Hybrid Dynamical Approach Research Articles

A Hybrid Dynamical Approach for Seasonal Prediction of Sea‐Level Anomalies: A Pilot Study for Charleston, South Carolina

AbstractUsing Earth system models for seasonal sea‐level prediction remains challenging due to model biases and initialization shocks. Here we present a hybrid dynamical approach for seasonal sea‐level prediction to alleviate some of these issues. The approach is based on convolving atmospheric forcings with sea‐level sensitivities to these forcings. The sensitivities are pre‐computed by the adjoint model of the Estimating Circulation and Climate of the Ocean (ECCO) system. The forcings are a concatenation of ECCO forcings before prediction initialization and a 10‐member predicted atmospheric forcing ensemble from the Community Climate System Model version 4 (CCSM4) after initialization, with offline forcing bias corrections applied using the observationally‐constrained ECCO seasonal forcing climatology. As a pilot study, we conducted 12‐month hindcasts from 1995 to 2016 in Charleston (United States East Coast). Our approach avoids drifts in CCSM4 sea‐level predictions and beats seasonal climatology and damped persistence as predictors up to a 6‐month lead time. The prediction skill comes from two factors: (a) ECCO forcings prior to prediction initialization influence sea level after initialization through delayed oceanic adjustments (e.g., coastally‐trapped waves, open‐ocean Rossby waves, and advection of steric anomalies) leading to skillful predictions beyond 2 months after initialization, and (b) the 10‐member CCSM4 ensemble forcing predictions have relatively good skill at 1–2 months lead times. Our method is computationally efficient for operational sea‐level prediction at specific locations and can attribute sea‐level prediction skill and uncertainty to specific forcings or forcing from particular regions, thereby providing useful information to seasonal prediction centers for improving their prediction systems.

Data Supplement for 'A hybrid dynamical approach for seasonal prediction of sea-level anomalies: a pilot study for Charleston, South Carolina'

Data Supplement for 'A hybrid dynamical approach for seasonal prediction of sea-level anomalies: a pilot study for Charleston, South Carolina'

Time-triggered and event-triggered control of switched affine systems via a hybrid dynamical approach

This paper focuses on the design of both periodic time- and event-triggered control laws of switched affine systems using a hybrid dynamical system approach. The novelties of this paper rely on the hybrid dynamical representation of this class of systems and on a free-matrix min-projection control, which relaxes the structure of the usual Lyapunov matrix-based min-projection control. This contribution also presents an extension of the usual periodic time-triggered implementation to the event-triggered one, where the control input updates are permitted only when a particular event is detected. Together with the definition of an appropriate optimization problem, a stabilization result is formulated to ensure the uniform global asymptotic stability of an attractor for both types of controllers, which is a neighborhood of the desired operating point. Finally, the proposed method is evaluated through a numerical example.

Hybrid Controller with Fuzzy Logic Technique for Three Phase Half Bridge Interleaved Buck Shunt Active Power Filter

This paper addresses a new control of three phase half bridge interleaved buck shunt active power filter (HBIB-SAPF). We aim for a control strategy achieving simultaneously, the two following objectives: i) compensation of harmonic currents and reactive power absorbed by nonlinear loads for satisfying a power factor correction; ii) regulation of the HBIB converter DC capacitor voltage. To meet the above objectives, the proposed controller structure consists of two loops. The inner loop is designed using a hybrid dynamical approach to model the system, the hybrid automaton is proposed to deal with the compensation topic by switching between the different operative modes, which is conditioned by some invariance and transition conditions. The outer loop is built up based on fuzzy logic control (FLC), applied to regulate the DC bus voltage of three phase HBIB-SAPF. It is confirmed, via simulation results in Matlab/ SimPowerSystems & Stateflow toolbox that the proposed controller actually achieves the objectives it is designed for.

