Shape memory alloys (SMAs) offer a high power-to-weight ratio, large recovery strain, and low driving voltages, and have thus attracted considerable research attention. The difficulty of controlling SMA actuators arises from their highly nonlinear hysteresis and temperature dependence. This paper describes a combination of self-sensing and model-based control, where the model includes both the major and minor hysteresis loops as well as the thermodynamics effects. The self-sensing algorithm uses only the power width modulation (PWM) signal and requires no heavy equipment. The method can achieve high-accuracy servo control and is especially suitable for miniaturized applications.

Mechanical devices usually come with undesirable nonlinearities, such as friction, backlashes, and saturations. Under the assumption of linear systems, the commonly seen identification schemes utilize sinusoidal excitation signals for parameter identification. However, the data needed for identification are unavoidably distorted by the aforementioned nonlinearities and the identification result may not be satisfactory. In the paper, binary test signals are used to perform identification, thus simplifying the behavior of friction. An identification method based on the difference of binary multifrequency excitation signals is proposed. The modified identification algorithm does not suffer from the problem of nonlinear distortions in the signal shape and is able to determine the nonlinear friction such that an accurate servo system model can be derived. A high-precision ball-screw table with asymmetric friction is identified as a test plant for this approach. The results prove that the method can be used very successfully.

This paper proposes a variable-sampling variable structure controller (VSC) for brushless dc (BLDC) motor drives with low-resolution position sensors (Hall sensors). The variable-sampling characteristics arising from the situation where measurements depend on the path-embedded sensors will result in the uncertainty of the discrete-time models. To circumvent this issue, a modification of the conventional discrete-time VSC control law for BLDC motor drives with Hall sensors is derived to achieve the robustness of speed control. Three measurement error-mitigation methods are also presented to reduce the errors due to low-resolution position feedback. Both simulated and experimental results confirm the effectiveness of the proposed controller and error-mitigation techniques.