An LPV Approach to Sensor Fault Diagnosis of Robotic Arm

One of the major challenges in robotic arms is to diagnosis sensor fault. To address this challenge, this paper presents an LPV approach. Initially, the dynamics of a two-link manipulator is modelled with a polytopic linear parameter varying structure and then by using a descriptor system approach and a robust design of a suitable unknown input observer by means of pole placement method along with linear matrix inequalities, in addition to providing an estimate of state variables for using in state feedback, the detection, isolation, and identification of sensor faults in the manipulator are addressed. The proposed observer provides a robust estimate of the faults along with attenuating the disturbance effects. Further, the desired angles of the joints are calculated for achieving the desired trajectory of the robot’s end-effector using the inverse kinematics and by designing a suitable state feedback law with integral mode, the reference signals are tracked. The sufficient condition for stability of the closed-loop system is obtained as a set of linear matrix inequalities at the vertices of the system. The efficiency and effectiveness of the control system, along with the designed fault diagnosis unit, are shown using numerical simulations.

Keywords:

Fault diagnosis , Linear Parameter Varying , Polytopic Model , Descriptor System , Unknown Input Observer , Robotic Manipulator , Inverse Kinematics