A Hybrid Dynamical Modelling and Control Approach for Energy Saving of Central Air Conditioning

Currently in China, energy conservation and emission reduction are important initiatives for society. Because of its large proportion of building energy consumption, several methods for building energy conservation have been introduced for central air conditioning. This paper presents a hybrid system for a modelling and control approach. By analysing the cooling capacity transfer process and the electromagnetic properties of pumps, the modelling is performed in a hybrid system framework. Pumps are classified as fixed-frequency pumps, variable-frequency pumps, and switchable pumps; a switch control strategy is used in the chilled water system for supplying cooling capacity. In order to adjust indoor temperature and save electrical energy, the cooling capacity allocation and average temperature methods are presented, which satisfy the goal of optimal control of real-time energy consumption. As a numerical example, the temperature variation and cold regulation processes are simulated. Three rooms are the control objects that lower the setting points, and pumps waste as little electrical energy as possible. The results show 49.4% of water pump power consumption when compared with constant water volume technology. The modelling and control approach is more advantageous in ensuring the success of reconstruction projects for central air conditioning.

A Hybrid Dynamical Approach for Allocating Materials in a Dry Bulk Terminal

This paper proposes a new modeling and control methodology for allocating materials in a dry bulk terminal with a finite storage capacity. The dynamical process of material storage allocation in the terminal is modeled using a hybrid system perspective that combines both discrete-event and continuous-time dynamics. The stockyard space is partitioned into a number of slots for exchanging incoming and outgoing material flows in the terminal, leading to a so-called mixed logical dynamical (MLD) model with the maximal storage capacity. Based on the MLD model, a model predictive controller is then proposed for maximizing the economic profit in a rolling horizon manner. A number of Monte Carlo simulations have been performed involving a real case study for analyzing the effects of different slot volumes on the economic performance and the computational performance of the controller. Simulations also demonstrate the potential of the proposed methodology. Note to Practitioners —This paper is motivated by the problem of allocating dry bulk materials in the stockyard of a small import terminal. In current approaches for allocating materials, the storage capacity cannot be considered, and this could lower the terminal profit resulting from delaying the vessel in the terminal when a finite storage capacity is considered. This paper suggests a new approach from a hybrid system perspective that captures the dry bulk terminal operation dynamics. In this paper, we mathematically describe the process of allocating materials into different slots in the stockyard using a hybrid dynamical model and propose a model predictive controller to maximize the terminal operation profit. We then show how the slot size influences the economic performance and analyze its associated computations by conducting simulation experiments involving a case study. Simulation experiments also suggest that this approach achieves significantly more economic benefits compared with current approaches. In future research, a large intermodal terminal will be investigated whereby incoming and outgoing materials of different transport modalities need to be coordinated properly.

New MPPT algorithm for PV applications based on hybrid dynamical approach

This paper proposes a new Maximum Power Point Tracking (MPPT) algorithm for photovoltaic applications using the multicellular converter as a stage of power adaptation. The proposed MPPT technique has been designed using a hybrid dynamical approach to model the photovoltaic generator. The hybrid dynamical theory has been applied taking advantage of the particular topology of the multicellular converter. Then, a hybrid automata has been established to optimize the power production. The maximization of the produced solar energy is achieved by switching between the different operative modes of the hybrid automata, which is conditioned by some invariance and transition conditions. These conditions have been validated by simulation tests under different conditions of temperature and irradiance. Moreover, the performance of the proposed algorithm has been then evaluated by comparison with standard MPPT techniques numerically and by experimental tests under varying external working conditions. The results have shown the interesting features that the hybrid MPPT technique presents in terms of performance and simplicity for real time implementation.

Optimal distributed real-time scheduling of flexible manufacturing networks modeled as hybrid dynamical systems

The paper considers a class of flexible manufacturing networks. We employ hybrid dynamical systems to model such networks. The main and new achievement of the paper is that we propose a distributed implementable in real time scheduling rule such that the corresponding closed-loop system is stable and optimal. In stable systems the processes converge to periodic ones. The paper gives computing relations for the determination of the parameters of the periodic processes. These are very much suitable for planning purposes. On this basis—and this, we consider, is also a new, significant result—optimal arrival (demand) rates determination method is proposed. Quality characteristics are outlined. Field of application of hybrid dynamical approach for FMS scheduling is analyzed. The results open perspectives for MRP level task planning. Example and simulation results are presented.

