Controller reduction for linear systems

This dissertation proposes some H-infinity and H2 performance preserving controller reduction methods for linear systems. The proposed methods can guarantee robust stability and performance for the closed-loop system with the reduced order controllers. Several H-infinity stability and performance preserving controller reduction methods are proposed in this dissertation. It is shown that the weighting functions used in the proposed controller reduction methods can be directly obtained from the parametrization of the H-infinity controllers. Hence, comparing with the most existing controller reduction approaches, the proposed controller reduction methods require less computation and are easy to apply. At the same time, several algorithms are proposed to simplify some existing controller reduction algorithms. Examples are explored to demonstrate the advantages of the proposed controller reduction methods. The parallel problems are also discussed for H2 performance preserving controller reductions. Furthermore, some parallel controller reduction methods are presented to reduce controllers for preserving the closed-loop system stability and performance. Similarly, relevant simplified algorithms are also proposed for those existing H2 performance preserving controller reduction algorithms. One example is explored to demonstrate those controller reduction methods. Another H-infinity controller reduction method is introduced for SISO system to maintain the closed-loop system stability and performance. This approach provides upper bound on the controller weighting function for general SISO H-infinity control problem, and then a lower order controller is provided using frequency weighted model reduction method, which preserves stability and performance for the closed-loop system. Finally, some possible future work are outlined

Coprime Factor Reduction of H-infinity Controllers

We consider the efficient solution of the coprime factorization based H infinity controller approximation problems by using frequency-weighted balancing related model reduction approaches. It is shown that for a class of frequency-weighted performance preserving coprime factor reduction as well as for a relative error coprime factor reduction method, the computation of the frequency-weighted controllability and observability grammians can be done by solving Lyapunov equations of the order of the controller. The new approach can be used in conjunction with accuracy enhancing square-root and balancing-free techniques developed for the balancing related coprime factors based model reduction

Computationalcost Reduction of Robust Controllers Foractive Magnetic Bearing Systems

This work developed strategies for reducing the computational complexity of implementing robust controllers for active magnetic bearing (AMB) systems and investigated the use of a novel add-on controller for gyroscopic effect compensation to improve achievable performance with robust controllers. AMB systems are multi-input multi-output (MIMO) systems with many interacting mechanisms that needs to fulfill conflicting performance criteria. That is why robust control techniques are a perfect application for AMB systems as they provide systematic methods to address both robustness and performance objectives. However, robust control techniques generally result in high order controllers that require high-end control hardware for implementation. Such controllers are not desirable by industrial AMB vendors since their hardware is based on embedded systems with limited bandwidths. That is why the computational cost is a major obstacle towards industry adaptation of robust controllers. Two novel strategies are developed to reduce the computational complexity of singlerate robust controllers while preserving robust performance. The first strategy identifies a dual-rate configuration of the controller for implementation. The selection of the dualrate configuration uses the worst-case plant analysis and a novel approach that identifies the largest tolerable perturbations to the controller. The second strategy aims to redesign iv the controller by identifying and removing negligible channels in the context of robust performance via the largest tolerable perturbations to the controller. The developed methods are demonstrated both in simulation and experiment using three different AMB systems, where significant computational savings are achieved without degrading the performance. To improve the achievable performance with robust controllers, a novel add-on controller is developed to compensate the gyroscopic effects in flexible rotor-AMB systems via modal feedback control. The compensation allows for relaxing the robustness requirements in the control problem formulation, potentially enabling better performance. The effectiveness of the developed add-on controller is demonstrated experimentally on two AMB systems with different rotor configurations. The effects of the presence of the add-on controller on the performance controller design is investigated for one of the AMB systems. Slight performance improvements are observed at the cost of increased power consumption and increased computational complexity

Mixed H2/H∞ control for infinite dimensional systems

The class of infinite dimensional systems often occurs when dealing with distributed parameter models consisting of partial differential equations. Although forming a comprehensive description, they mainly become manageable by finite dimensional approximations which likely neglect important effects, but underlies a certain structure. In contrast to common techniques for controlling infinite dimensional systems, this work focuses on using robust control methods. Thus, the uncertainty structure that occurs due to the discretization shall be taken into account particularly. Additionally, optimal performance measures can be included into the design process. The mixed H2/H∞ control approach handles the inclusion of disturbances and inaccuracies while guaranteeing specified energy or magnitude bounds. In order to include various of these system requirements, multi-objective robust control techniques based on the linear matrix inequality framework are utilized. This offers great flexibility concerning the formulation of the control task and results in convex optimization problems which can be solved numerically efficient by semi-definite programming. A flexible robot arm structure serves as the major application example during this work. The model discretization leads to an LTI system of specified order with an uncertainty model which is obtained by considering the concrete approximation impact and frequency domain tests. A structural analysis of the system model relates the neglected dynamics to a robust characterization. For the objective selection, stability shall be ensured under all expected circumstances while the aspects of optimal H2 performance, passive behavior and optimal measurement output selection are included. The undesirable spillover effect is thoroughly investigated and thus avoided.Tesi

Maximum current injection method for grid-forming inverters in an islanded microgrid subject to short circuits

In islanded microgrids, when a short circuit or a sudden overload occurs, it provokes an abrupt increment in the currents supplied by the generation nodes, which feed the load collaboratively. This is particularly challenging for inverter-based nodes, due to its reduced power capacity. This work takes advantage of the droop-method basic configuration to propose an additional closed-loop control, which ensures maximum current injection during any kind of short circuit maintaining the underlying droop control. Ensuring that any node injects its maximum rated current during the short circuit, it emulates the most common low-voltage ride-through protocols for grid-feeding sources oriented to support the grid and, in this way, the voltage unbalance is reduced. To develop the control proposal, a model of the faulted system is presented in order to evaluate the stability of the closed-loop system. A general modelling methodology is introduced in order to derive the control for any microgrid configuration. Finally, selected experimental results are reported in order to validate the effectiveness of the proposed control.Peer ReviewedPostprint (author's final draft

An admittance shaping controller for exoskeleton assistance of the lower extremities

We present a method for lower-limb exoskeleton control that defines assistance as a desired dynamic response for the human leg. Wearing the exoskeleton can be seen as replacing the leg's natural admittance with the equivalent admittance of the coupled system. The control goal is to make the leg obey an admittance model defined by target values of natural frequency, peak magnitude and zero-frequency response. No estimation of muscle torques or motion intent is necessary. Instead, the controller scales up the coupled system's sensitivity transfer function by means of a compensator employing positive feedback. This approach increases the leg's mobility and makes the exoskeleton an active device capable of performing net positive work on the limb. Although positive feedback is usually considered destabilizing, here performance and robust stability are successfully achieved through a constrained optimization that maximizes the system's gain margins while ensuring the desired location of its dominant poles

Adaptive Optimal Control The Thinking Man's GPC

Exploring connections between adaptive control theory and practice, this book treats the techniques of linear quadratic optimal control and estimation (Kalman filtering), recursive identification, linear systems theory and robust arguments