Two-level Hierarchical Structure Research Articles

Co-ordinated hierarchical control strategy for multi-infeed HVDC systems

A co-ordinated hierarchical control strategy for multi-infeed HVDC systems is presented. The control law of the HVDC system's transfer power can be derived using optimal control theory with the HVDC system being treated as a variable admittance connected at the commutation busbars. A two-level hierarchical control structure is assumed for the rectifier and inverter side AC system, respectively. The control of constituent HVDC subsystems can be better co-ordinated by the consideration of the AC commutation voltage included in the optimised performance index, and the performance of both rectifier and inverter side AC systems is considered.

Structural modelling of Eu3+-based siloxane–poly(oxyethylene) nanohybrids

The modelling of the local structure of sol–gel derived Eu3+-based organic/inorganic hybrids is reported, based on Small-Angle X-ray Scattering (SAXS), photoluminescence and mid-infrared spectroscopy. The hybrid matrix of these organically modified silicates, classed as di-ureasils and termed U(2000) and U(600), is formed by poly(oxyethylene) (POE) chains of variable length grafted to siloxane domains by means of urea cross-linkages. Europium triflate, Eu(CF3SO3)3, was incorporated in the two di-ureasil matrices with compositions 400 ≥ n ≥ 10, n is the molar ratio of ether oxygens per Eu3+. The SAXS data for undoped hybrids (n = ∞) show the presence of a well-defined peak attributed to the existence of a liquid-like spatial correlation of siloxane rich domains embedded in the polymer matrix and located at the ends of the organic segments. The obtained siloxane particle gyration radius Rg1 is around 5 Å (error within 10%), whereas the interparticle distance d is 25 ± 2 Å and 40 ± 2 Å, for U(600) and U(2000), respectively. For the Eu3+-based nanocomposites the formation of a two-level hierarchical local structure is discerned. The primary level is constituted by strongly spatially correlated siloxane particles of gyration radius Rg1 (4–6 and 3–8 Å, errors within 5%, for U(600)nEu(CF3SO3)3, 200 ≥ n ≥ 40, and U(2000)nEu(CF3SO3)3, 400 ≥ n ≥ 40, respectively) forming large clusters of gyration radius Rg2 (≈75 ± 10 Å). The local coordination of Eu3+ in both di-ureasil series is described combining the SAXS, photoluminescence and mid-infrared results. In the di-ureasils containing long polymer chains, U(2000)nEu(CF3SO3)3, the cations interact exclusively with the carbonyl oxygens atoms of the urea bridges at the siloxane–POE interface. In the hybrids containing shorter chains, U(600)nEu(CF3SO3)3 with n ranging from 200 to 60, the Eu3+ ions interact solely with the ether-type oxygens of the polymer chains. Nevertheless, in this latter family of hybrids a distinct Eu3+ local site environment involving the urea cross-linkages is detected when the europium content is increased up to n = 40.

Two-Layer Control of Integrated Quality and Quantity in Dynamic Water Distribution Systems

An integrated approach to control of quantity and quality in water supply and distribution systems is proposed. The integrated control consists in optimising the operational cost, meeting a demand on water of desired quality and maintaining the constraints. This constrained optimising control problem is complex due to nonlinearities, large dimension, output constraints, mixed-integer structure of the variables involved, at least two time scales in the system dynamics and an uncertainty. A sub-optimal two-level hierarchical control structure is proposed that allows incorporating the desired controller functions and yet making the synthesis of these functions possible. The control trajectories optimising the operational cost over one day to one week horizon are generated by the upper layer. The upper layer controller operates according to a repetitive control strategy. Due to model-reality differences the prescribed bounds on chlorine residuals may not be met when the generated controls are applied to a real systems. The main objective of the lower control layer is to adjust on-line actions of the booster stations determined by the upper control layer so that the chlorine residuals are kept within the limits. The lower layer controller operates almost continuously as opposed to the upper layer one. Its design is very difficult as the dynamics between the chlorine injection nodes and monitored nodes involves time-varying delays and parameters that can abruptly change. A decentralisation of the lower layer controller into a number of independent local controllers allocated to selected sub-areas of a distribution system by using the interaction trajectories determined by the upper layer is discussed. The design of the lower layer controller and its performance are illustrated on an example water system.

