SUMMARY Many different control schemes have been proposed in the technical literature to control the special class of underactuated systems, the- so-called brachiation robots. However, most of these schemes are limited with regard to the method by which the robot executes the brachiation movement. Moreover, many of these control strategies do not take into account the energy of the system as a decision variable. To observe the behavior of the system’s, energy is very important for a better understanding of the robot dynamics while performing the motion. This paper discusses a variety of energy-based strategies to better understand how the system’s energy may influence the type of motion (under-swing or overhand) the robot should perform.

AbstractIn this work, the effectiveness of the adaptive neural based fuzzy inference system (ANFIS) in identifying underactuated systems is illustrated. Two case studies of underactuated systems are used to validate the system identification i. e., linear inverted pendulum (LIP) and rotary inverted pendulum (RIP). Both the systems are treated as benchmark systems in modeling and control theory for their inherit nonlinear, unstable, and underactuated behavior. The systems are modeled with ANFIS using the input-output data acquired from the dynamic response of the nonlinear analytical model of the systems. The dynamic response of the ANFIS model is simulated and compared to the nonlinear mathematical model of the inverted pendulum systems. In order to check the effectiveness of the ANFIS model, mean square error is used as the performance index. From the obtained simulation results, it has been perceived that the ANFIS model performed satisfactorily within the trained operating range while a minor deviation is seen outside the trained operating region for both the case studies. Furthermore, the experimental validation of the of the proposed ANFIS model is done by comparing it with the experimental model of the rotary inverted pendulum. The obtained results show that the response of ANFIS model is in close agreement to the experimental model of the rotary inverted pendulum.