In this paper, the analytical dynamic model derivation and the robust and optimal position control of Shape Memory Alloy (SMA) bundle actuators using the LQR and H 2 techniques are presented. SMA bundle actuators, composed of multiple SMA wires placed in parallel, have been recently proposed as a means to considerably increase the lifting capabilities of SMA actuators. Robust and optimal linear controllers could provide the desired robustness in the performance of these nonlinear and highly sensitive actuators combined with the simplicity of these control schemes. The novel contributions of the present research are: a) the derivation of a generic, linearized, time-invariant analytical system model for SMA Bundle actuators that is used in the design of the LQR and H 2 based controllers; b) the development of a new improved estimator in discrete-time H 2 optimal control design based on the Kalman Filter predictor form for use in the control of SMA bundle actuators; c) the experimental study of two control design methods using state-space models, LQR and H 2 Optimal Design, in discrete-time domain, using an experimental SMA bundle actuator consisting of 48 Flexinol SMA wires and able to apply up to 100 lbs. (445 N). As demonstrated in the experiments, the designed controllers provide satisfactory results in accuracy, stability and speed.
A different option is the optimal controller based on the LQR method adopted by Lee and Mavroidis to control SMA actuators REF .
Analytical Dynamic Model and Experimental Robust and Optimal Control of Shape-Memory-Alloy Bundle Actuators
Dynamic Systems and Control
Dynamic Systems and Control
Engineering