Magnetic order and categorization in attractor neural networks

The thermodynamic behavior of an extended Hopfield model for an attractor neural network with units in three Ising-states S i and symmetrically random diluted synaptic connections J ij d, between units i and j, is discussed here in the thermodynamic limit within replica-symmetric mean-field theory. A macroscopic set of random patterns in a two-level hierarchical structure of ancestors and descendents is used to construct the synaptic connections and to determine the magnetic order associated with the recognition of ancestors.

Scheduling of Refinery Processes with Optimal Control Approach.

A new scheduling algorithm based on an optimal control theory is presented for large-scale industrial problems. The main feature of this idea lies in a two-level hierarchical structure consisting of a reference model and a rigorous model, respectively. As a fair compromise between the excess of decision detail and long-range planning inspiration, we address simplified or relaxed models to derive optimal trajectories. The optimal trajectory is then used as a reference trajectory to be tracked in real time by a feedback control system to cope with uncertainty and modeling errors. We apply this idea to operation scheduling of refinery processes that convert crude oil mix into a variety of marketable products through a number of refining processes. The optimal control formulation is shown to enhance solution performance compared with the traditional mixed-integer model.

Modelling supervisory control systems using fuzzy cognitive maps

Modelling complex systems and their supervisior has attracted the high interest of many scientists and engineers. There has been a need for highly sophisticated Autonomous Intelligent Systems. A very promising methodology to model the Supervisor of a plant is the use of Fuzzy Cognitive Maps (FCM). FCM are a combination of Fuzzy Logic and Neural Networks. A new mathematical model for FCMs is proposed and its representation is examined in this paper. FCM construction is presented through the development of the model for a simple control process problem. Then, issues for the application of FCM as the model of the supervisor of a complex system are addressed and a hierarchical two-level structure is proposed.

A Soft Computing Approach for Modelling the Supervisor of Manufacturing Systems

The development of a novel soft computing approach to model the supervisor of manufacturing systems is described, it is named Fuzzy Cognitive Maps (FCMs) and it is used to model the behaviour of complex systems. Fuzzy cognitive maps combine characteristics of both fuzzy logic and neural networks. The description and the construction of fuzzy cognitive maps are examined, a new methodology for developing fuzzy cognitive maps is proposed here and as an example the fuzzy cognitive map for a simple plant is developed. A hierarchical two-level structure for supervision of manufacturing systems is presented, where the supervisor is modelled as a fuzzy cognitive map. The fuzzy cognitive map model for the failure diagnosis part of the supervisor for a simple chemical process is constructed.

Unit commitment with voltage constraints

This paper proposes an efficient algorithm for considering reactive power and voltage constraints in unit commitment. Because the problem is formulated as a large mixed-integer programming and has a two-level hierarchical structure, the Benders decomposition method is used. Using decomposition, the master problem solves unit commitment, and the subproblem examines reactive power and voltage constraints in each hour to test the feasibility of the unit commitment solution. In the case of infeasibility, a proper constraint (Benders cut) is introduced and placed in the master problem for unit commitment rescheduling. The iterative process between the master and subproblems provides a minimum cost solution for generation scheduling while satisfying reactive power and voltage constraints. The constrained economic dispatch is used in our unit commitment. The constraints in the subproblem are formulated as linear programming with a block-angular structure. So, the Dantzig–Wolfe decomposition is applied in the subproblem to solve large-scale power system problems. A modified IEEE-30 bus system is presented to demonstrate the efficiency of the method. © 1997 by John Wiley and sons, Ltd.

Computer Control of Propofol Infusion using Quantitative and Qualitative Approaches

A two-level hierarchical structure using quantitative and qualitative approaches for controlling propofol infusion rate is proposed in this paper. The first level merges online measurements (i.e. systolic arterial pressure and heart rate) to interpret the primary depth of anaesthesia. The second level uses an average three-comparanent pharmacokinetic model to predict the propofol concentration in the blood of the patient Then, using fuzzy set theory to combine these two levels, a lookup table to administer the propafol infusion rate is obtained. This lookup table has given confidence of anaesthetists to perform automatic. control of propofol in clinical trials at the next stage.

