Grzegorz Ewald

Grid Implementation of a Parallel Multiobjective Genetic Algorithm for Optimized Allocation of Chlorination Stations in Drinking Water Distribution Systems: Chojnice Case Study

Solving multiobjective optimization problems requires suitable algorithms to find a satisfactory approximation of a globally optimal Pareto front. Furthermore, it is a computationally demanding task. In this paper, the grid implementation of a distributed multiobjective genetic algorithm is presented. The distributed version of the algorithm is based on the island algorithm with forgetting island elitism used instead of a genetic data exchange. The algorithm is applied to the allocation of booster stations in a drinking water distribution system. First, a multiobjective formulation of the allocation problem is further enhanced in order to handle multiple water demand scenarios and to integrate controller design into the allocation problem formulation. Next, the new grid-based algorithm is applied to a case study system. The results are compared with a nondistributed version of the algorithm.

Model Predictive Controller for Networked Control Systems

Abstract Control of the networked control systems is a crucial challenge. In the environment of shared communication media, data may be randomly delayed or even lost. As the shared communication links are used in the critical infrastructure systems, the problem becomes even more important. As opposed to network compensation, solutions presented in the paper integrate network with the controlled plant. The proposed networked control system employs the model predictive control technology and is based on the buffer in the actuator. Stability of the presented solution used to control a linear discrete time system is analyzed. A simulation example is also provided.

IMPLEMENTATION OF INTEGRATED CONTROL IN DRINKING WATER DISTRIBUTION SYSTEMS–IT SYSTEM PROPOSAL

Abstract Implementation of integrated control algorithms requires suitable hardware and software platforms. Proposed solution must allow realizing control and monitoring tasks, while ensuring high reliability and security of processed data. Additionally, the software and hardware solutions must be immune to outside influence. This paper presents an approach to implementation of control systems in drinking water distribution system. Presented approach takes into consideration safety and reliability of the control core.

Multiprocessor Implementation of Parallel Multiobjective Genetic Algorithm for Optimized Allocation of Chlorination Stations in Drinking Water Distribution System a New Water Quality Model Approach

Abstract The Critical Infrastructure Systems (CISs) have received in recent years a considerable attention due to their heavy impact on sustainable development of modern societies. Most CISs may be classified as large scale complex systems of network structure, influenced by strong interactions form the surrounding environment, internal and external interconnections. The later is a result of inter-CIS dependencies. The control, monitoring and control of these system is crucial to guaranty safe access to the resources distributed by the means of CIS. Among those systems the Drinking Water Distribution System (DWDS) may be found – a nonlinear dynamic carrier-load networked system. To handle these systems in a proper (robustly feasible) manner one needs to consider a nontrivial control task complimented by a set of input and state constraints. This surely points to model predictive optimal control schemes. To carry on the control a set of actuators – disinfectant booster stations – needs to be allocated within the DWDS to enable the control system to be robustly feasible. The task of optimised allocation has been addressed within this paper based on old (linear) and new (nonlinear) quality models in order to determine the impact of model structure and thus precision on the allocation results. The allocation task is formulated as a multiobjective, nonlinear/linear mixed-integer optimisation problem to be solved by a genetic algorithm (implementation of NSGA-II) due to nature of the problem. The newly obtained numerical examples are to illustrate the results. For this purpose a Chojnice (city in northern Poland) DWDS case study plant was utilised.

Research Platform for Monitoring, Control and Security of Critical Infrastructure Systems

Abstract Sustainable operation of Critical Infrastructure Systems (CISs) is of a major concern to modern societies. Monitoring, control and security of such systems plays a key role in guaranteeing continuous, reliable and above all secure access to the resources provided by these systems. Development of adequate software and hardware structures, as well as algorithms to perform such functions cannot be done apart from the operational conditions of the plant. On the other hand the dependencies between the resources provided by the CIS and the societies, prevents from experiments. Also this approach could be found costly and hard to justify in the world driven by hard economics. This, once again calls for the simulation tools to be exploited. Due to the vast complexity of these systems including spatial distribution over a wide area, a control engineering based multiagent framework is often utilised to cope with the issues of monitoring, control and security of CIS. Since there is no off the shelve solution for the development of such systems a novel, interesting, approach is proposed within this work to cope with the CIS simulation environment. The environment is based on the JADE and Matlab. A simple, but computational demanding example is provided, presenting the abilities and performance of the Research Platform. The simulation example is presented in the context of the new complex water quality model.

EVENT DRIVEN MPC FOR NETWORKED CONTROL SYSTEMS

Abstract Because of variable delays and stochastic data packets loss networked control systems require suitable algorithms to ensure stability of the control system and guarantee desired control performance. This paper presents the idea of an event driven approach with MPC controller. In opposition to network compensation, where standard regulators are used, the presented solution integrates network with plant. A MPC based controller is applied to extended plant that consists of plant and communication network. In order to reduce network influence on control quality, control signal computation and control signal application are done, when a data receive event occurs.

SSWN learning algorithms with application to WWTP

Abstract 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.

GRID IMPLEMENTATION OF PARALLEL MULTIOBJECTIVE GENETIC ALGORITHM FOR OPTIMISED ALLOCATION OF CHLORINATION STATIONS IN DRINKING WATER DISTRIBUTION SYSTEMS: CHOJNICE CASE STUDY

Abstract There is a group of problems that require big amount of computing power to solve. Computer grids allow building effective computing platforms at relatively low cost. It is expected that algorithms like Genetic Algorithm will perform well on the grid. In this paper, grid implementation of multiobjective distributed genetic algorithm is proposed. A distributed version of the algorithm is based on a modified island algorithm where genetic data exchange is replaced by introduced new Forgetting Island Elitism. The algorithm is applied to booster station allocation in Chojnice water distribution system.

Hybrid approach to Networked Control System

Abstract Efficient control of Networked Control System (NCS) is a challenge, as the control methods need to deal with non-deterministic variable delays and data loss. This paper presents a novel hybrid approach to NCS where Model Predictive Control (MPC) is applied as a main controller and implicit switching MPC is used for data transmission control in event-driven shared communication medium, leading to complex control system with active data transmission mechanisms.