In robotics, while rigid joints are common due to their accuracy and fast response ability, elastic joints are wellknown for their safety when interacting with the environment. To harmonise the advantages of these joint types, robots with mixed rigid-elastic joints can be considered. In this paper, a robust-adaptive two-loop control algorithm is proposed to control this type of hybrid robots when there are uncertainties in system parameters. In the outer loop, a robust control algorithm is proposed to deal with the uncertainties in the parameters of the joint dynamics, together with an adaptive controller for the rigid joints. In the inner loop, another robust control algorithm is proposed to handle the uncertainties in system parameters of the elastic joint’s motor contribution, and a similar adaptive control algorithm is presented to manipulate the elastic joints’ motors. The stability of the system is assured by Lyapunov’s stability theory. Finally, simulations are conducted to verify the proposed control algorithm.

In this paper, we consider a 2-degrees-of-freedom (DOF) helicopter system subject to input delays and uncertain system parameters. To address this challenge in control design, we develop an adaptive predictor-feedback control law. The control law is designed to compensate for a known delay while considering the system uncertainty. Stability of the closed-loop system is established, where tracking is achieved. We demonstrate the effectiveness of our proposed control approach through simulations of the helicopter system, where the input delays are compensated in the control-loop.

In this paper the attitude tracking control problem of a 2 degrees-of-freedom helicopter system with network induced constraints is studied. A predictor feedback control law is developed to compensate a known delay in the communication, where the inputs are quantized before transmitted over the network. Stability of the closed-loop system is established, where tracking is achieved with bounded tracking errors due to the network issues. The developed predictor-based controller is experimentally tested on the helicopter system, where we demonstrate that tracking is achieved in presence of both input delay and quantization.

This paper proposes a new adaptive controller for a 2-Degree of Freedom (DOF) helicopter system in the presence of input quantization. The inputs are quantized by uniform quantizers. A nonlinear mathematical model is derived for the 2-DOF helicopter system based on Euler-Lagrange equations, where the system parameters and the control coefficients are uncertain. A new adaptive control algorithm is developed by using backstepping technique to track the pitch and yaw position references independently. Only quantized input signals are used in the system which reduces communication rate and cost. It is shown that not only the ultimate stability is guaranteed by the proposed controller, but also the designers can tune the design parameters in an explicit way to obtain the required closed loop behavior. Experiments are carried out on the Quanser helicopter system to validate the effectiveness, robustness and control capability of the proposed scheme.