A Neural-Network-Based Controller for Piezoelectric-Actuated Stick–Slip Devices

Cheng, Long; Liu, Weichuan; Yang, Chenguang; Huang, Tingwen; Hou, Zeng-Guang; Tan, Min

doi:10.1109/tie.2017.2740826

Cited by 105 publications

(39 citation statements)

References 32 publications

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“…Using a subspace-based modelling technique as described in [16], the system is identified. The modelling methods such as neural networks or genetic algorithms [17,18] are typically used to model systems where all parameters are not directly identifiable. Typically, a simple second-order transfer function with a suitably low damping coefficient and the correct resonant frequency is sufficient to capture the dominant in-bandwidth dynamics of a nanopositioner's axis.…”

Section: Linear Dynamics Modelmentioning

confidence: 99%

High-Precision Control of a Piezo-Driven Nanopositioner Using Fuzzy Logic Controllers

Altaher

Aphale

2018

Computers

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This paper presents single-and dual-loop fuzzy control schemes to precisely control the piezo-driven nanopositioner in the x-and y-axis directions. Various issues are associated with this control problem, such as low stability margin due to the sharp resonant peak, nonlinear dynamics, parameter uncertainty, etc. As such, damping controllers are often utilised to damp the mechanical resonance of the nanopositioners. The Integral Resonant Controller (IRC) is used in this paper as a damping controller to damp the mechanical resonance. A further inherent problem is the hysteresis phenomenon (disturbance), which leads to degrading the positioning performance (accuracy) of the piezo-driven stage. The common approach to treat this disturbance is to invoke tracking controllers in a closed-loop feedback scheme in conjunction with the damping controllers. The traditional approach uses the Integral Controller (I) or Proportional Integral (PI) as a tracking controller, whereas this paper introduces the Proportional and Integral (PI)-like Fuzzy Logic Controller (FLC) as a tracking controller. The effectiveness of the proposed control schemes over conventional schemes is confirmed through comparative simulation studies, and results are presented. The stability boundaries of the proposed control schemes are determined in the same way as with a conventional controller. Robustness against variations in the resonant frequency of the proposed control schemes is verified.

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Section: Linear Dynamics Modelmentioning

confidence: 99%

High-Precision Control of a Piezo-Driven Nanopositioner Using Fuzzy Logic Controllers

Altaher

Aphale

2018

Computers

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“…These vibrational transients are undesirable in industrial settings because they not only waste time in settling down, thus decreasing productivity, but also introduce structural defects in the soft robot, which reduces its useful lifespan [12], [13]. The problem of undesirable deactuation transients in soft robots require the utmost attention to increase their viability in real-world applications [14], [15].…”

Section: Introductionmentioning

confidence: 99%

Sliding Mode Control With PID Sliding Surface for Active Vibration Damping of Pneumatically Actuated Soft Robots

Khan

2020

IEEE Access

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This paper proposes a novel active vibration damping mechanism for soft robots. In recent years, soft robots have gained increasing research attention for robotic researchers and industrial developers alike. Soft robots offer a significant number of advantages when it comes to the handling of fragile objects, clinical rehabilitation tasks, and human-machine interaction. Soft robots demonstrate a high degree of compliance and safety because of their inherent softness, achieving the same with rigid robots will require intricate controller design and sensing mechanisms. However, the most commonly used soft robots use pneumatic systems for actuation. These pneumatic soft robots undergo large amplitude vibrations when deactuated suddenly. These vibrations not only decrease the accuracy of these soft robots but also compromise their structural integrity, which results in a decrease in their useable lifespan. An active vibration damping mechanism is very much needed to increase the utility of soft robots in industrial applications. To accurately control the dynamic behavior of soft robots, we propose a sliding mode based controller with PID sliding surface. The proposed controller uses feedback error to define a PID sliding surface, and a nonlinear sliding mode controller works to keep the system attached to the sliding surface. The coefficients of the PID sliding surface determine the dynamic behavior of the soft robot. The performance of the proposed controller is verified by using a multi-chambered parallel soft robot. The experimental results demonstrate that the proposed controller can suppress vibration amplitude to a decidedly smaller range. INDEX TERMS Soft robot, sliding mode control, active damping, parallel-soft robot, multi-chambered soft robot.

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“…At present, there are many methods to control the active suspension system, including linear quadratic optimal control [7], [8], PID control [9], [10], adaptive control [11]- [16], neural network control [17]- [20], [29], and sliding mode variable structure control [21]- [23]. These suspension control methods can improve the ride comfort and ride stability of the vehicle.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Fault Tolerant Control of Active Suspension Systems With Time-Varying Displacement and Velocity Constraints

Zhang

Liu

2020

IEEE Access

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In this paper, active suspension system is selected as the research object. Back-stepping method is adopted, and virtual fault tolerant controller, main fault tolerant controller and adaptive law are designed by constructing Time-varying Barrier Lyapunov Function (TVBLF), to ensure that the displacement and speed of the vehicle do not violate the constraint boundary and achieve the goal of fast fault tolerance. For the unknown continuous function caused by the uncertain body mass and other factors in the system, Radial Basis Function Neural Network (RBFNN) is used for approximation. At the same time, the suspension space limitation and tire dynamic load are analyzed. Finally, the effectiveness of the proposed fault-tolerant control method is verified by simulation of deviation fault and partial failure fault. INDEX TERMS Fault-tolerant control, semi-vehicle active suspension system, time-varying displacement, velocity constraints.

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A Neural-Network-Based Controller for Piezoelectric-Actuated Stick–Slip Devices

Cited by 105 publications

References 32 publications

High-Precision Control of a Piezo-Driven Nanopositioner Using Fuzzy Logic Controllers

High-Precision Control of a Piezo-Driven Nanopositioner Using Fuzzy Logic Controllers

Sliding Mode Control With PID Sliding Surface for Active Vibration Damping of Pneumatically Actuated Soft Robots

Adaptive Fault Tolerant Control of Active Suspension Systems With Time-Varying Displacement and Velocity Constraints

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