Adaptive predictions of the euro/złoty currency exchange rate using state space wavelet networks and forecast combinations

The paper considers the forecasting of the euro/Polish złoty (EUR/PLN) spot exchange rate by applying state space wavelet network and econometric forecast combination models. Both prediction methods are applied to produce one-trading-day-ahead forecasts of the EUR/PLN exchange rate. The paper presents the general state space wavelet network and forecast combination models as well as their underlying principles. The state space wavelet network model is, in contrast to econometric forecast combinations, a non-parametric prediction technique which does not make any distributional assumptions regarding the underlying input variables. Both methods can be used as forecasting tools in portfolio investment management, asset valuation, IT security and integrated business risk intelligence in volatile market conditions

Adaptive prediction of stock exchange indices by state space wavelet networks

The paper considers the forecasting of the Warsaw Stock Exchange price index WIG20 by applying a state space wavelet network model of the index price. The approach can be applied to the development of tools for predicting changes of other economic indicators, especially stock exchange indices. The paper presents a general state space wavelet network model and the underlying principles. The model is applied to produce one session ahead and five sessions ahead adaptive predictors of the WIG20 index prices. The predictors are validated based on real data records to produce promising results. The state space wavelet network model may also be used as a forecasting tool for a wide range of economic and non-economic indicators, such as goods and row materials prices, electricity/fuel consumption or currency exchange rates

Adaptive predictions of the euro/złoty currency exchange rate using state space wavelet networks and forecast combinations

The paper considers the forecasting of the euro/Polish złoty (EUR/PLN) spot exchange rate by applying state space wavelet network and econometric forecast combination models. Both prediction methods are applied to produce one-trading-day-ahead forecasts of the EUR/PLN exchange rate. The paper presents the general state space wavelet network and forecast combination models as well as their underlying principles. The state space wavelet network model is, in contrast to econometric forecast combinations, a non-parametric prediction technique which does not make any distributional assumptions regarding the underlying input variables. Both methods can be used as forecasting tools in portfolio investment management, asset valuation, IT security and integrated business risk intelligence in volatile market conditions

Monitoring of chlorine concentration in drinking water distribution systems using an interval estimator

This paper describes the design of an interval observer for the estimation of unmeasured quality state variables in drinking water distribution systems. The estimator utilizes a set bounded model of uncertainty to produce robust interval bounds on the estimated state variables of the water quality. The bounds are generated by solving two differential equations. Hence the numerical efficiency is sufficient for on-line monitoring of the water quality. The observer is applied to an exemplary water network and its performance is validated by simulations

Servo tracking of targets at sea

This paper details a proposal for the position control system of a two-axis ship-mounted tracker. Aspects of the non-linear dynamics governing Line-Of-Sight (LOS) errors between the tracker and the target are presented. It is shown that the regulation of LOS errors can be achieved by introducing a feed-forward term based on the target’s velocity. This velocity is not measurable, and an estimator is required. Given that the tracking problem is non-linear, the classical separation principle does not hold, and cascading the estimator and regulator together may not lead to an optimal position control system. The ‘LQAdaptive’ system proposed here aims therefore to improve conformity to the separation principle. Simulation trials show that tracking is improved under the LQAdaptive system in comparison to a simple estimator-regulator structure

Fuzzy logic gain scheduling for non-linear servo tracking

This paper proposes the use of gain scheduling as a method of controlling a servo system with hard non-linear elements. The servo controls two elements of a tracker mounted on a ship at sea. There is stiction at the zero velocity point and non-linear friction against the motion of each tracker axis. A dual feedback loop control structure is employed. Fuzzy logic is used to provide smoothly varying non-linear scheduling functions to map the velocity of the servo relevant to the deck of the ship onto the rate loop controller parameters. Consideration is given to the use of a derivative signal as a secondary input to the fuzzy inference system. Results are presented which demonstrate that this method of controlling the servo system gives a dramatic improvement over the traditional linear control methodology for low velocity tracking performance. A linear PID controller is used in the outer loop and its design is also given some consideration

Design and Stability of Fuzzy Logic Multi-Regional Output Controllers

Design and stability analysis of fuzzy multi-regional digital controllers is considered in the paper. The controllers are based on a notion of NARMAX systems, very similar to the Takagi-Sugeno fuzzy model. The nonlinear system is approximated by a number of linear subsystems. Linear controllers are designed for all subsystems. It can be made in a classical way due to the subsystems linearity. The controllers are blended into one controller by employing fuzzy logic, the result being the fuzzy multi-regional controller (FuMR). The stability analysis of nonlinear systems with FuMR controllers composed of dynamic output feedback local linear controllers is provided. Examples illustrate the design procedure and the meaning of the stability criterion

Multiregional softly switched PI controller for dissolved oxygen tracking at wastewater treatment plant

Napowietrzanie jest podstawowym procesem decydującym o jakości oczyszczania ścieków. Prawidłowy przebieg procesów biologicznych wymaga dostarczenia odpowiedniej ilości tlenu. Zapewnia to optymalne warunki oczyszczania ścieków, dostateczne wymieszanie ścieków z osadem czynnym i zmniejsza główny koszt eksploatacji oczyszczalni ścieków, czyli koszt pompowania powietrza. W artykule zaproponowano sterowanie stężeniem tlenu z wykorzystaniem wielkoobszarowego miękko przełączalnego regulatora PI. Jako metodę przełączania pomiędzy sygnałami sterującymi w poszczególnych obszarach pracy układu wybrano metodę przełączania Takagi-Sugeno-Kanga. Zaprojektowany system sterowania został symulacyjnie zbadany na podstawie rzeczywistych danych z oczyszczalni ścieków w Kartuzach.Aeration is a very important and expensive process at wastewater treatment plant. Oxygen is provided as a fundamental component for the biological processes. This paper proposes the multiregional PI control system with softly switched Takagi-Sugeno-Kang method for dissolved oxygen concentration tracking. The controller is validated by simulation based on real data records from wastewater treatment plant in Kartuzy