Sliding Mode Control (SMC) technique is a well-established method in positioning pneumatic actuators due to its consistent performance in the presence of model uncertainties. Brain Emotional Learning Based Intelligent Controller (BELBIC) is a new model free controller with flexible structure and low computational load. It has been successfully applied to many control problems. In this work we study, for the first time, how well a BELBIC performs in comparison with SMC approach in positioning a pneumatic actuator. Different position tracking tasks are evaluated on a low-cost pneumatic actuator and in presence of significant friction. Comparison is done based on positioning accuracy, non-oscillatory motion and robustness to external load. The results show that while both controllers successfully track different trajectories, SMC is generally more accurate. BELBIC maintains its performance in the presence of large static friction. Furthermore, it produces less oscillatory control action. This work concludes that BELBIC can be a good choice for positioning of pneumatic actuators.

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