Adaptive neural higher order terminal sliding mode controller application to trajectory tracking of robotic manipulator

This paper proposes a hybrid control scheme based on Non-singular Terminal Sliding Mode Control (NTSMC), Higher Order Sliding Mode (HOMS) and Neural Network (NN) structure for n-DOF robot manipulator. The NTSMC is used with time delay estimation method (TDE). Through TDE the equivalent control is designed without needs of system model. The HOMS consists of the Super Twisting algorithm which is estimated using Radial Based Function Neural Network (RBFNN). The stability is verified using candidate Lyapunov function and the parameters' of the designed controller are adjusted adaptively. The superiority and the effectiveness of the proposed approach are examined under 2-DOF robotic manipulator in trajectory tracking mode and compared with classical case.