Abstract
This work presents a new discrete-time adaptive-predictive control algorithm for a system with force disturbance and input delay. This scenario is representative of a mechatronic device for percutaneous intervention with pneumatic actuation and long supply lines which is controlled remotely in the presence of an unknown external force resulting from needle-tissue interaction or gravity. The ultimate goal of this research is the robotic-assisted percutaneous intervention of the liver under Magnetic Resonance Imaging (MRI) guidance. Since the control algorithm is intended for a digital microcontroller, it is presented in the discrete-time form. The controller design is illustrated for a 1 degree-of-freedom (DOF) system and is conducted with a modular approach combining position control, adaptive disturbance compensation, and predictive control. The controller stability is analyzed and the effect of the input delay and of the tuning parameters is discussed. The controller performance is assessed with simulations considering a disturbance representative of needle insertion forces. The results indicate that the adaptive-predictive controller is effective in the presence of a variable disturbance and of a known or variable input delay.
Highlights
Mechatronics instruments for magnetic resonance imaging (MRI)-guided intervention allow conducting complex procedures that would otherwise be very time consuming and error prone (Tse et al, 2012; Yang et al, 2014; Franco et al, 2016)
While input delay is an ubiquitous phenomenon in systems characterized by transportation or transmission, the particular case of a pneumatically actuated master-slave system for percutaneous intervention operating with an impedance-control scheme is considered here as a motivating example for the new adaptivepredictive control algorithm
This paper presented a discrete-time control scheme that combines adaptive and predictive algorithms for a system subject to force disturbance and input delay
Summary
Mechatronics instruments for magnetic resonance imaging (MRI)-guided intervention allow conducting complex procedures that would otherwise be very time consuming and error prone (Tse et al, 2012; Yang et al, 2014; Franco et al, 2016). Pneumatic actuation represents a clean, affordable, and safe solution It has been used in several robots for MRI-guided intervention (Melzer et al, 2008; Stoianovici et al, 2014). In order to minimize image degradation, several systems employ a control unit and a power source located outside the MRI room, supplying the robot through long transmission lines (Yang et al, 2011; Iranpanah et al, 2015; Franco et al, 2016). While recent research has proposed the use of steerable needles for MRI-guided percutaneous intervention (Comber et al, 2016), more work is required before this solution could become clinically viable
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