Energy Optimal Control Research Articles

Energy-Optimal Control of an Automotive Air Conditioning System for Ancillary Load Reduction

The air conditioning (A/C) system is currently the largest ancillary load in passenger cars, with a significant impact on fuel economy and CO2 emissions. Considerable energy savings could be attained by simply adopting supervisory energy management algorithms that operate the A/C system to reduce power consumption of the compressor, while maintaining the cabin comfort requirements. This paper proposes a model-based approach to the design of a supervisory energy management strategy for automotive A/C systems. Starting from an energy-based model of the A/C system that captures the complex dynamics of the refrigerant in the heat exchangers and the compressor power consumption, a constrained multiobjective optimal control problem is formulated to jointly account for fuel consumption, cabin comfort, and system durability. The tradeoff between fuel economy, performance, and durability is analyzed by performing a Pareto analysis of a family of solutions generated using dynamic programming. A forward-looking optimal compressor clutch policy is then obtained by developing an original formulation of Pontryagin's minimum principle for hybrid dynamical systems. The simulation results demonstrate that the proposed control strategy allows for fuel economy improvement while retaining system performance and driver comfort.

Optimal Energy Control of a Grid-Connected Solar Wind-Based Electric Power Plant Applying Time-of-Use Tariffs

The paper considers the daily energy consumption variations for low demand season and high demand season weekdays and weekends in order to compare the corresponding fuels cost and analyse the operational efficiency of the PV/PW/DG/battery system for 24 hours period taken as control horizon. Previous researches have assumed a fixed load and uniform daily cost. A load following diesel dispatch strategy is used in this paper and the fuel costs and energy flows are analysed. The results show that a renewable energy system which combines the PV/PW/diesel/battery models achieves a better saving for the fuel during the high demand as well as the low demand seasons for days considered when compared to a model where the diesel generator satisfies the loads on its own.

OPTIMAL IMPACT ANGLE CONTROL GUIDANCE LAWS AGAINST A MANEUVERING TARGET

Optimal impact angle control guidance law and its variants for intercepting a maneuvering target are introduced in this paper. The linear quadratic(LQ) optimal control theory is reviewed first to setup framework of guidance law derivation, called the sweep method. As an example, the inversely weighted time-to-go energy optimal control problem to obtain the optimal impact angle control guidance law for a fixed target is solved via the sweep method. Since this optimal guidance law is not applicable for a moving target due to the angle mismatch at the impact instant, the law is modified to three different biased proportional navigation(PN) laws: the flight path angle control law, the line-of-sight(LOS) angle control law, and the relative flight path angle control law. Effectiveness of the guidance laws are verified via numerical simulations.

Oscillators Near Hopf Bifurcation

In this paper the differential transformation method (DTM) is employed to solve a system of linear differential equations derived for energy optimal control theory and nonlinear differential equations and their systems for oscillators near Hopf bifurcation. They are given by differential equations in a complex plane. Different types of forced terms are considered. The approximate solutions are given in the form of series with required accuracy. Some numerical examples are provided.

Development of Dynamically Optimized Wireless Transmission System for Wireless Sensor Networks in Highrise Apartment Building Heating Systems / Optimizētas Dinamiskās Bezvadu Sensoru Tīklu Pārraides Risinājuma Izstrāde Daudzstāvu Ēku Apkures Sistēmas Parametru Izgūšanai Un Vadībai

Abstract Smart meters will be at the centre of the integrated solutions, including interaction with other networks in the next decade. The developed solution for multi-apartment building ventilation and heating parameter monitoring aims to increase energy efficiency and optimal control of the existing system. Dynamic control of heat and ventilation systems, heat loss detection, calculation and mitigation, and individual heat energy accounting are difficult tasks to accomplish. This article deals with the data transmission system using battery powered ISM band radio transmitters. The temperature measurement sensors with cumulative temperature reading are used as sensor part for this solution. The offered approach to monitoring system is used for overall building and individual apartment monitoring. Data coding and antenna designs are explained for this particular application.

