The article deals with the problems of transferring reliable signals of control and control over the communication channels of complex power supply management systems for production facilities. The discrepancy between...
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This book includes papers presented at SOCO 2018, CISIS 2018 and ICEUTE 2018, all held in the beautiful and historic city of San Sebastian (Spain), in June 2018. Soft computing represents a collection or set of comput...
ISBN:
(纸本)9783319941196
This book includes papers presented at SOCO 2018, CISIS 2018 and ICEUTE 2018, all held in the beautiful and historic city of San Sebastian (Spain), in June 2018. Soft computing represents a collection or set of computational techniques in machine learning, computer science and some engineering disciplines, which investigate, simulate, and analyze highly complex issues and phenomena. After a rigorous peer-review process, the 13th SOCO 2018 international Program Committee selected 41 papers, with a special emphasis on optimization, modeling and control using soft computing techniques and soft computing applications in the field of industrial and environmental enterprises. The aim of the 11th CISIS 2018 conference was to offer a meeting opportunity for academic and industry researchers from the vast areas of computational intelligence, information security, and data mining. The need for intelligent, flexible behaviour by large, complexsystems, especially in mission-critical domains, was the catalyst for the overall event. Eight of the papers included in the book were selected by the CISIS 2018 international Program Committee. The international Program Committee of ICEUTE 2018 selected 11 papers for inclusion in these conference proceedings.
This paper provides a novel and practical approach, to check the correctness and completeness of functional specifications (the completeness means complete for one specified function), especially for complex safety cr...
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This paper is about the incremental computation of control sequences for timed discrete events in uncertain environments. The considered uncertainties are the occurrences of uncontrollable events. The domains of appli...
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This paper is about the incremental computation of control sequences for timed discrete events in uncertain environments. The considered uncertainties are the occurrences of uncontrollable events. The domains of application include but are not restricted to flexible manufacturing, communication, computer science, transportation and traffic. Timed Petri nets that include uncontrollable transitions and behave under earliest firing policy are used for modeling purpose. Unexpected firings of the uncontrollable transitions are considered and result in a risk to deviate from the scheduled trajectories. The aim of the controller is to drive the marking of the net from an initial value to a reference one, in minimal time and risk. For this purpose, a cost function is proposed that includes an evaluation of the risk. This function is used with a beam search approach that prunes the expansion of the reachability graph and computes feasible sequences in the most promising subparts of this graph. Robust scheduling is obtained as a consequence. (C) 2018, IFAC (international Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.
With the growing global competition, the importance of innovations for the success of many companies is increasing significantly. An important concept in an innovation process is the innovation communities, which deve...
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With the growing global competition, the importance of innovations for the success of many companies is increasing significantly. An important concept in an innovation process is the innovation communities, which develop and implement innovative ideas. The modeling of such non-physical systems is not a simple task. However, this can be performed with the agent based modeling technique in a more natural way than by differential equations. Unfortunately, the resulting agent-based model is not well-suited for control design. By using input and output data, it is possible to approximate an agent-based model as a Takagi-Sugeno (TS) fuzzy model. In this work, approximation of an agent-based model as a TS fuzzy model is presented. (C) 2018, IFAC (international Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.
Fault tolerance to a switch in SDN (Software Defined Network) requires implementation of redundancy. The article is devoted to research of some economical methods of entering of redundancy into SDN which allow to prov...
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The proceedings contain 30 papers. The special focus in this conference is on . The topics include: Multiclass GI/GI/∞ Queueing systems with Random Resource Requirements;cost and Effect of Replication and Quorum in D...
