In this paper, a novel, unified model-based fault-detection and prediction (FDP) scheme is developed for nonlinear multiple-input-multiple-output (MIMO) discrete-time systems. The proposed scheme addresses both state and output faults by considering separate time profiles. The faults, which could be incipient or abrupt, are modeled using input and output signals of the system. The fault-detection (FD) scheme comprises online approximator in discrete time (OLAD) with a robust adaptive term. An output residual is generated by comparing the FD estimator output with that of the measured system output. A fault is detected when this output residual exceeds a predefined threshold. Upon detecting the fault, the robust adaptive terms and the OLADs are initiated wherein the OLAD approximates the unknown fault dynamics online while the robust adaptive terms help in ensuring asymptotic stability of the FD design. Using the OLAD outputs, a fault diagnosis scheme is introduced. A stable parameter update law is developed not only to tune the OLAD parameters but also to estimate the time to failure (TTF), which is considered as a first step for prognostics. The asymptotic stability of the FDP scheme enhances the detection and TTF accuracy. The effectiveness of the proposed approach is demonstrated using a fourth-order MIMO satellite system.

A Model-Based Fault-Detection and Prediction Scheme for Nonlinear Multivariable Discrete-Time Systems With Asymptotic Stability Guarantees

A controller for solving the tracking problem of flexible robot arms is presented. In order to achieve this goal, the desired trajectory for the link (flexible) coordinates is computed from the dynamic model of the robot arm and is guaranteed to be bounded, and the desired trajectory for the joint (rigid) coordinates can be assigned arbitrarily. The case of no internal damping is also considered, and a robust control technique is used to enhance the damping of the system.

On tracking control of flexible robot arms

The authors present a simple approach for designing tracking controllers for rigid-link flexible-joint robot manipulators. The control approach is intuitively simple since it is based on concepts which are familiar to most control engineers. To illustrate the approach, the authors develop a robust tracking controller that achieves global uniform ultimate boundedness, stability of the link tracking error in spite of bounded disturbances, and model uncertainty. They then discuss some extensions for rigid-link electrically driven and for rigid-link flexible-joint electrically driven robot manipulators. >

Robust tracking of rigid-link flexible-joint electrically-driven robots

Presents an approach for designing robust tracking controllers for rigid-link flexible-joint (RLFJ) robot manipulators with redundant actuators in the joints. With the proposed controller, the authors prove that the link tracking error is globally uniformly ultimately bounded (GUUB) in spite of additive bounded disturbances, parametric uncertainty, and other modeling uncertainty. The authors also illustrate how the load at each joint is shared by two actuators. Finally simulation results are presented to illustrate the effectiveness of the proposed controller. >

Robust control of rigid-link flexible-joint robots with redundant joint actuators

Brief Tracking control of flexible robot arms with a nonlinear observer

The authors describe two classes of robust controllers for the tracking of robot motion. The controllers are simple linear proportional derivative (PD) controllers plus a nonlinear term that compensates for the uncertainties present in the manipulator dynamic equation. The main result is that it is explicitly shown that the response of the tracking error can be modified by adjusting the control parameters. The corresponding stability result for the tracking error for the two classes of controllers presented are global uniform ultimate boundedness and global exponential stability. >

http://ieeexplore.ieee.org/iel2/607/6597/00261482.pdf

S. Lim

Papers

Re-thinking the robust control of robot manipulators