A Primal-Dual method for low order H∞ controller synthesis (original) (raw)

A Partially Augmented Lagrangian Method for Low Order ${\rm H}$-Infinity Controller Synthesis Using Rational Constraints

IEEE Transactions on Automatic Control, 2012

When designing robust controllers, H-infinity synthesis is a common tool to use. The controllers that result from these algorithms are typically of very high order, which complicates implementation. However, if a constraint on the maximum order of the controller is set, that is lower than the order of the (augmented) system, the problem becomes nonconvex and it is relatively hard to solve. These problems become very complex, even when the order of the system is low. The approach used in this work is based on formulating the constraint on the maximum order of the controller as a polynomial (or rational) equation. This equality constraint is added to the optimization problem of minimizing an upper bound on the H-infinity norm of the closed loop system subject to linear matrix inequality (LMI) constraints. The problem is then solved by reformulating it as a partially augmented Lagrangian problem where the equality constraint is put into the objective function, but where the LMIs are kept as constraints. The proposed method is evaluated together with two wellknown methods from the literature. The results indicate that the proposed method has comparable performance in most cases.

A Quasi-Newton Interior Point Method for Low Order H-Infinity Controller Synthesis

IEEE Transactions on Automatic Control, 2011

This paper proposes a method for low order Hinfinity synthesis where the constraint on the order of the controller is formulated as a rational equation. The resulting nonconvex optimization problem is then solved by applying a quasi-Newton primal-dual interior point method. The proposed method is evaluated together with a well-known method from the literature. The results indicate that the proposed method has comparable performance and speed.

Improved optimisation approach to the robust H2/H∞ control problem for linear systems

IEE Proceedings - Control Theory and Applications, 2005

A strategy for robust H 2 /H 1 state-feedback control synthesis, with regional pole placement, applied to continuous-or discrete-time linear time-invariant uncertain systems is presented. It is based on a multiobjective optimisation over the space of the controller parameters. In the case of systems with polytope-bounded uncertainty, the H 2 and H 1 norms, calculated in all polytope vertices and in possible 'worst case' interior points are taken as the optimisation objectives. An a posteriori exact cost norm computation based on a branch-and-bound algorithm is applied for closed-loop performance assessment. The proposed strategy is applied to continuousand discrete-time examples, including the design of a decentralised controller, and the results are compared with LMI-based formulations. E.N. Gonçalves is with the

Multiobjective Optimization Applied to Robust H2/H∞ State-Feedback Control Synthesis

Proceedings of the 2004 …, 2004

This paper presents an algorithm for robust H2/H∞ state-feedback control synthesis, with regional pole placement, based on a multiobjective optimization algorithm with non-smooth problem-solving capability. The problem is formulated with the state-feedback matrix coefficients as optimization parameters. The closed-loop performance obtained by means of the proposed strategy is assessed for the whole uncertainty-set through an LMI-based H2 and H∞ guaranteed cost computation. The proposed strategy is compared with three former LMI approaches, for systems with polytope-bounded uncertainties, and presents better results.

Robust controller synthesis via non-linear matrix inequalities

International Journal of Control, 1999

Over the last several years xed-structure multiplier versions of MSSV theory have been developed and have led to the development of LMI's for the analysis of robust stability and performance. These LMI's have in turn led to the development of BMI's for the synthesis of robust controllers. The BMI formulation in practice requires the multiplier to lie in the span of a stable basis, potentially introducing signi cant conservatism. This paper uses the LMI approach to MSSV analysis to develop an approach to robust controller synthesis that is based on the stable factors of the multipliers and does not require the multipliers to be restricted to a basis. It is shown that this approach requires the solution of nonlinear matrix inequalities. A continuation algorithm is presented for the solution of NMI's. The primary computational burden of the continuation algorithm is the solution of a series of LMI's.

Robust mixed H 2 /H ∞ optimal controller design

IFAC Proceedings Volumes, 2003

This paper addresses the problem of dynamic output feedback robust mixed H 2 / H"" norm optimal control with regional pole constraints. The problem can be formulated a optimization problem involving LMI, Linear Matrix Inequalities. The main purpose of the robust optimal control problem is to minimize mixed H 2 / H"" norm of the closed loop transfer function matrix under some constraints. In the other words, the main objectives of the robust optimal control is to minimize mixed H 2 / H"" norm of the closed loop transfer function matrix under the system performance constraints. In this paper, mixed H 2 / H"" performance index is minimized under the constraint of H 2 performance, the constraint of H"" performance and the regional pole placement. Recent years LMI are extensively used in control system synthesis. The synthesis problem is solved via LMI.

Improved H2 and H¥ conditions for robust analysis and control synthesis of linear systems

Sba: Controle & Automação Sociedade Brasileira de Automatica, 2005

This paper proposes improved H-2 and H-infinity conditions for continuous-time linear systems with polytopic uncertainties based on a recent result for the discrete-time case. Basically, the performance conditions are built on an augmented-space with additional multipliers resulting in a decoupling between the Lyapunov and system matrices. This nice property is used to develop new conditions for the robust stability, performance analysis, and control synthesis of linear systems using parameter dependent Lyapunov functions in a numerical tractable way.

Robust H∞ Controller Synthesis for Linear

In this paper, we consider the problem of delay-dependent H ∞ control of a class of linear uncertain systems with interval time-varying delay and norm-bounded uncertainties using Lyapunov-Krasovskii approach. By exploiting a candidate Lyapunov-Krasovakii (LK) functional and using slack matrix variables in the delay-dependent stability analysis, a less conservative stability criterion is first derived in terms of linear matrix inequalities (LMIs). Subsequently, based on the criterion obtained, a delay-dependent condition for the existence of a static state feedback controller, which ensures asymptotic stability as well as a prescribed H ∞ performance of the closed loop system for all admissible uncertainties, is deduced. A numerical example is employed to demonstrate the effectiveness of the proposed controller.

Stable H 2-optimal controller synthesis

This paper considers "xed-structure stable H-optimal controller synthesis using a multiobjective optimization technique which provides a trade-o! between closed-loop performance and the degree of controller stability. The problem is presented in a decentralized static output feedback framework developed for "xed-structure dynamic controller synthesis. A quasi-Newton/continuation algorithm is used to compute solutions to the necessary conditions. To demonstrate the approach, two numerical examples are considered. The "rst example is a second-order spring}mass}damper system and the second example is a fourthorder two-mass system, both of which are considered in the stable stabilization literature. The results are then compared with other methods of stable compensator synthesis.

Fixed-order robust controller design with the polynomial toolbox 3.0

2004 IEEE International Conference on Robotics and Automation (IEEE Cat. No.04CH37508), 2004

With the help of numerical examples, we describe new fixed-order robust controller design functions implemented in version 3.0 of the Polynomial Toolbox for Matlab. The functions use convex optimization over linear matrix inequalities (LMIs) solved with the SeDuMi solver.