Design of H∞Control and Simplified Instrument Fault Detection on DC Motor

In the presence of uncertainty, a closed-loop system must be able to maintain its stability and performance. Uncertainty can be categorized into two meanings, disturbance from external systems and perturbation in a dynamical system. In this paper, we will present a robust control design by considering a disturbance from external factors, and analyze its robustness using Structured Singular Value respect to parametric uncertainty and external disturbance. Beside that, every control system has their own region to operate, outside that region a performance degradation will occur, and led into unstability. One factor to that catastrophic is a fault in instrument reading, to anticipate it, this paper also implement Simplified Instrument Fault Detection method to detect a sensor fault in order to give an alarm for further action.

Design of H∞Control and Simplified Instrument Fault Detection on DC Motor

In the presence of uncertainty, a closed-loop system must be able to maintain its stability and performance. Uncertainty can be categorized into two meanings, disturbance from external systems and perturbation in a dynamical system. In this paper, we will present a robust control design by considering a disturbance from external factors, and analyze its robustness using Structured Singular Value respect to parametric uncertainty and external disturbance. Beside that, every control system has their own region to operate, outside that region a performance degradation will occur, and led into unstability. One factor to that catastrophic is a fault in instrument reading, to anticipate it, this paper also implement Simplified Instrument Fault Detection method to detect a sensor fault in order to give an alarm for further action.

An extension of the structured singular value to nonlinear systems with application to robust flutter analysis

The paper discusses an extension of $$\mu$$ μ (or structured singular value), a well-established technique from robust control for the study of linear systems subject to structured uncertainty, to nonlinear polynomial problems. Robustness is a multifaceted concept in the nonlinear context, and in this work the point of view of bifurcation theory is assumed. The latter is concerned with the study of qualitative changes of the steady-state solutions of a nonlinear system, so-called bifurcations. The practical goal motivating the work is to assess the effect of modeling uncertainties on flutter, a dynamic instability prompted by an adverse coupling between aerodynamic, elastic, and inertial forces, when considering the system as nonlinear. Specifically, the onset of flutter in nonlinear systems is generally associated with limit cycle oscillations emanating from a Hopf bifurcation point. Leveraging $$\mu$$ μ and its complementary modeling paradigm, namely linear fractional transformation, this work proposes an approach to compute margins to the occurrence of Hopf bifurcations for uncertain nonlinear systems. An application to the typical section case study with linear unsteady aerodynamic and hardening nonlinearities in the structural parameters will be presented to demonstrate the applicability of the approach.