ISBN:
(纸本)9783319975948
The proceedings contain 30 papers. The special focus in this conference is on . The topics include: Multiclass GI/GI/∞ Queueing systems with Random Resource Requirements;cost and Effect of Replication and Quorum in Desktop Grid Computing;optimal Estimation of the States of Synchronous Generalized Flow of Events of the Second Order Under Its Complete Observability;asymptotic Sojourn Time Analysis of Finite-Source M/M/1 Retrial Queuing System with Two-Way Communication;an Analysis Method of Queueing Networks with a Degradable Structure and Non-zero Repair Times of systems;An Infinite-Server Queueing MMAPk|Gk|∞ Model in Semi-Markov Random Environment Subject to Catastrophes;retrial Queueing Model with Two-Way Communication, Unreliable Server and Resume of Interrupted Call for Cognitive Radio Networks;mittag-Leffler Function in Applied problems of Queuing Theory;a Contribution to modeling Two-Way Communication with Retrial Queueing systems;nonaffine Models of Yield Term Structure;Steady State Probabilistic Characteristics of the On/Off Production Rate control Production-Inventory System with MMPP Demand Arrivals;system State Distribution of a Finite-Source Retrial Queue with Subscribed Customers;modeling of a Multi-link Transport Connection by a Network of Queuing systems;estimation of Prioritized Disciplines Efficiency Based on the Metamodel of Multi-flows Queueing systems;Analysis of an Infinite-Server Queue MAPk|Gk|∞ in Random Environment with k Markov Arrival Streams and Random Volume of Customers;optimization of Two-Level Discount Values Using Queueing Tandem Model with Feedback;Performance Analysis of an M/G/1 Retrial Queueing System Under LCFS-PR Discipline with General Retrial and Setup Times;method of Generating Functions for Performance Characteristic Analysis of the Polling systems with Adaptive Polling and Gated Service.
In this work, we address through model predictive control (MPC) a constrained nonlinear plant described by a continuous-time dynamical model, which naturally leads to a sampled data control system. The numerical solut...
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In this work, we address through model predictive control (MPC) a constrained nonlinear plant described by a continuous-time dynamical model, which naturally leads to a sampled data control system. The numerical solution of the optimal controlproblems involved in MPC must utilize, eventually, some form of discretization. Nevertheless, there are several advantages in maintaining a continuous-time model until later stages. One advantage is that we can devise numerical procedures which, by exploiting additional freedom in selecting the discretization points, are more efficient when continuous-time models are used. Here, we discuss an extension to MPC of an Adaptive Mesh Refinement (AMR) algorithm, which has shown to be efficient in solving nonlinear optimal controlproblems. We derive a sufficient condition that guarantees that an MPC scheme using an adaptive time mesh refinement algorithm preserves stability. (C) 2018, IFAC (international Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.
Motivated by practical applications, the paper highlights MPC formulations suitable for counteracting system drift and the effects of large measured disturbances/set-point changes, and for overcoming limitations of un...
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Motivated by practical applications, the paper highlights MPC formulations suitable for counteracting system drift and the effects of large measured disturbances/set-point changes, and for overcoming limitations of underactuation. For drift counteraction, where the objective is to maximize the time or yield until the system trajectory exits a prescribed set, defined by system safety constraints, operating limits and/or efficiency requirements, MPC, based on mixed integer or conventional linear programming, can lead to effective solutions for higher order systems than possible with dynamic programming and value iterations based methods. Such solutions can have broad applicability including for fuel optimal Geostationary Orbit (GEO) station keeping, spacecraft Low Earth Orbit (LEO) maintenance, underactuated spacecraft attitude control, hybrid electric propulsion energy management, glider flight management, and the development of driving policies for adaptive cruise control and autonomous driving. The paper also highlights the capability of MPC to achieve non-smooth local stabilization of underactuated systems that can be exploited for attitude control of underactuated spacecraft with reaction wheel failures. Related results for systems that cannot be globally stabilized by continuous feedback are also mentioned. Finally, opportunities to handle large load and set-point changes with reference governors are discussed. (C) 2018, IFAC (international Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.
A methodology is proposed to design stabilising fixed-order decentralised controllers for interconnected systems with identical nodal dynamics and identical local controllers. The systems considered are linear time in...
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A methodology is proposed to design stabilising fixed-order decentralised controllers for interconnected systems with identical nodal dynamics and identical local controllers. The systems considered are linear time invariant (LTI) multiple-input multiple-output retarded type time-delay systems. The closed-loop systems of local controllers and subsystems (nodes) are modelled by a system of delay differential algebraic equations. The proposed approach combines the non-conservative direct optimisation approach towards stabilisation of delay systems with a decoupling transformation. The latter reduces the overall design problem to a robust/simultaneous controller design problem for one parameterised subsystem, where the allowable values of the parameter correspond to eigenvalues of the adjacency matrix of the network graph. By treating the eigenvalues as perturbations, contained in specific intervals or regions in the complex plane determined by the topology of the network, and by optimising the corresponding pseudospectral abscissa using a novel structure exploiting algorithm, we can ensure that the achieved stability property, and the computational complexity of the controller design, are independent of the number of subsystems. A numerical example is presented to validate the proposed approach in MATLAB software. (C) 2018, IFAC (international Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.
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