Decomposition approach to unit commitment with reactive constraints

The authors propose an efficient algorithm for considering reactive power and voltage constraints in unit commitment. The inclusion of these reactive constraints in unit commitment will ensure enough commitment of real power and a feasible distribution of reactive power in power systems. Because the problem is a large mixed-integer programming and has a two-level hierarchical structure, the Benders decomposition method is used. Using decomposition, the master problem solves unit commitment and the subproblem examines reactive power and voltage constraints every hour to test the feasibility of the unit commitment solution. In the case of infeasibility, a proper constraint (Benders cut) is introduced and placed in the master problem for rescheduling the units. The iterative process provides a minimum cost solution for generation scheduling while satisfying reactive constraints. Test examples on the modified IEEE 30 bus system are presented to demonstrate the efficiency of the method.

The Global Hierarchical Optimization of the Large-Scale Systems with Linear Constraint

A global concave minimization problem of large-scale systems is considered by using the overlapping coordination method (Macko, et al., 1978) to decompose it into subsystems, the mathematical formulation of a two-level hierarchical structures is presented. The overlapping coordination method presented here may be flexible for solving a large class of hierarchical optimization problems of large-scale systems. For each subsystem, the concavity of objective function preserves some distinctions which may be exploited for designing the numerical methods of the global minimization. The method is very simple and the related procedure always gives an improved value of the overall objective.

Electronic Data Interchange: Competitive Externalities and Strategic Implementation Policies

Electronic Data Interchange (EDI) is an emerging type of standardized inter-organizational information system. We analyze the impact of EDI on the upstream suppliers’ competitive position in a simple two-level hierarchical market structure where the buyer faces a linear demand curve and the competing heterogeneous suppliers have an upward-sloping marginal cost function. We show that a suppliers’ adoption of EDI can generate positive externalities for the buyer and negative (or competitive) externalities for other suppliers. As a result, the buyer provides a price premium to those suppliers who adopt EDI and increases their sales volume and market share. Moreover, when the benefits that the buyer can derive from implementing EDI are substantial, and the suppliers’ EDI adoption costs are high, it may be in the buyer’s best interest to subsidize the suppliers so as to encourage them to adopt EDI, instead of mandating them to do so. Regardless of whether the buyer employs a mandatory or a subsidizing policy, the buyer and the end consumers may be the only ones who gain from this new technology. Consequently, a partial adoption by the supplier base may be optimal for the buyer when the suppliers’ adoption costs are sufficiently high. We also show that, while EDI reduces the transaction costs of the buyer, the upstream market tends to become more concentrated as a result of increased cost differentials. These results provide one economic explanation of the fact that many companies have actually reduced their supplier base after implementing EDI, despite a significant reduction in their market transaction costs.

A multimedia storage system for on-demand playback

This paper presents the design of a multimedia storage system for on-demand playback. The design stresses effective utilization of disk bandwidth with minimal data buffer to minimize overall system costs. The design procedure is most distinctive in the following two aspects: it bases on a tight upper bound of the lumped disk seek time for the Scan disk scheduling algorithm to achieve effective utilization of the disk bandwidth; and it starts with a general two-level hierarchical disk array structure to derive the optimal configuration for specific requirements. >

Optimal design of a distributed network with a two-level hierarchical structure

This paper deals with the topological design of a network with a two-level hierarchical structure where the embedded backbone network is full-meshed and the local networks attached to it are of star type. The whole problem, unlike the conventional approaches partitioning it into two subproblems, is directly handled in such a general setting that both a backbone network and local access networks are to be simultaneously determined. We formulate this problem as a quadratic 0–1 programming model, and also propose an equivalent linearized version of the model. Based on the observation that the linearized model is a variant of the well established uncapacitated facility location problem, a dual-based solution procedure is developed and shown to be efficient from computing experiments which were done on a wide variety of problems with up to 50 backbone nodes and 50 user nodes.

