Tomasz Zubowicz

A biochemical multi-species quality model of a drinking water distribution system for simulation and design

Abstract Drinking Water Distribution Systems (DWDSs) play a key role in sustainable development of modern society. They are classified as critical infrastructure systems. This imposes a large set of highly demanding requirements on the DWDS operation and requires dedicated algorithms for on-line monitoring and control to tackle related problems. Requirements on DWDS availability restrict the usability of the real plant in the design phase. Thus, a proper model is crucial. Within this paper a DWDS multi-species quality model for simulation and design is derived. The model is composed of multiple highly inter-connected modules which are introduced to represent chemical and biological species and (above all) their interactions. The chemical part includes the processes of chloramine decay with additional bromine catalysis and reaction with nitrogen compounds. The biological part consists of both heterotrophic and chemo-autotrophic bacteria species. The heterotrophic bacteria are assumed to consume assimilable organic carbon. Autotrophs are ammonia oxidizing bacteria and nitrite oxidizing bacteria species which are responsible for nitrification processes. Moreover, Disinfection By-Products (DBPs) are also considered. Two numerical examples illustrate the derived model’s behaviour in normal and disturbance operational states.

Decentralized oxygen control in multi-zone aerobic bioreactor at wastewater treatment plant

Abstract This paper addresses the dissolved oxygen tracking problem in multi-zone bioreactor. The proposed approach utilizes decentralized control system incorporating fuzzy multiregional PI controllers so that satisfactory controller performance can be robustly and reliably achieved over a whole process operating range. A fuzzy supervisor of the completely decentralized control system is introduced in order to meet a global actuator capacity constraint. An overall control system can be implemented by using fairly standard equipment that is commonly available at a plant site.

Robust parameter estimation and output prediction for reactive carrier-load nonlinear dynamic networks

Abstract In this paper an extension of on-line model simplification technique for a class of networked systems, namely reactive carrier-load nonlinear dynamic networked system (RCLNDNS), kept within point-parametric model (PPM) framework is addressed. The PPM is utilised to acquire a piece wise constant time-varying parameter linear structure for the RCLNDNS suitable for the on-line one step ahead prediction that may be applied to monitoring and model predictive control purposes. The advantageous structure of PPM offers a considerable simplification of those algorithms in terms of computational burden in comparison to the nonlinear structures. Moreover, the availability of technical tools makes the analysis of the final form algorithms straightforward. An application to water quality estimation/prediction in drinking water distribution system illustrates the technology.

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.

Robust identification of quadrocopter model for control purposes

The paper addresses a problem of quadrotor unmanned aerial vehicle (so-called X4-flyer or quadrocopter) utility model identification for control design purposes. To that goal the quadrotor model is assumed to be composed of two abstracted subsystems, namely a rigid body (plant) and four motors equipped with blades (actuators). The model of the former is acquired based on a well-established dynamic equations of motion while the latter is to be identified as a static relationship from laboratory experiments data. Moreover, the actuator model is to account for the on-flight battery power source voltage drop effects. The actuator parameter identification algorithm is kept in a set-membership framework. In addition a mechanism to reduce the conservativeness of the solution is proposed and applied. Numerical illustration of the results is provided.

Takagi-Sugeno fuzzy model of dissolved oxygen concentration dynamics in a bioreactor at WWTP

The importance of dissolved oxygen (DO) concentration control in aeration tanks of a bioreactor at flow-through wastewater treatment plant (WWTP) can easily be justified by technological requirements as well as simple economics. Firstly, appropriate levels of DO concentration are essential for the vitality of microorganisms that comprise the bioreactor. Secondly, the costs of DO concentration control related to the blower station operation constitute up to 75% of the plant-wide electric bill. This paper addresses a problem of Takagi-Sugeno fuzzy model identification of DO dynamics for control design purposes. In the proposed approach the fuzzy partitions and the corresponding fuzzy sets are identified based on the knowledge of the process. Local model structure is obtained based on a larger well-established cognitive model from which a well-defined parameter set follows. Thereafter, a parameter identification is performed. A case study example of a bioreactor at Kartuzy WWTP illustrates the workflow of the proposed identification algorithm.