Design Gradient Descent Optimal Sliding Mode Control of Continuum Robots

In this research, a new approach for gradient descent optimal sliding mode controller for continuum robots is proposed. Based on the new dynamic models developed, a novel technique for nonlinear control of continuum manipulators to be employed in various situations has also been proposed and developed. A section of a continuum arm is modeled using lumped model elements (masses, springs and dampers) and control by nonlinear methodology (sliding mode method) and optimization the sliding surface slope by gradient descent method. It is shown that this type of control methodology, although used to a certain model, can be used to conveniently control the dynamics of the arm with suitable tradeoff in accuracy of modeling. This relatively controller is more plausible to implement in an actual real-time when compared to other techniques of nonlinear controller methodology of continuum arms. Principles of sliding mode methodology is based on derive the sliding surface slope and nonlinear dynamic model and applied in the system. Based on the gradient descent optimization method, the sliding surface slope and gain updating factor has been developed in certain and partly uncertain continuum robots. This methodology is represented in certain and uncertain area whose only optimization for certain area and test this optimization for uncertainty. The new techniques proposed and methodologies adopted in this paper supported by MATLAB/SIMULINK results represent a significant contribution to the field of design an optimized nonlinear sliding mode controller for continuum robots.