Robust stabilization of LTI negative imaginary systems using the nearest negative imaginary controller

This paper considers the problem of robust stabilization of linear time-invariant systems with respect to unmodelled dynamics and structure uncertainties. To that end, a methodology to find the nearest negative imaginary system for a given non-negative imaginary system is presented first. Then, this result is employed to construct a near optimal linear quadratic Gaussian controller achieving desired performance measures. The problem is formulated using port-Hamiltonian method and the required conditions are defined in terms of linear matrix inequalities. The technique is presented using the fast gradient method to solve the problem systematically. The designed controller satisfies a negative imaginary property and guarantees a robust feedback loop. The effectiveness of the approach is demonstrated by a simulation on a numerical example. The paper presents a methodology to find the nearest negative imaginary system for a given non-negative imaginary system. Then, this result is employed to construct a near optimal linear quadratic Gaussian controller that achieves the desired performance measures.image

Automated summary

This paper presents a methodology to find the nearest negative imaginary system and employs the result to construct a near optimal linear quadratic Gaussian controller. The problem is formulated using port-Hamiltonian method and the required conditions are defined in terms of linear matrix inequalities. The technique is solved systematically using the fast gradient method.