Adaptive Friction Compensation for Mechanisms: A New Perspective

Guerra, Ricardo; Acho, Leonardo; Aguilar, Luis T.

doi:10.2316/journal.206.2007.2.206-2942

Cited by 7 publications

(4 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Finally, outcomes interesting that, from the experimental results, the tracking error is significantly reduced when the closed-loop system is operated with enough velocity on its reference command. This is also observed in the proposed controllers in [21,22]. Hence, we can arrive to the same conclusion: that the tracking error is reduced if the system is operated with enough velocity.…”

supporting

confidence: 77%

A Recent Electronic Control Circuit to a Throttle Device

2020

View full text Add to dashboard Cite

The main objective of this paper was to conceive a new electronic control circuit to the throttle device. The throttle mechanical actuator is the most important part in an automotive gasoline engine. Among the different control strategies recently reported, an easy to implement control scheme is an open research topic in the analog electronic engineering field. Hence, we propose using the nonlinear dwell switching control theory for an analog electronic control unit, to manipulate an automotive throttle plate. Due to the switching mechanism commuting between a stable and an unstable controllers, the resultant closed-loop system is robust enough to the control objective. This fact is experimentally evidenced. The proposed electronic controller uses operational amplifiers along with an Arduino unit. This unit is just employed to generate the related switching signal that can be replaced by using, for instance, the timer IC555. Thus, this study is a contribution on design and realization of an electronic control circuit to the throttle device.

show abstract

supporting

confidence: 77%

A Recent Electronic Control Circuit to a Throttle Device

2020

View full text Add to dashboard Cite

show abstract

“…It is important to note that this kind of result has been reached, for instance, in [25,26]. Next, the control law (2) applied to (1) stabilizes the system.…”

Section: Control Designmentioning

confidence: 80%

A Proportional Plus a Hysteretic Term Control Design: A Throttle Experimental Emulation to Wind Turbines Pitch Control

Acho

2019

Energies

View full text Add to dashboard Cite

Pitch control is a relevant issue in wind turbines to properly operate the angle of the blades. Therefore, this control system pitches the blades usually a few degrees every time the wind changes in order to keep the rotor blades at the required angle thus controlling the rotational speed of the turbine. All the same time, the control of the pitch angle is not easy due to the system behavior being highly nonlinear. Consequently, the main objective of this paper is to depict an easy to implement control design based on a proportional controller and a hysteretic term to an emulator pitch control system in wind turbines. This emulator is just an automotive throttle device. This mechanical body dynamically captures some hard non-linearities presented in pitch wind turbine mechanisms, such as backlash, asymmetrical non-lineal effects, friction, and load variations. Even under strong non-linear effects that are difficult to model, a proportional controller and a hysteretic term may satisfy the main control design objective. Hence, a recent control design is developed and applied to a throttle system. We invoke the Lyapunov theory to confirm stability of the resultant closed-loop system. In addition, the proposed control approach is completely implemented by using operational amplifiers. Hence, no digital units are required at all. Moreover, the cost of the developed experimental platform and its outcomes are inexpensive. According to the experimental results, the controller performance seems acceptable, and validating of the control contribution too. For instance, a settling-time of about 0.03 s to a unit step-response is obtained.

show abstract

“…Applying an accurate friction model can facilitate friction compensation, helping to prevent issues such as slow responses, tracking errors, stick-slip motion, and limit cycles [44,45]. Notably, for dynamic systems developed purely through data-driven approaches, a separate friction model is unnecessary, as frictional losses are already accounted for in the experimental data used to build the model.…”

Section: Dynamic Modeling With Frictionmentioning

confidence: 99%

Time-Series Machine Learning Techniques for Modeling and Identification of Mechatronic Systems with Friction: A Review and Real Application

Ayankoso,

Olejnik

2023

Electronics

View full text Add to dashboard Cite

Developing accurate dynamic models for various systems is crucial for optimization, control, fault diagnosis, and prognosis. Recent advancements in information technologies and computing platforms enable the acquisition of input–output data from dynamical systems, resulting in a shift from physics-based methods to data-driven techniques in science and engineering. This review examines different data-driven modeling approaches applied to the identification of mechanical and electronic systems. The approaches encompass various neural networks (NNs), like the feedforward neural network (FNN), convolutional neural network (CNN), long short-term memory (LSTM), transformer, and emerging machine learning (ML) techniques, such as the physics-informed neural network (PINN) and sparse identification of nonlinear dynamics (SINDy). The main focus is placed on applying these techniques to real-world problems. A real application is presented to demonstrate the effectiveness of different machine learning techniques, namely, FNN, CNN, LSTM, transformer, SINDy, and PINN, in data-driven modeling and the identification of a geared DC motor. The results show that the considered ML techniques (traditional and state-of-the-art methods) perform well in predicting the behavior of such a classic dynamical system. Furthermore, SINDy and PINN models stand out for their interpretability compared to the other data-driven models examined. Our findings explicitly show the satisfactory predictive performance of six different ML models while also highlighting their pros and cons, such as interpretability and computational complexity, using a real-world case study. The developed models have various applications and potential research areas are discussed.

show abstract

Adaptive Friction Compensation for Mechanisms: A New Perspective

Cited by 7 publications

References 9 publications

A Recent Electronic Control Circuit to a Throttle Device

A Recent Electronic Control Circuit to a Throttle Device

A Proportional Plus a Hysteretic Term Control Design: A Throttle Experimental Emulation to Wind Turbines Pitch Control

Time-Series Machine Learning Techniques for Modeling and Identification of Mechatronic Systems with Friction: A Review and Real Application

Contact Info

Product

Resources

About