Data-driven sliding mode control of shape memory alloy actuators with prescribed performance

In this paper, a novel data-driven model-free adaptive fractional-order sliding mode controller with prescribed performance is proposed for the shape memory alloy (SMA) actuator. Due to the strong asymmetric saturated hysteresis nonlinear characteristics of the SMA actuators, it is not easy to establish an accurate model and develop an effective controller. Therefore, we present a controller without using the model of the SMA actuators. In other words, the proposed controller depends merely on the input/output (I/O) data of the SMA actuators. To obtain the reasonable compensation for hysteresis, enhance the noise robustness of the controller, and reduce the chattering, a fractional-order sliding mode controller with memory characteristics is employed to improve the performance of the controller. In addition, the prescribed performance control (PPC) strategy is introduced in our work to guarantee the tracking errors converge to a sufficiently small boundary and the convergence rate is not less than a predetermined value which are significant and considerable in practical engineering applications of the SMA actuator. Finally, experiments are carried out, and results reveal the effectiveness and success of the proposed controller. Comparisons with the classical Proportional Integral Differential (PID), model-free adaptive control (MFAC), and model-free adaptive sliding mode control (MFAC-SMC) are also performed.

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Indirect Intelligent Sliding Mode Control of Antagonistic Shape Memory Alloy Actuators Using Hysteretic Recurrent Neural Networks

IEEE Transactions on Control Systems Technology ◽

10.1109/tcst.2013.2272420 ◽

2014 ◽

Vol 22 (3) ◽

pp. 921-929 ◽

Cited By ~ 11

Author(s):

Jennifer Hannen Wiest ◽

Gregory D. Buckner

Keyword(s):

Neural Networks ◽

Shape Memory Alloy ◽

Sliding Mode Control ◽

Shape Memory ◽

Recurrent Neural Networks ◽

Sliding Mode ◽

Mode Control

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Hybrid Control of Offshore Jacket Platforms Using Decentralized Sliding Mode Control and Shape Memory Alloy-Rubber Bearing Under Multiple Hazards

Journal of Offshore Mechanics and Arctic Engineering ◽

10.1115/1.4044361 ◽

2019 ◽

Vol 142 (1) ◽

Author(s):

Diptesh Das ◽

Minaruddin Khan

Keyword(s):

Shape Memory Alloy ◽

Sliding Mode Control ◽

Shape Memory ◽

Control Algorithm ◽

Hybrid Control ◽

Sliding Mode ◽

High Energy ◽

Multiple Hazards ◽

Mr Dampers ◽

Mode Control

Abstract The motivation and objective of the present study are to propose a hybrid control system for offshore jacket platforms to mitigate the vibrations induced by multiple hazards, namely, the earthquakes and regular and irregular waves. State-of-the-art indicates that not much work is reported on hybrid control of offshore jacket platforms for multiple hazards using a control algorithm, which is robust against uncertainties. A decentralized sliding mode control algorithm using magneto-rheological (MR) dampers is employed for the semi-active controller because of its robustness against parametric uncertainties and reliability. Passive shape memory alloy rubber bearings (SMARBs) are selected as passive isolators because of their high damping capacities, high fatigue resistance, and super elastic behavior, which are highly desirable for offshore applications. The scope of the present study is to demonstrate the efficiency of the proposed controller and investigate the effects of different influencing parameters. A jacket platform, reported in the literature, is taken as an illustrative example. A significant reduction in the top deck displacement is observed. The position and number of MR dampers affect the performance of the controller significantly. Limitations of the controller imposed due to the greater weightage or penalty imposed on displacements by the semi-active control algorithm as well as due to the magnetic saturation of MR dampers are overcome by the high energy dissipation of the passive SMARBs, thus making the hybrid controller highly efficient. The effectiveness of the controller is more for the earthquakes and random waves than for the regular waves.

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