An attempt to connect finite automata theory with multi-agent systems is presented. The purpose is to obtain an accurate way to plan and control the robot activities within a multi-robot system. The proposed model is ...
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An attempt to connect finite automata theory with multi-agent systems is presented. The purpose is to obtain an accurate way to plan and control the robot activities within a multi-robot system. The proposed model is an adapted Moore machine, which is to be used with a contract net protocol agent coordination procedure. The considered architecture was tested in an educational flexible manufacturing system with two industrial robots.
Reliable decentralized stabilization is considered for general multi-channel plants, where the objective is to maintain stability of the closed-loop system when all of decentralized controllers work together and when ...
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Reliable decentralized stabilization is considered for general multi-channel plants, where the objective is to maintain stability of the closed-loop system when all of decentralized controllers work together and when one of the controllers is extracted due to a failure. A dilated LMI technique is employed for deriving reliable state feedback design, while a version of unknown disturbance observer is used as a decentralized observer for extending the design to output feedback case. Advantages and usefulness of the proposed method are demonstrated through an application to a power system.
In this paper, the state estimation problem with constrained error variance for linear discrete-time systems is investigated. To this end, in a first stage, the vector variance equation describing the evolution of the...
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In this paper, the state estimation problem with constrained error variance for linear discrete-time systems is investigated. To this end, in a first stage, the vector variance equation describing the evolution of the state error variance is established. Then, by applying results from the theory of positively invariant polyhedral sets of discrete-time systems, necessary and sufficient conditions for the state error variance to respect linear constraints are developed. Thus, the determination of the state estimator parameters is reduced to a nonlinear programming problem which can be solved by using various optimization algorithms.
This paper presents an approach to trajectory generation for Unmanned Aerial Vehicles (UAV) by using Mixed Integer Linear Programming (MILP) and a modification of the A{sup}* algorithm to optimize paths in dynamic env...
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This paper presents an approach to trajectory generation for Unmanned Aerial Vehicles (UAV) by using Mixed Integer Linear Programming (MILP) and a modification of the A{sup}* algorithm to optimize paths in dynamic environments, particularly having pop-ups with a known future probability of appearance. Each pop-up leads to one or several possible evasion maneuvers, characterized with a set of values used as decision making parameters in an Integer Linear Programming (ILP) model that optimizes the final route by choosing the most suitable alternative trajectories, according to the imposed constrains such as maximum fuel consumption and spent time. The model of the system in MILP and A{sup}* algorithms is presented, as well as the ILP formulation for decision making. Results and discussions are given to promote future real time implementations.
In this paper, a control scheme applied to distributed UPSs forming a microgrid is proposed. The control architecture consists of two levels of hierarchy: 1) the P/Q droop control method of every UPS unit and 2) the m...
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In this paper, a control scheme applied to distributed UPSs forming a microgrid is proposed. The control architecture consists of two levels of hierarchy: 1) the P/Q droop control method of every UPS unit and 2) the management of the microgrid through the control of the setpoints of the units, and the connection or disconnection to the utility mains.
Providing required quality of water delivered to the consumers is still a challenging operational task at drinking water distribution systems. Water quality meets the quality requirements at the outputs from the treat...
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Providing required quality of water delivered to the consumers is still a challenging operational task at drinking water distribution systems. Water quality meets the quality requirements at the outputs from the treatment plants but it may significantly deteriorate when travelling throughout the system and become not usable at the consumption nodes. It becomes then necessary to introduce secondary chlorine disinfection at certain nodes within the system network. The booster stations are located at these quality control nodes to inject the chlorine so that the quality requirements are met throughout the network, including the consumption nodes. The integrated quality and quantity optimized control can then be safely carried out in the system. The paper proposes a method for allocation of the booster stations such that a desired trade off between several objectives is robustly achieved. An advanced genetic solver of the derived optimization task is applied to determine the optimized allocation. The method is illustrated by application to the case study system.
The paper considers a feedback optimising control of drinking water distribution systems (DWDS). Although the optimised pump and valves scheduling and disinfectant injection control attracted considerable attention ov...
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The paper considers a feedback optimising control of drinking water distribution systems (DWDS). Although the optimised pump and valves scheduling and disinfectant injection control attracted considerable attention over last two decades most of the contributions were limited to an open-loop optimisation repetitively performed during the DWDS operation. An information feedback from the DWDS is needed in reality in order to compensate uncertainty in the water demand prediction and the modelling errors. Also, while a strong interaction between the water quantity and quality exists most of the proposals regards either quality or quantity control. In this paper a generic model predictive controller for the optimising control of an integrated quantity and quality in DWDS is derived and applied to the case - study system. The simulation results based on real data records are presented..
MultiScale – Principal Component Analysis (MS-PCA) is a very suitable method for fault detection of wastewater treatment processes. It will be shown that MS-PCA can notice non-measurable process abnormalities signifi...
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MultiScale – Principal Component Analysis (MS-PCA) is a very suitable method for fault detection of wastewater treatment processes. It will be shown that MS-PCA can notice non-measurable process abnormalities significantly faster than a human eye. Simulation results based on bacteria population decrease case will be presented.
State Space Wavelet Network is a specific neural network with non trivial structure. Such a structure implies problems with the network training. In SSWN, during the training process, weights and wavelons parameters a...
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State Space Wavelet Network is a specific neural network with non trivial structure. Such a structure implies problems with the network training. In SSWN, during the training process, weights and wavelons parameters are adapted. This paper presents algorithms and methods for optimising the SSWN parameters. During researches Hybrid Distributed Evolutionary Algorithm has been developed and Extended initialisation strategy was applied. Finally it was found that usage of Hybrid Distributed Evolutionary Algorithm with extended initialisation significantly reduce the time of SSWN learning.
The predictive integrated water quantity and quality yields better performance then different approaches. However, it requires solving a nonlinear, non-convex optimization problem. Therefore, a specialized optimizatio...
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The predictive integrated water quantity and quality yields better performance then different approaches. However, it requires solving a nonlinear, non-convex optimization problem. Therefore, a specialized optimization solver has to be used within designated time. In this paper a dedicated genetic algorithm specially designed in order to efficiently solve predictive optimization task is derived and the simulation results of the case study Gdynia drinking water distribution system are presented.
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