Modelling Transcriptional Interference and DNA Looping in Gene Regulation

We describe a hybrid statistical mechanical and dynamical approach for modelling the formation of closed, open and elongating complexes of RNA polymerase, the interactions of these polymerases to produce transcriptional interference, and the regulation of these processes by a DNA-binding and DNA-looping regulatory protein. As a model system, we have used bacteriophage 186, for which genetic, biochemical and structural studies have suggested that the CI repressor binds as a 14-mer to form alternative DNA-looped complexes, and activates lysogenic transcription indirectly by relieving transcriptional interference caused by the convergent lytic promoter. The modelling showed that the original mechanisms proposed to explain this relief of transcriptional interference are not consistent with the available in vivo reporter data. However, a good fit to the reporter data was given by a revised model that incorporates a novel predicted regulatory mechanism: that RNA polymerase bound at the lysogenic promoter protects itself from transcriptional interference by recruiting CI to the lytic promoter. This mechanism and various estimates of in vivo biochemical parameters for the 186 CI system should be testable. Our results demonstrate the power of mathematical modelling for the extraction of detailed biochemical information from in vivo data.

Global modeling of nitrate and ammonium: Interaction of aerosols and tropospheric chemistry

Global radiative forcing of nitrate and ammonium aerosols has mostly been estimated from aerosol concentrations calculated at thermodynamic equilibrium or using approximate treatments for their uptake by aerosols. In this study, a more accurate hybrid dynamical approach (HDYN) was used to simulate the uptake of nitrate and ammonium by aerosols and the interaction with tropospheric reactive nitrogen chemistry in a three‐dimensional global aerosol and chemistry model, Umich/IMPACT, which also treats sulfate, sea salt and mineral dust aerosol. The calculated sulfate, ammonium and nitrate aerosol concentrations show good agreement with the available ground‐based measurements over both ocean and land areas. The global annual average nitrate aerosol burden is 0.16 Tg N, with 43% (i.e., 0.079 Tg N) in the fine mode (D < 1.25 μm) that scatters most efficiently. The global annual average ammonium burden is 0.29 Tg N with 92% in the fine mode. A sensitivity study with a thermodynamic equilibrium model underestimates the fine‐mode nitrate aerosol burden by 25%, because of the excessive nitrate formation on coarse aerosols. These underpredictions are especially important in the remote continents or over the oceans, where the availability of the total nitrate is limited. We also examined two common approaches used to treat nitrate and ammonium aerosols in global models, including the first‐order gas‐to‐particle approximation based on uptake coefficients (UPTAKE) and a simple hybrid method that combines the former with an equilibrium model (HYB). The two methods calculate higher nitrate aerosol burdens than HDYN by +106% and +47%, respectively. Both fine‐ and coarse‐model nitrate aerosols are overestimated by UPTAKE, but the overestimation by HYB is mainly due to uptake of nitrate by the coarse aerosols. As a result, HYB calculates lower surface concentrations of the fine‐mode nitrate aerosol by up to 50% over most continental areas, compared to HDYN. Surface HNO3 and NOx concentrations are underpredicted by HYB by up to 90% and 5%, respectively. Since the reaction of N2O5 on sulfate aerosols is not included in the UPTAKE method, the NOx burden and surface concentrations are overestimated by 56% and a factor of 2–5, respectively. These results suggest the importance of using the more accurate hybrid dynamical method in the estimates of both aerosol forcing and tropospheric ozone chemistry.

Improving FMS scheduling by lot streaming

The global minimum of completion time for manufacturing systems is determined by the processing capacities of the bottleneck machine-group. How to go close to this minimum for given production tasks is analysed in the paper. Lot streaming can significantly improve the schedules. Hybrid Dynamical Approach (HDA) realizes in automatic way lot streaming and overlapping production. A Brute Force Method (BFM) is proposed in the paper when HDA can not be applied. The essence of this is that the series are divided into the same number of sub-series. The increase of sub-series number stops when the completion time becomes suitable. The effect of setup times is analysed. Theoretical analysis for a simplified problem is performed and planning proposals are provided.

