Adaptive predictive control of a novel shape memory alloy rod actuator

Hoseini, Seyedeh Farzaneh; MirMohammadSadeghi, S. Ali; Fathi, Alireza; Daniali, Hamid Reza Mohammadi

doi:10.1177/0959651820974488

Cited by 7 publications

(10 citation statements)

References 69 publications

(63 reference statements)

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“…56 Similarly, using advanced control strategies, such as feedforward, adaptive, or model predictive control, could help compensate for the slow response time by considering the system dynamics and predicting the actuator's behaviour. 57 In this study, needle deflection control in tissuemimicking gels was performed using a manually tuned PI controller at a low insertion speed of 2 mms −1 , assuming that the effect due to response lag would be small. Furthermore, the tissue medium adds damping to the system compared to the air medium, reducing settling fluctuations and overshoot 58 and reducing response lag.…”

Section: Tip Deflection Tracking Control Of the Active Needlementioning

confidence: 99%

Design and evaluation of shape memory alloy‐actuated active needle using finite element analysis and deflection tracking control in soft tissues

Acharya,

Hutapea

2023

Robotics Computer Surgery

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BackgroundConventional needles lack active mechanisms for large tip deflection to bypass obstacles or guide through a desired trajectory in needle‐based procedures, compromising accuracy and effectiveness.MethodsAn active needle with a shape memory alloy (SMA) actuator was designed and evaluated by demonstrating deflections in tissue‐mimicking gels. Finite element simulation and real‐time needle tip deflection tracking in tissue‐mimicking gels were performed.ResultsThe active needle deflected 50 and 39 mm at 150 mm insertion depth in the liver and prostate mimicking gels, respectively. Reasonable simulation errors of 16.42% and 12.62% in needle deflections and small root mean squared errors of 1.42 and 1.47 mm in deflection tracking were obtained.ConclusionsThe proposed needle produced desirable large tip deflections capable of bypassing obstacles in the insertion path and tracked a preplanned trajectory with minor errors. The finite element study would help optimise needle designs and predict deflections in soft tissues.

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Section: Tip Deflection Tracking Control Of the Active Needlementioning

confidence: 99%

Design and evaluation of shape memory alloy‐actuated active needle using finite element analysis and deflection tracking control in soft tissues

Acharya,

Hutapea

2023

Robotics Computer Surgery

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“…where l 2 (0, 1] and m > 0 are the parameters to be designed. With the help (19), (20), and (21), we can get…”

Section: Controller Designmentioning

confidence: 99%

“…A model predictive controller was proposed for the SMA actuators in the Ref. 19. The hysteresis was compensated by an inverse model combining a rate-dependent (PI) model with a deadband function in the literature, 20 and a PID feedback controller is added to ensure effective position tracking.…”

Section: Introductionmentioning

confidence: 99%

Data-driven model-free adaptive fractional-order sliding mode control for the SMA actuator with prescribed performance

Liu

Hao

Liu

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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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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“…Being intermediate between large cyclic simulations and simplistic transfer functions, the MVM model can estimate the main external variables including manifold pressure and crankshaft speed. MVMs are mostly known as lumped parameter models, that is, systems represented by ordinary differential equations (ODEs) [52,53]. This is why they fit real-time applications.…”

Section: Model Developmentmentioning

confidence: 99%

Development of an Extended Mean Value Model for Control-Oriented Modeling of Gasoline Engines Equipped with Continuously Variable Valve Timing

Bakhshinezhad¹,

Garivani²,

Sadeghi³

et al. 2022

SAE Technical Paper Series

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Model-based control system design is a well-established method for advanced engine control systems. These control systems maintain engine operation at levels that meet stringent environmental regulations on vehicular emissions. However, the models required for model-based design need to be accurate enough for design and pre-calibration and fast enough for optimization and implementation purposes. On the other hand, the variable valve timing (VVT) technology significantly affects the dynamic performance of internal combustion engines. This study aims at developing a control-oriented, extended mean-value model (EMVM) of a gasoline engine, taking into account the effects of VVT on the dynamic model. The developed model analyzes the engine's performance characteristics in transient and steady-state regimes. The engine model incorporates four peripheral, nonlinear, dynamic subsystems: manifold, fuel injection, wall-film adhesion, and evaporation processes. Moreover, lying at the core of the developed model is a nonlinear, static, in-cylinder process (ICP) model which simulates gas exchange and combustion processes based on the cylinder's boundary conditions. Based on the experimental data obtained from the engine test setup, an artificial neural network has been trained to predict the in-cylinder processes as a single model. The ICP model was integrated into the dynamic peripheral models to form the final EMVM model. The results of the developed model were compared to the engine experimental tests for two test scenarios: half-throttle and full-throttle cases. It was observed that the developed model could accurately simulate the engine speed, inlet air pressure, aspirated air mass, and exhaust temperature. Moreover, the EMVM model could successfully predict the effects of VVT in the performance of ICEs.

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Adaptive predictive control of a novel shape memory alloy rod actuator

Cited by 7 publications

References 69 publications

Design and evaluation of shape memory alloy‐actuated active needle using finite element analysis and deflection tracking control in soft tissues

Design and evaluation of shape memory alloy‐actuated active needle using finite element analysis and deflection tracking control in soft tissues

Data-driven model-free adaptive fractional-order sliding mode control for the SMA actuator with prescribed performance

Development of an Extended Mean Value Model for Control-Oriented Modeling of Gasoline Engines Equipped with Continuously Variable Valve Timing

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