Dynamically balanced hopping robots have been extensively studied for the past two decades. Usually powerful hydraulic or electrical actuators are harnessed for the control of the hopping robot. Our research is focused on developing a real-time embedded controller for a hopping robot powered by a pneumatic actuator, which is more cost effective and it enjoys higher power to mass ratio than its counterpart, electromechanical actuators. A mathematical model is derived for the pneumatically actuated hopper considering the actuator and control valve dynamics.; A real world prototype of a one-legged hopping robot was designed and constructed. Proportional (P), Proportional and Derivative (PD), Proportional and Derivative and Integral (PID) and Inverse dynamics based PD (i.e. Artificial Neural Network-based PD) control algorithms were implemented on the real prototype and their performances were compared. A PD controller in conjunction with an Artificial Neural Network representing the nonlinear relationship between the control input and the measured state of the system yielded promising results.
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