A standard model of the placement problem aimed at resolving a cutting stock problem

To deal with a class of problems in which dimensions of objects to be cut are unknown beforehand, a cutting optimization technique is proposed. This solution has been applied to the wood industry. It is based on a two-level hierarchical structure consisting of a placement algorithm assigned to a given plank to optimize the cutting and a process control procedure permitting production of a requested list of pieces that is the best on a limited horizon. The placement algorithm is modeled in order to formalize the control strategy. In particular, a method for connecting a system of discrete events to the more classical theory of continuous samples systems is proposed, and under the given hypothesis, an optimal control policy is established.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Reactor Diagnostics Rule Generation Through Statistical Pattern Recognition

This paper reports on a pattern recognition algorithm developed for systematic generation of shallow knowledge for nuclear power plant transient diagnostics. The algorithm involves feature selection and pattern discovery. The selection of N best features is attained by discarding redundant and nondiscriminatory features. An entropy minimax algorithm is used to discover the patterns by searching an N-dimensional feature space, populated with transient events of the data base, to locate subspaces that discriminate among the event classes. These patterns are then represented as production rules for diagnostics. A series of approximations have been implemented in the algorithm to handle the discovery of patterns in multidimensional space. The authors have also developed a perturbation algorithm within the entropy minimax framework to update the patterns in an incremental fashion as new data are obtained. The Midland Nuclear Power Plant Unit 2 simulator is used to generate 144 single-failure events. Based on these events, 25 production rules are generated, representing a two-level hierarchical knowledge structure of single-failure events along the critical safety function approach. These rules represent the common characteristics of time-varying features over the diagnostic time, thereby providing diagnostic capability at any time during the transient.

Transient stability control: a multi-level hierarchical approach

A two-level hierarchical control structure for obtaining an optimal control strategy during the transient ensuing major disturbances in multimachine power systems is presented. This structure involves localized subsystem controllers communicating with a transient coordinating controller. The local controllers, making computations in parallel, control each subsystem according to the interconnection variables provided by the transient controller. These interconnection variables are updated to satisfy interaction feasibility by means of an iterative procedure. The control strategy maintains system stability, even when the severity of the disturbances is increased, due to the feedback or closed-loop control formulation inherent in the strategy. A nonlinear multimachine example is included to illustrate the technique.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Augmented model-based double iterative loop techniques for hierarchical control of complex industrial processes

Two novel hierarchical structures are presented which extend the applicability of previous model-based double iterative loop techniques using input-output information feedback to non-convex problems. The techniques incorporate integrated system optimization and parameter estimation, which utilize process measurements to achieve real process optimality in spite of model reality differences. The double iterative loop structures of the proposed algorithms use the real process measurements within the output loops while the inner loops involve model-based computations only. By this means the algorithms use available information from the real process efficiently and a significant reduction in set-point alterations to real sub-processes is achieved. In order to cater for process complexity, the inner loops are organized in the form of two-level hierarchical structures. An applicability of the techniques to non-convex problems is achieved by a suitable convexification of an original process performance index. It ...

Decentralized, stochastic control for a static LQ problem

An original problem statement for the optimal control laws design is presented. A large scale system composed of M linear static subsystems with an interaction and quadratic performance index is considered. A two-level hierarchical control structure is assumed, in which a coordinator and local controllers have access to different information. The so-called elastic constraint (Gessing 1985) is used for coordination. For the problem the possibility of partial decomposition of calculations and a decentralization of the control, as well as an analytical form of the optimal laws are obtained. The influence of the particular subsystem on the control quality is investigated.

Decentralised and hierarchical control of interconnected uncertain systems

The paper develops new decentralised and hierarchical control techniques for linear interconnected, uncertain dynamical systems with additive-type bounded uncertainties. The overall system is decomposed into N lower order subsystems, each containing uncertain elements and is corrupted by uncertain bounded disturbances. The uncertainties of the systems&apos; parameters are known to belong to prescribed compact bounding intervals. It has been shown that, if uncertainty of the system is within a certain structure (i.e. the matching conditions hold), stabilising control always exists, no matter how large the uncertainty is. Based on this and on the theory of ultimate boundedness, the proposed decentralised and hierarchical control structures guarantee global uniform ultimate boundedness behaviour for the decomposed subsystems. Sufficient conditions are given for the stability of the global system, when driven with proposed control schemes and in the presence of interconnections with bounded uncertainties. It has been established that, with the satisfaction of these conditions and/or validity of the uncertainty matching structure, the developed decentralised and hierarchical control strategies provide robust design schemes, i.e. they are insensitive to the structural perturbations, either between the subsystems and/or in the communication network between the two-level hierarchical structure. Furthermore, the design algorithms are insensitive to parameter perturbations in their bounded ranges.