Load frequency control (LFC) is one of the most challenging problems in multi-area power systems. In this paper, we consider power system formed of distinct control areas with identical dynamics which are interconnected via weak tie-lines. We then formulate a disturbance rejection problem of power-load step variations for the interconnected network system. We follow a top-down method to approximate a centralized linear quadratic regulator (LQR) optimal controller by a distributed scheme. Overall network stability is guaranteed via a stability test applied to a convex combination of Hurwitz matrices, the validity of which leads to stable network operation for a class of network topologies. The efficiency of the proposed distributed load frequency controller is illustrated via simulation studies involving a six-area power system and three interconnection schemes. In the study, apart from the nominal parameters, significant parametric variations have been considered in each area. The obtained results suggest that the proposed approach can be extended to the non-identical case.

We consider the problem of simultaneous scheduling and resource allocation of an incoming flow of requests to a set of computing units. By representing each computing unit as a node, we model the overall system as a multiqueue scheme. Inspired by congestion control approaches in communication networks, we propose an AIMD-like (additive increase multiplicative decrease) admission control policy that is stable irrespective of the total number of nodes and AIMD parameters. The admission policy allows us to establish an event-driven discrete model, triggered by a locally identifiable enabling condition. Subsequently, we propose a decentralized resource allocation strategy via a simple nonlinear state feedback controller, guaranteeing global convergence to a bounded set in finite time. Last, we reveal the connection of these properties with Quality of Service specifications, by calculating local queuing time via a simple formula consistent with Little's Law.

This article is concerned with modelling, controllability analysis and the design of aggressive robust controllers for interconnected electric power systems. The load/frequency controller relies on a pole clustering scheme and provides the fastest transient response despite any disturbance load application. The inherent saturation constraints are handled by the combination of a controller gain minimization scheme and an anti-windup enhanced controller design which provides stability guarantees, while avoiding frequency and tie-line power oscillations. For this scheme, particular attention should be paid on the modeling aspects of the power system. It is shown that due to the positive semidefinite graph-connection Laplacian of the system, a reduction of the state vector is necessary. Simulation studies are offered to illustrate the effectiveness of the suggested scheme.

Exothermic chemical reaction taking place in continuous stirred tank reactor is considered. Heat release from the chemical reaction, non-linear dynamic behavior of the process and uncertainty in parameters are the main factors motivating the use of robust control design. Viewing temperature and molar concentration as variables both accessible in real time, PI and optimal state-feedback controllers driven by temperature and concentration error signals are proposed to regulate the system over reactor’s steady-state working points by counteracting undesired disturbances. Since access to concentration value has proved beneficial for the reactor’s performance, estimation techniques are examined to compensate for the problematic nature of the concentration’s measurement. A linear reduced-order observer is first proposed to estimate the concentration value using temperature measurements. In addition, assuming concentration measurement is available with a relatively short delay via sample analysis, a linear and non-linear discrete-time predictor is constructed to estimate the concentration’s real-time value. A linear combination of the two estimation schemes (observer, predictor) is proposed resulting in a combined estimator, in which the emphasis between the two individual schemes can be controlled via a scalar parameter. The work presented in this paper was supported by the GLOW project – New weather-stable low gloss powder coatings based on bifunctional acrylic solid resins and nanoadditives – as part of the development of novel and efficient processing technologies regarding the production of new families of powder coatings, responding to industrial requirements for quality improvement at lower cost and shorter development cycles.

Two well-established complementary distributed linear quadratic regulator (LQR) methods applied to networks of identical plants are extended to the non-identical plant case. The first uses a top-down approach where the centralized optimal LQR controller is approximated by a distributed control scheme whose stability is guaranteed by the stability margins of LQR control. The second consists of a bottom-up approach in which optimal interactions between self-stabilizing agents are defined so as to minimize an upper bound of the global LQR criterion. In this paper, local state-feedback controllers are designed by solving model-matching type problems and mapping all the plants in the network to a target system specified a priori. Existence conditions for such schemes are established for various families of systems. The single-input case and the multi-input case relying on the controllability indices of the plants are first considered followed by an LMI approach combined with LMI regions for pole clustering. Then, the two original top-down and bottom-up methods are adapted and the stability problem for networks of non-identical plants is solved. The applicability of our approach for distributed network control is illustrated via a simple example.