Argyrios C. Zolotas

Mixed-sensitivity approach to H/sub /spl infin// control of power system oscillations employing multiple FACTS devices

This paper demonstrates the enhancement of inter-area mode damping by multiple flexible AC transmission systems (FACTS) devices. Power system damping control design is formulated as an output disturbance rejection problem. A decentralized H/sub /spl infin// damping control design based on the mixed-sensitivity formulation in the linear matrix inequality (LMI) framework is carried out. A systematic procedure for selecting the weights for shaping the open loop plant for control design is suggested. A 16-machine, five-area study system reinforced with a controllable series capacitor (CSC), a static VAr compensator (SVC), and a controllable phase shifter (CPS) at different locations is considered. The controllers designed for these devices are found to effectively damp out inter-area oscillations. The damping performance of the controllers is examined in the frequency and time domains for various operating scenarios. The controllers are found to be robust in the face of varying power-flow patterns, nature of loads, tie-line strengths, and system nonlinearities, including device saturations.

Optimal design of PID controllers using the QFT method

An optimisation algorithm is proposed for designing PID controllers, which minimises the asymptotic open-loop gain of a system, subject to appropriate robust stability and performance QFT constraints. The algorithm is simple and can be used to automate the loop-shaping step of the QFT design procedure. The effectiveness of the method is illustrated with an example

Model predictive control based on mixed ℋ2/ℋ∞control approach for active vibration control of railway vehicles

This paper investigates the application of model predictive control technology based on mixed ℋ2/ℋ∞ control approach for active suspension control of a railway vehicle, the aim being to improve the ride quality of the railway vehicle. Comparisons are made with more conventional control approaches, and the applicability of the linear matrix inequality approach is illustrated via the railway vehicle example.

Fault detection and isolation filter design for systems subject to polytopic uncertainties

This paper considers the robust fault detection and isolation (FDI) problem for linear time-invariant dynamic systems subject to faults, disturbances and polytopic uncertainties. We employ an observer-based FDI filter to generate a residual signal. We propose a cost function that penalizes a weighted combination of the deviation of the fault to residual dynamics from a given fault isolation reference model, as well as the effects of disturbances and uncertainties on the residual, using the Hinfin norm as a measure. The proposed cost function thus captures the requirements of fault detection and isolation and disturbance rejection in the presence of polytopic uncertainties. We derive necessary and sufficient conditions for the existence of an FDI filter that achieves the design specifications. This condition takes the form of easily implementable linear matrix inequality (LMI) optimization problem.

Passive suspensions for ride quality improvement of two-axle railway vehicles

The aim of this paper is to investigate the possibility of improving the ride quality of a two-axle railway vehicle with a single-stage suspension by means of passive suspensions employing an inerter device. The inerter is a mechanical one-port element that is analogous to a capacitor in electrical circuits. The goal is to improve the ride quality in both the vertical and lateral motions in response to track irregularities. Performance benefits for several simple passive suspension layouts are demonstrated and compared with the conventional scheme. The elastic effects of the damper and inerter device are then taken into consideration for practical purposes. The optimum parameter values of the damper, inerter and the parameters representing the elastic effects provide guidance for mechanical design purposes.

Optimised configuration of sensors for fault tolerant control of an electro-magnetic suspension system

For any given system the number and location of sensors can affect the closed-loop performance as well as the reliability of the system. Hence, one problem in control system design is the selection of the sensors in some optimum sense that considers both the system performance and reliability. Although some methods have been proposed that deal with some of the aforementioned aspects, in this work, a design framework dealing with both control and reliability aspects is presented. The proposed framework is able to identify the best sensor set for which optimum performance is achieved even under single or multiple sensor failures with minimum sensor redundancy. The proposed systematic framework combines linear quadratic Gaussian control, fault tolerant control and multiobjective optimisation. The efficacy of the proposed framework is shown via appropriate simulations on an electro-magnetic suspension system.

Modelling of High Redundancy Actuation Utilising Multiple Moving Coil Actuators

This paper presents the modelling of a moving coil actuator for use as an element in a High Redundancy Actuator (HRA). A single element model is derived from first principles and verified using experimental data. This model is subsequently used to describe an approach to deriving models of multi-element HRAs and determine the effect of a variety of faults, chosen to be appropriate for the electro-magnetic technology, on the behaviour of multi-element assemblies.

Modelling and Control of Railway Vehicle Suspensions

This chapter uses a railway vehicle as an example of a mechanical dynamic system to which control can be applied in a manner that yields significant benefits from an engineering and operational viewpoint. The first part describes the fundamentals of railway vehicles and their dynamics: the normal configuration, the suspension requirements, how they are modelled and an overview of the types of control concept that are currently applied or under consideration. The second part provides a case study of controller design issues.

Robust system state estimation for active suspension control in high-speed tilting trains

The interaction between the railway vehicle body roll and lateral dynamics substantially influences the tilting system performance in high-speed tilting trains, which results in a potential poor ride comfort and high risk of motion sickness. Integrating active lateral secondary suspension into the tilting control system is one of the solutions to provide a remedy to roll–lateral interaction. It improves the design trade-off for the local tilt control (based only upon local vehicle measurements) between straight track ride comfort and curving performance. Advanced system state estimation technology can be applied to further enhance the system performance, i.e. by using the estimated vehicle body lateral acceleration (relative to the track) and true cant deficiency in the configuration of the tilt and lateral active suspension controllers, thus to further attenuate the system dynamics coupling. Robust H∞ filtering is investigated in this paper aiming to offer a robust estimation (i.e. estimation in the presence of uncertainty) for the required variables, In particular, it can minimise the maximum estimation error and thus be more robust to system parametric uncertainty. Simulation results illustrate the effectiveness of the proposed schemes.

MAGLEV suspensions - A sensor optimisation framework

In this paper, a systematic framework for optimised sensor configurations is implemented via Hinfin loop shaping procedure. The optimisation framework, gives the sensor sets that satisfy predefined user criteria and the preset constraints required for the MAGnetic LEVitated suspension performance via evolutionary algorithms. The scheme is assessed via appropriate simulations for its efficacy.