Diurnal changes in Sorghum leaf starch molecular structure

Control of the fine structure of transitory starch synthesized during the day in leaves is required for its normal degradation during the subsequent night. In this study, the molecular structure of transitory starch from Sorghum leaves over the diurnal cycle was characterized using size-exclusion chromatography. This is the first study of diurnal changes in the chain-length distribution (CLD) of amylopectin and amylose over the entire range of chain lengths, and in the size distribution of whole starch molecules. It was found that the outer layers of leaf starch granules, which were synthesized during the daytime and degraded during the night, contained more large molecules, including amylopectin with more short chains and more branching, than those in the inner layers. The outer layers also had lower amylose content. Starch molecular sizes in leaves are much smaller than in grain starch. The starch structures observed are likely to give optimal energy control during plant growth. Lack of this control may contribute to poor plant growth.

Suboptimal formation reconfiguration of satellites under input directional constraints

Proximity operations of satellites such as formation flying and on-orbit servicing offer more advanced missions than missions achieved by a single satellite. In a practical situation of formation flying, thrust directions for keeping and controlling a relative orbit is limited, e.g., for astronomical observation and plume impingement avoidance. The aim of this paper is to provide an energy efficient control method for a formation reconfiguration under input directional constraints with respect to both an inertial and a leader-fixed frames. The proposed controller is designed consisting of two parts: (1) guaranteeing a formation reconfiguration to a desirable formation on the basis of an energy optimal controller and (2) satisfying the input directional constraints by superimposing additional inputs. The analytical form of the control input shows that the input direction forms an ellipse in the leader-fixed frame when a particular boundary condition is satisfied, which is exploited as a nominal controller to take into account the input directional constraints. Due to the singularity avoidance of the nominal controller, the additional inputs can be analytically obtained. The effect on the follower trajectory due to the additional inputs is compensated by setting a virtual target orbit, and thus the successful formation reconfiguration is still guaranteed. Some numerical simulation results verify the effectiveness of the proposed method and compare the energy efficiency.

Energy Optimal Control Design for Steer-by-Wire Systems and Hardware-in-the-Loop Simulation Evaluation

A Steer-By-Wire (SBW) control scheme is proposed for enhancing the lateral stability and handling capability of a super lightweight vehicle by using the energy optimal control method. Tire dissipation power and virtual power, which is the product of yaw moment and the deviation of actual yaw rate from the target yaw rate, were selected as performance measures to be minimized. The SBW control scheme was tested using Hardware-In-the-Loop (HIL) simulation on an SBW test rig. The case studies performed were high-speed rapid lane change, crosswind, and braking-in-a-turn. HIL simulation results showed that the SBW control scheme was able to maintain vehicle stability. The proposed SBW control design taking advantage of the full range steering of front wheel, significantly improves the vehicle handling capability. The results also demonstrate the importance of SBW control for super lightweight vehicles.

Optimal entrainment of heterogeneous noisy neurons.

We develop a methodology to design a stimulus optimized to entrain nonlinear, noisy limit cycle oscillators with uncertain properties. Conditions are derived which guarantee that the stimulus will entrain the oscillators despite these uncertainties. Using these conditions, we develop an energy optimal control strategy to design an efficient entraining stimulus and apply it to numerical models of noisy phase oscillators and to in vitro hippocampal neurons. In both instances, the optimal stimuli outperform other similar but suboptimal entraining stimuli. Because this control strategy explicitly accounts for both noise and inherent uncertainty of model parameters, it could have experimental relevance to neural circuits where robust spike timing plays an important role.

Convergence non-destructive evaluation system for the parts and materials

Ultrasound infrared thermography non-destructive analysis system for main shaft of offshore wind power generator is established. As preliminary study, optimal design of ultrasound excitation equipment and infrared thermography analysis for optimal design and external energy control is investigated. For the improved defect detection capability through higher energy penetration, optimal design for ultrasound transducer and excitation time (defect detection time) is determined. Impact of ultrasound incident angle and contact point of ultrasound horn is analysed. In addition, amplitude is controlled through controller for ultrasound excitation, and elastic wave from ultrasonic energy will be injected to test unit in a short amount of time using lock-in wave mode. Periodic injection causes heat generation in defect area, and time for preventing significant temperature increase and cooling time is also controllable. Using the specially designed and fabricated jig for ultrasound infrared thermography, optimal design for ultrasound equipment can be achieved.