Periodic and transient switched server schedules for FMS

Hybrid dynamical approach is an effective way of solving FMS scheduling problems. In this paper the mathematical model and processes determination are shortly reviewed. New results are outlined for the determination of time periods of periodic motions for simple (two part types) problems and for complex (multi-part types, multi-machine groups) cases, too. Having the time periods, all the significant planning parameters can be easily determined. As a consequence of the above, the idea of periodic and transient schedules is introduced. A planning procedure is developed. Based on the new prospects obtained, an important development of the mathematical model is proposed. This is to expand the mathematical model with buffer capacities constraints. These new constraints determine the final results of planning. Using a manipulation of set-up times (regularizibility) a future improvement of the processes can be realized. All this leads to a very simple, real-time scheduling of FMS.

Pragmatic aspects of the solution of FMS scheduling problems using hybrid dynamical approach

Hybrid Dynamical ( or Switched Server) approach is a relatively new direction in the solution of FMS scheduling problems. The theoretical results in this field are promising, but a number of questions should be cleared for practical applications. Some of these are: How to choose demand rates? How to provide the stability of processes in multi-machine group cases? What are the main characteristics of the processes and how to determine the suitable values of the parameters? In relation to the first two questions, proposals are given in the present paper. For demand rates determination, relations giving the upper and lower boundary values are proposed. For multi-machine group processing, the controlled buffer technique was developed. In relation to the others, simulation studies are proposed. Two of the simulation approaches are described in this paper and some demonstration is also given. The simulation results obtained from case studies show that the overlapping production obtained using the hybrid dynamical approach (HDA) are far more effective than batch processing. The decrease of production times may reach 20–30% or more.

Optimisation Aspects of Hybrid Dynamical Approach to FMS Scheduling

Good quality of scheduling is a key issue for Manufacturing Systems (CIM, FMS, CAD/CAM, etc.). Optimisation problems were formulated for this field, but, to find solutions is very hard task. In practise, heuristic methods, based on priority rules, can be used, providing suitable schedules. Recently, AI (Artificial Intelligence) techniques promise effective ways for quality solutions. A little bit more than 10 years ago, a new formulation of the problem the Hybrid Dynamical Approach was proposed for high number of parts cases. One of the authors (see: Somlo, 2001) proposed for this a new demand rate determination method and the so called controlled buffer technique to handle multiple machine group cases. In the present paper it is shown that this new proposals allow to realise schedules resulting close to the global optimum results if the performance measure is the minimum of maximums of completion time. From engineering point of view the solution corresponds to the use of dynamic division of series to sub-series and overlapping production. The processes can be analysed by simulation methods. A discrete simulation system was developed, see: (Anufriev, 2002)

Study of Hybrid Dynamical Approach for Manufacturing Systems Scheduling by Discrete Event Simulation

This article uses a novel construction of double buffer structure serving manufacturing systems and providing higher utilization of machines. The proposed system automatically changes parameters giving a possibility of predesign based on the actual demand rates. The effectiveness of manufacturing system using event-controlled buffers depends on the applied switching policies and on the method of the determination of demand rates. Each of the production system elements have simple analytical model. But, if they are connected together into the proposed event controlled buffer structure the only way of analysing the system processes is the simulation technique. The modelling of process when hybrid dynamical approach is applied for manufacturing scheduling is outlined in this paper.

Discrete Model for Hybrid Dynamical Approach to FMS Scheduling

Introduction to the use of hybrid dynamical approach to FMS scheduling is given. New results in formatting the demand rate requirements in the field of discrete models of switching laws are outlined. It is relatively simple task to determine the suitable processes at single machine processing. It is rather complicated to handle the multiple machine job shop type manufacturing case. In the paper a new way: the use of controlled buffer technique is proposed to solve this problem.