Edward Boje

Stabilizing SSR oscillations with a shunt reactor controller for uncertain levels of series compensation

The authors demonstrate how frequency-domain techniques based on I. Horowitz et al.s (1986) quantitative feedback theory can be applied to the design of fixed-parameter controllers in power systems where the plant parameters have large uncertainties. They present the design of a controller for a shunt reactor to eliminate torsional shaft oscillations in a turbogenerator susceptible to subsynchronous resonance (SSR). The considered parameter uncertainty is the series capacitor compensation level, which has been assumed to vary between 12% and 76%. Simulated transients results of the uncontrolled/controlled system are depicted. >

Brief Multivariable quantitative feedback design for tracking error specifications

The use of tracking error specifications in quantitative feedback theory (QFT) design is discussed for multi-input, multi-output (MIMO) systems. These specifications bound the closed loop transfer function within a disk around some nominal (model) performance while preserving the QFT approach that allows treatment of highly structured (and unstructured) uncertainty. Because the specifications capture phase information, the level of over-design in certain MIMO QFT designs is reduced. The method presented allows independent, two-degree-of-freedom design.

Quantitative multivariable feedback design for a turbofan engine with forward path decoupling

A detailed quantitative feedback design example of robust control of a multivariable turbofan engine is presented. The Perron root of the so-called interaction matrix is used as a measure of the level of triangularization of uncertain multivariable plants. This leads to a design approach where a decoupling pre-compensator is used to reduce the level of interaction between loops before quantitative design of a diagonal feedback controller matrix is attempted. If the interaction index can be made less than unity by the design, stability of the diagonal loop designs guarantees stability of the closed-loop multivariable system. The decoupling pre-compensator is designed to be in the forward path, between the diagonal controller and the plant. For the design example presented, a simple, static pre-compensator reduces interaction in the critical gain crossover frequency range. Careful design of the diagonal controller and pre-filter result in an improved, lower-order design than has been obtained previously using the quantitative Nyquist array approach. Copyright

Water circulation control during once-through boiler start-up

Abstract A loop-by-loop approach is used to analyse multivariable water flow and collecting vessel-level control problems during Benson® type boiler start-up. It is shown that the circulation loop must be tuned so that its bandwidth is less than the feed water loop bandwidth.

Finding nonconvex hulls of QFT templates

To reduce the computational overhead in quantitative feedback theory (QFT) bound computation, only the (nonconvex) outside edge of a template should be used. This note presents an algorithm to calculate the nonconvex hull with minimum concave radius defined by the feedback system specifications.

Feedback controller design for plants with modes and disturbances above the sampling frequency

The digital feedback controller design technique of Eitelberg (1988) could not treal closed-loop performance accurately if the continuous-time plan. had significant models and signals above the sampling frequency. Here, the above simple techinques applicability is extended by implementing the controller with additional analogue low-pass filters, cancelled by digital ‘high-pass’ terms at or below the sampling frequency.

Further results on Eitelberg's sampling rate design based on (1 — sT/2)

The approximation (l—sT/2) for the effect of sampling proposed by Eitelberg (1988) is shown to be accurate to order T2 , where 1/T is the sampling rate.

Linear Model Identification for Multivariable Continuous Time Systems

Abstract A parameter identification algorithm for multivariable, continuous-time systems is presented. It is capable of treating systems with (non-zero) initial conditions and measurement offset or bias. The system model structure used is a minimal order input-output representation. Differentiation of measured data is avoided by means of either multiple lowpass filtering or multiple finite time integration. Equations in unknown parameters are set up and then solved by linear least-squares. The singular value decomposition is used to solve the least-squares problem because of its numerical robustness and because of the extra data it provides for analysis. Examples of up to 14th order are discussed.

Implicit Quasi-Steady-State Approximation and Application to a Power Plant Evaporator

Construction of reduced order models using the conventional quasi-steady-state (QSS) or singular perturbation approach may not yield good low frequency, approximations, especially if there is not a distinct time scale separation into slow and fast subsystems. An implicit QSS technique is proposed for general nonlinear models. The resulting reduced order model is accurate to first order in the perturbation parameter and its linearization is accurate to first order in frequency. An example is included showing the application of the proposed method to model reduction on a power plant evaporator.

Augmented Kalman filtering for a superheated steam header system

This paper examines the distributed parameter model of a main steam header system and simplifies it to retain only the significant dynamics of the pipe wall temperature and quasisteady-state behavior of the steam in the headers. An augmented linear optimal filter is developed for estimating the steam and pipe wall temperatures along the interconnected main steam headers, between the superheater outlet and the turbine. The filter algorithm is illustrated using data from a power plant.