Span of control

Modellen, meten, regelen, terugkoppeling en optimaliseren zijn algemeen gebruikte begrippen. Zij hebben in het vakgebied ‘regelen’ een precieze wiskundige betekenis gekregen. Daardoor zijn krachtige en relevante inzichten ontstaan en hulpmiddelen beschikbaar gekomen om veel technische processen te optimaliseren. In zijn rede wordt gereflecteerd op de rol van modellen en regelen in de techniek en in de industrie. Een belangrijke overweging hierbij vormt de ‘Span of Control’. Er is een bovengrens aan wat een model redelijkerwijs kan uitdrukken of wat een regeling of een bestuur kan bereiken. Dankzij het generieke karakter van deze begrippen zullen ze worden geïllustreerd met technische en niet-technische voorbeelden, zoals de organisatie van een universiteit

Identification and parameter-varying decoupling of a 3-DOF platform with manipulator

The paper describes identification and a new parameter-varying decoupling method for a 3-degree-of-freedom (DOF) platform with a manipulator on top of it, which is magnetically levitated by 9 voice-coil actuators. The identification has been performed in closed-loop using two different indirect approaches. In the first approach time-domain data of the system were processed using Ho-Kalman algorithm. The second approach was based on frequency-response measurements. The 3 DOFs of the platform are coupled and the coupling is even varying as the manipulator on top is moving. In order to design separate SISO controllers for each DOF of the platform, a new decoupling method has been developed which uses frequency response measurements of the system obtained for different positions of the manipulator

Price-based control of electrical power systems

In this chapter we present the price-based control as a suitable approach to solve some of the challenging problems facing future, market-based power sys tems. On the example of economically optimal power balance and transmission network congestion control, we present how global objectives and constraints can in real-time be translated into time-varying prices which adequately reflect the cur rent state of the physical system. Furthermore, we show how the price signals can be efficiently used for control purposes. Becoming the crucial control signals, the timevarying prices are employed to optimally shape, coordinate and synchronize local, profit-driven behaviors of producers/consumers to mutually reinforce and guarantee global objectives and constraints. The main focus in the chapter is on exploiting specific structural properties of the global system constraints in the synthesis of price-based controllers. The global constraints arise from sparse and highly struc tured power flow equations. Preserving this structure in the controller synthesis implies that the devised solutions can be implemented in a distributed fashion

General framework for real-time implementation of balancing services market outcome

Load frequency control (LFC) is widely used for real-time balancing connected power systems. With the deregulation of power system markets, there is a necessity for adapting the current LFC to support market-based operation. In this paper we propose a general balancing tool which covers both, regulated, and deregulated load frequency control. The proposed approach enables implementation of conventional, two-sided markets possible as well as implementation of the integrated markets for balancing reserves, i.e. cooperation in provision of reserves among different control area

Stabilization and vibration isolation of a contactless electromagnetic isolator : a frequency-shaped sliding surface approach

A Frequency-Shaped Sliding Surface Control (FSSSC) approach is applied to an unstable model of a candidate Electro-Magnetic Isolator (EMI) design which has three Degrees Of Freedom (DOF). The EMI is designed to achieve contactless passive gravity compensation for heavy load by permanent magnets. The 3-DOF model can be regarded as three exactly the same double-integrators disturbed by the nonlinear and coupled passive force which results in its inherent instability. The sliding surface is designed based on relative displacement and payload acceleration feedback to achieve low-frequency vibration isolation. To avoid the algebraic control loop, a linear converging controller is designed instead of the conventional switching control. Regardless of the plant uncertainties, the closed-loop transmissibility converges to the designed transmissibility with increasing open-loop gain. A sufficient condition for the closed-loop stability is developed. Both time domain and frequency domain performance of the designed controller is evaluated by simulation. It shows that robust vibration isolation performance is achieved despite of the nonlinear and coupled passive force

Optimal decentralized Kalman filter

The Kalman filter is a powerful state estimation algorithm which incorporates noise models, process model and measurements to obtain an accurate estimate of the states of a process. Implementation of conventional Kalman filter algorithm requires a central processor that harvests measurements from all the sensors in the field. Central algorithms have some drawbacks such as reliability, robustness and high computation which result in a need for non-central algorithms. This study takes optimality in decentralized Kalman filter (DKF) as its focus and derives the optimal decentralized Kalman filter (ODKF) algorithm, in case the network topology is provided to every node in the network, by introducing global Kalman equations. ODKF sets a lower bound of estimation error in least squares sense for DKF

State fusion with unknown correlation : ellipsoidal intersection

Some crucial challenges of estimation over sensor networks are reaching consensus on the estimates of different systems in the network and separating the mutual information of two estimates from their exclusive information. Current fusion methods of two estimates tend to bypass the mutual information and directly optimize the fused estimate. Moreover, both the mean and covariance of the fused estimate are fully determined by optimizing the covariance only. In contrast to that, this paper proposes a novel fusion method in which the mutual information results in an additional estimate, which defines a mutual mean and covariance. Both variables are derived from the two initial estimates. The mutual covariance is used to optimize the fused covariance, while the mutual mean optimizes the fused mean. An example of decentralized state estimation, where the proposed fusion method is applied, shows a reduction in estimation error compared to the existing alternatives

Distributed, price-based control approach to market-based operation of future power systems

In this paper we present, discuss and illustrate on examples the price-based control paradigm as a suitable approach to solve some of the challenging problems facing future, market-based power systems. It is illustrated how global objectives and constraints are optimally translated into time-varying prices. The real-time varying price signals are guaranteed to adequately reflect the state of the physical system and present the signals that optimally shape, coordinate and synchronize local, profit driven behaviors of producers/consumers to mutually reinforce and guarantee global objectives and constraints. As an illustrative example, the real-time price-based power balance control with congestion management is presented

Optimal spatial allocation of ancillary services for power systems

Abstract onl