time Composite Position Control for a Disturbed Pneumatic Servo System

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaojun Wang ◽  
Jiankun Sun ◽  
Guipu Li
Keyword(s):  
Finite Time ◽  
State Feedback ◽  
Position Control ◽  
Sliding Mode ◽  
State Feedback Control ◽  
Servo Systems ◽  
Control Approach ◽  
Composite Control ◽  
Control Scheme ◽  
Pneumatic Servo System

This paper investigates the finite-time position tracking control problem of pneumatic servo systems subject to hard nonlinearities and various disturbances. A finite-time disturbance observer is firstly designed, which guarantees that the disturbances can be accurately estimated in a finite time. Then, by combining disturbances compensation and state feedback controller together, a nonsmooth composite controller is developed based on sliding mode control approach and homogeneous theory. It is proved that the tracking errors under the proposed composite control approach can be stabilized to zero in finite time. Moreover, compared with pure state feedback control, the proposed composite control scheme offers a faster convergence rate and a better disturbance rejection property. Finally, numerical simulations illustrate the effectiveness of the proposed control scheme.

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