Optimal energy control of grid tied PV–diesel–battery hybrid system powering heat pump water heater

This paper develops an optimal control strategy for power dispatch of the grid-tied photovoltaic (PV)–battery–diesel system to power heat pump water heaters (HPWH). The system consists of the PV modules, grid, battery, HPWH, diesel generator (DG) and other domestic appliances. The PV can simultaneously feed in the excess power to the grid and supply the loads. The battery is used as storage of cheaper-to-buy off-peak grid energy, dependent on the time-of-use (TOU) electricity tariff, while the DG is a backup power source to the HPWH. The objective function of the model is to minimize energy and fuel cost while maximizing PV energy trade-off for incentives. The TOU is an important control parameter in this model. The power flows from each power source are the control variables. The optimal control shows a great potential to realize a practical net zero-energy building and demand side management. This model meets both the technical and operational constraints. A case study is done based on a 3×16kW HPWH installed at a Pretoria Hotel in South Africa. Simulations run over a year on selected seasonal dates using the actual measured demand of the HPWH. The optimal control problem is solved using a mixed integer non-linear program and the results show how TOU affects the power dispatch to the HPWH. The energy and cost savings are presented in this paper.

Near Optimal Energy Control and Approximate Capacity of Energy Harvesting Communication

We consider an energy-harvesting communication system where a transmitter powered by an exogenous energy arrival process and equipped with a finite battery of size B <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">max</sub> communicates over a discrete-time AWGN channel. We first concentrate on a simple Bernoulli energy arrival process where at each time step, either an energy packet of size E is harvested with probability p, or no energy is harvested at all, independent of the other time steps. We provide a near optimal energy control policy and a simple approximation to the information-theoretic capacity of this channel. Our approximations for both problems are universal in all the system parameters involved (p, E and B <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">max</sub> ), i.e., we bound the approximation gaps by a constant independent of the parameter values. Our results suggest that a battery size B <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">max</sub> ≥ E is (approximately) sufficient to extract the infinite battery capacity of this channel. We then extend our results to general i.i.d. energy arrival processes. Our approximate capacity characterizations provide important insights for the optimal design of energy harvesting communication systems in the regime where both the battery size and the average energy arrival rate are large.

Energy Optimal Control of PMSM Drive for Time-Varying Load Torque

Speed and position controller respecting principles of energy optimal control for the drives with permanent magnet synchronous motor and time varying load torque are developed as a contribution to the energy saving and environmental protection. Two approaches to the energy saving controller design are analyzed and compared. The first one is strictly based on energy optimal control theory and derives analytical solutions of the control problem. The second approach for comparison presents approximated solution for the drive’s position controller when the optimal speed trajectory is modified to trapezoidal profile. Results are verified by simulation.

Energy-optimal control of temperature for wine fermentation based on a novel model including the yeast dying phase

We study energy-optimal control of the cooling process during wine fermentation. The process of wine fermentation is described by a novel model (Borzì et al. (2014)) including a death phase for yeast and the influence of oxygen on the process. The parameters determining the fermentation dynamics are estimated from measurements and the optimal cooling profile is computed. The numerical results regarding the development of the substrates and the product as well as the control profiles for a common fermentation temperature profile and the optimal temperature profile are compared. It turns out that significant improvement can be achieved by using the optimal calculated temperature profile.

Optimal energy control of a crushing process based on vertical shaft impactor

This paper presents an optimal control model to improve the operation energy efficiency of a vertical shaft impact (VSI) crushing process. The optimal control model takes the energy cost as the performance index to be minimized by accounting for the time-of-use tariff and process constraints such as storage capacity of the VSI crusher hopper, capacity of the main storage system, flow rate limits, cascade ratio setting, production requirement and product quality requirement. The control variables in the developed model are the belt conveyor feed rate, the material feed rate into the VSI crusher rotor, the bi-flow or cascade feed rate and the rotor tip speed of the crusher. These four control variables are optimally coordinated in order to improve the operation energy efficiency of the VSI crushing process. Simulation results based on a crushing process in a coal-fired power plant demonstrate a potential of a daily energy cost saving of about 49.7% and energy saving of about 15.3% in a high-demand season weekday.

