The shape memory alloy (SMA)-based robotic hand has been a new emerging technology with potential applications ranging from life service to surgical treatment, because of the characteristics of SMA, such as high power-to-weight ratio, small volume and low driving voltage. However, due to the complex dynamic model and nonlinear aspects of SMA, it is complicated to control an SMA-based robotic hand. This paper presents a novel model free adaptive control for the SMA-based robotic hand system. By applying the Taylor series expansion method and the differential mean value theorem, the SMA based robotic hand system can be transformed into an equivalent linearization model, which merely depends on measurement data without any information on the system. Combined with prescribed performance control, the novel control method can constrain the tracking error in a preassigned domain. Experiments are conducted on the SMA-based robotic hand system to verify the performance of the presented control method.
In this study, a model-free adaptive sliding mode control method was developed in combination with the prescribed performance method. On this basis, this study attempted to fulfill the joint position tracking trajectory task for the one-degree of freedom (DOF) upper-limb exoskeleton in passive robot-assisted rehabilitation. The proposed method is capable of addressing the defect of the initial error in the controller design and the application by adopting a tuning function, as compared with other prescribed performance methods. Moreover, the method developed here was not determined by the dynamic model parameters, which merely exploit the input and output data. Theoretically, the stability exhibited by the proposed controller and the tracking performance can be demonstrated. From the experimental results, the root mean square of the tracking error is equal to 1.06 degrees, and the steady-state tracking error converges to 1.91 degrees. These results can verify the expected performance of the developed control method.
Shape memory alloy (SMA), a kind of smart material, can be used as an actuator in many fields; however, its strong nonlinearity and parameter uncertainty hinders its application in high-tracking accuracy tasks. This paper addresses the tracking control problem of the shape memory alloy actuated swing platform suffering from completely unknown nonlinear model information and prescribed finite-time error constraints. First, the equivalent dynamic linearization model of the swing platform is established, and the unknown disturbance is estimated and compensated by the extended state observer (ESO). Meanwhile, a novel discrete-time performance function is proposed, and the prescribed finite-time tracking error constraints are transformed into a new equivalent unconstrained task. Second, the model-free adaptive sliding mode controller is designed by using the unconstrained error, and the complete control law, including sliding mode control law and equivalent control law, is derived. Third, the stability of the closed-up swing platform is guaranteed by employing the Lyapunov method. Finally, experiments reveal that the proposed method is preferable.
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