Radial basis function neural network based adaptive fast nonsingular terminal sliding mode controller for piezo positioning stage
Published 2017 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Radial basis function neural network based adaptive fast nonsingular terminal sliding mode controller for piezo positioning stage
Authors
Keywords
Fast nonsingular terminal sliding mode, neural network, piezo positioning stage, robust control
Journal
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
Volume 15, Issue 6, Pages 2892-2905
Publisher
Springer Nature
Online
2017-10-07
DOI
10.1007/s12555-016-0650-1
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Neural network based adaptive fuzzy PID-type sliding mode attitude control for a reentry vehicle
- (2016) Zhen Jin et al. INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
- Adaptive nonsingular fast terminal sliding mode guidance law with impact angle constraints
- (2016) Junhong Song et al. INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
- Modeling and analysis of stick-slip motion in a linear piezoelectric ultrasonic motor considering ultrasonic oscillation effect
- (2016) Xiang Li et al. INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
- Continuous Nonsingular Terminal Sliding-Mode Control of Shape Memory Alloy Actuators Using Time Delay Estimation
- (2015) Maolin Jin et al. IEEE-ASME TRANSACTIONS ON MECHATRONICS
- Inverse modeling and control of a dielectric electro-active polymer smart actuator
- (2015) Bui Ngoc Minh Truong et al. SENSORS AND ACTUATORS A-PHYSICAL
- Design and optimization of a modal- independent linear ultrasonic motor
- (2014) Shengli Zhou et al. IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL
- Filtering design for two-dimensional Markovian jump systems with state-delays and deficient mode information
- (2014) Yanling Wei et al. INFORMATION SCIENCES
- Self-tuning speed control of ultrasonic motor combined with efficiency optimization
- (2014) Jingzhuo Shi et al. INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
- New approach to delay-dependent H ∞ filtering for discrete-time Markovian jump systems with time-varying delay and incomplete transition descriptions
- (2013) Yanling Wei et al. IET Control Theory and Applications
- A hysteresis functional link artificial neural network for identification and model predictive control of SMA actuator
- (2012) Nguyen Trong Tai et al. JOURNAL OF PROCESS CONTROL
- Identification of an ionic polymer metal composite actuator employing Preisach type fuzzy NARX model and Particle Swarm Optimization
- (2012) Doan Ngoc Chi Nam et al. SENSORS AND ACTUATORS A-PHYSICAL
- Stability for Neural Networks With Time-Varying Delays via Some New Approaches
- (2012) Oh-Min Kwon et al. IEEE Transactions on Neural Networks and Learning Systems
- Output Feedback Direct Adaptive Controller for a SMA Actuator With a Kalman Filter
- (2011) Nguyen Trong Tai et al. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
- Speed Control of a Hydraulic Pressure Coupling Drive Using an Adaptive Fuzzy Sliding-Mode Control
- (2011) Triet Hung Ho et al. IEEE-ASME TRANSACTIONS ON MECHATRONICS
- A RBF neural network sliding mode controller for SMA actuator
- (2011) Nguyen Trong Tai et al. INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
- Adaptive Sliding-Mode Position Control for Piezo-Actuated Stage
- (2009) Xinkai Chen et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- Disturbance-Observer-Based Hysteresis Compensation for Piezoelectric Actuators
- (2009) Jingang Yi et al. IEEE-ASME TRANSACTIONS ON MECHATRONICS
- Design and implementation of an adaptive recurrent neural networks (ARNN) controller of the pneumatic artificial muscle (PAM) manipulator
- (2009) Kyoung Kwan Ahn et al. MECHATRONICS
Add your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload NowCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now