Estimation and predictive control of nonlinear diffusion processes with application to drying of coatings

This article deals with the estimation and control of a class of distributed parameter processes dominated by nonlinear diffusion. The major challenges in control of such systems lie in the nonlinear infinite-dimensional nature of the systems and the lack of direct sensing for relevant system states. In the proposed scheme, the proper orthogonal decomposition-Galerkin method is adopted to derive a reduced-order model in terms of temporal coefficients from the original system described by nonlinear partial differential equation(s). To overcome the sensing problem, the unscented Kalman filter is implemented to estimate the temporal coefficients of the reduced-order model online and subsequently reconstruct the distributed system states. A set of improved sufficient conditions are also established to ensure stability of the estimation scheme. Then, once these difficulties are addressed, a nonlinear model predictive control scheme is formulated to achieve desired control objectives such as trajectory tracking for distributed states, energy optimization and quality control. The proposed estimation and control scheme is demonstrated via an application to infrared drying of coatings in the automotive industry.

Energy Optimal Control of Induction Motor for Electric Vehicle Drive System Base DTC

The requirements of the drive system for electric vehicle is high efficiency and fast dynamic response, an optimal control method base direct torque control is proposed to improve respose speed of energy optimal controlled induction motor. In stator flux orientation coordinate system, the loss mathematical model of the induction motor was established by analyzing the relationship between loss and motor torque, speed and stator flux, then the optimal stator flux formula is derived under different operating conditions to achieve the maximum efficiency of induction motor, the getted optimal stator flux is used as stator flux set value in DTC. Simulation results reveal that the proposed method improve the efficiency and respose spee of induction motor.

Strategy of Intelligent Energy-Saving Optimization Control and Energy Consumption Analysis on Regulator Control System of Closed Greenhouse

Adopting the integrated TOPSIS intelligent energy optimization control strategy, and compared to conventional single control strategy on energy consumption of greenhouse equipment under closed condition, this paper arrives at the best energy saving optimization control strategy with comprehensive benefits. The result shows that, integrated intelligent optimizing control was obviously more energy saving compared to those did not take optimization control. Specific results as follows: TOPSIS integration strategy with energy saving of 725.39kwh, energy-saving rate of 44.19%.This shows that the proposed integrated intelligent energy optimization control strategy and energy saving effect is remarkable.

A Hamilton-Jacobi-Bellman approach for termination of seizure-like bursting.

We use Hamilton-Jacobi-Bellman methods to find minimum-time and energy-optimal control strategies to terminate seizure-like bursting behavior in a conductance-based neural model. Averaging is used to eliminate fast variables from the model, and a target set is defined through bifurcation analysis of the slow variables of the model. This method is illustrated for a single neuron model and for a network model to illustrate its efficacy in terminating bursting once it begins. This work represents a numerical proof-of-concept that a new class of control strategies can be employed to mitigate bursting, and could ultimately be adapted to treat medically intractible epilepsy in patient-specific models.

Review of building energy modeling for control and operation

Buildings consume about 41.1% of primary energy and 74% of the electricity in the U.S. Better or even optimal building energy control and operation strategies provide great opportunities to reduce building energy consumption. Moreover, it is estimated by the National Energy Technology Laboratory that more than one-fourth of the 713 GW of U.S. electricity demand in 2010 could be dispatchable if only buildings could respond to that dispatch through advanced building energy control and operation strategies and smart grid infrastructure. Energy forecasting models for building energy systems are essential to building energy control and operation. Three general categories of building energy forecasting models have been reported in the literature which include white-box (physics-based), black-box (data-driven), and gray-box (combination of physics based and data-driven) modeling approaches. This paper summarizes the existing efforts in this area as well as other critical areas related to building energy modeling, such as short-term weather forecasting. An up-to-date overview of research on application of building energy modeling methods in optimal control for single building and multiple buildings is also summarized in this paper. Different model-based and model-free optimization methods for building energy system operation are reviewed and compared in this paper. Agent based modeling, as a new modeling strategy, has made a remarkable progress in distributed energy systems control and optimization in the past years. The research literature on application of agent based model in building energy system control and operation is also identified and discussed in this paper.