Improving the Control Energy in Model Reference Adaptive Controllers Using Fractional Adaptive Laws

This paper presents the analysis of the control energy consumed in model reference adaptive control(MRAC)schemes using fractional adaptive laws, through simulation studies. The analysis is focused on the energy spent in the control signal represented by means of the integral of the squared control input(ISI). Also, the behavior of the integral of the squared control error(ISE) is included in the analysis.The orders of the adaptive laws were selected by particle swarm optimization(PSO), using an objective function including the ISI and the ISE, with different weighting factors. The results show that, when ISI index is taken into account in the optimization process to determine the orders of adaptive laws,the resulting values are fractional, indicating that control energy of the scheme might be better managed if fractional adaptive laws are used.

Best Tracking Performance under Plant Uncertainty and Control Energy Constraint

This paper has investigated best tracking performance for linear feedback control systems in the case that plant uncertainty and control effort need to be considered simultaneously. Firstly, an average integral square criterion of the tracking error and the plant input energy over a class of additive model errors is defined. Then, utilizing spectral factorization to minimize the performance index, we obtain an optimal controller design method, and furthermore study optimal tracking performance under plant uncertainty and control energy constraint. The results can be used to evaluate optimal average tracking performance and control energy in designing practical control systems.

Autonomous Multi-Factor Energy Flows Controller (AmEFC): Enhancing Renewable Energy Management with Intelligent Control Systems Integration

The transition to sustainable energy systems is one of the defining challenges of our time, necessitating innovations in how we generate, distribute, and manage electrical power. Micro-grids, as localized energy hubs, have emerged as a promising solution to integrate renewable energy sources, ensure energy security, and improve system resilience. The Autonomous multi-factor Energy Flow Controller (AmEFC) introduced in this paper addresses this need by offering a scalable, adaptable, and resilient framework for energy management within an on-grid micro-grid context. The urgency for such a system is predicated on the increasing volatility and unpredictability in energy landscapes, including fluctuating renewable outputs and changing load demands. To tackle these challenges, the AmEFC prototype incorporates a novel hierarchical control structure that leverages Renewable Energy Sources (RES), such as photovoltaic systems, wind turbines, and hydro pumps, alongside a sophisticated Battery Management System (BMS). Its prime objective is to maintain an uninterrupted power supply to critical loads, efficiently balance energy surplus through hydraulic storage, and ensure robust interaction with the main grid. A comprehensive Simulink model is developed to validate the functionality of the AmEFC, simulating real-world conditions and dynamic interactions among the components. The model assesses the system’s reliability in consistently powering critical loads and its efficacy in managing surplus energy. The inclusion of advanced predictive algorithms enables the AmEFC to anticipate energy production and consumption trends, integrating weather forecasting and inter-controller communication to optimize energy flow within and across micro-grids. This study’s significance lies in its potential to facilitate the seamless incorporation of RES into existing power systems, thus propelling the energy sector towards a more sustainable, autonomous, and resilient future. The results underscore the potential of such a system to revolutionize energy management practices and highlight the importance of smart controller systems in the era of smart grids.

A brand new green coating technology for realizing the regulation of spherical propellant energy release process

To achieve the controllable release of energy of nitrocellulose-based propellants,this paper combines the cellulose-based nanocomposites aqueous coating(Surelease®-NC)with fluidized bed coating equipment to successfully prepare the coated spherical propellant for the first time.The effects of fluidized bed coating temperature,air velocity,flow speed and atomization pressure on the adhesion rate,coating integrity and coating uniformity of the coated spherical propellant were investigated,and the preparation of coated spherical propellant with homogeneous size and structural integrity was achieved for the first time.The microscopic morphology,chemical structure,water vapor adsorption behavior,combustion performance,and ageing resistance property of the coated spherical propellant were systematically investigated by,Fourier transforms infrared spectroscopy(FTIR),Micro confocal raman spectrometer,field scanning electron microscopy(SEM),dynamic vapor adsorption techniques,and closed bomb test,confirming the surface core-shell structure and the tightly bonded interfacial structure of coated spherical propellant.Meanwhile,the coated spherical propellant has good hygroscopic,excellent progressive burning and long storage stability.

Minimum Control Energy of Spatial Beam with Assumed Attitude Adjustment Target

The dynamic analysis on the ultra-large spatial structure can be simplified drastically by ignoring the flexibility and damping of the structure.However,these simplifications will result in the erroneous estimate on the dynamic behaviors of the ultra-large spatial structure.Taking the spatial beam as an example,the minimum control energy defined by the difference between the initial total energy and the final total energy in the assumed stable attitude state of the beam is investigated by the structure-preserving method proposed in our previous studies in two cases:the spatial beam considering the flexibility as well as the damping effect,and the spatial beam ignoring both the flexibility and the damping effect.In the numerical experiments,the assumed simulation interval of three months is evaluated on whether or not it is long enough for the spatial flexible damping beam to arrive at the assumed stable attitude state.And then,taking the initial attitude angle and the initial attitude angle velocity as the independent variables,respectively,the minimum control energies of the mentioned two cases are investigated in detail.From the numerical results,the following conclusions can be obtained.With the fixed initial attitude angle velocity,the minimum control energy of the spatial flexible damping beam is higher than that of the spatial rigid beam when the initial attitude angle is close to or far away from the stable attitude state.With the fixed initial attitude angle,ignoring the flexibility and the damping effect will underestimate the minimum control energy of the spatial beam.

Lower bound of tracking performance with finite control energy and channel energy constraint

This paper studies the tracking performance of the single-input single-output （SISO）, finite dimensional, linear and time-invariant （LTI） system over an additive white Gaussian noise （AWGN） channel with finite control energy and channel input energy constraint. A new performance index is proposed which is minimized over all stabilizing two-degree-of-freedom controllers. The explicit expressions of the lower bound of the tracking performance and the minimum of signal-to-noise required are obtained. The results show that the lower bound is correlated to the unstable pole, nonminimum phase zero and the channel scaling factor. Finally, one example is given to validate the conclusions by adopting the special inner-outer factorization.

Analysis of cut vertex in the control of complex networks

The control of complex networks is affected by their structural characteristic. As a type of key nodes in a network structure, cut vertexes are essential for network connectivity because their removal will disconnect the network. Despite their fundamental importance, the influence of the cut vertexes on network control is still uncertain. Here, we reveal the relationship between the cut vertexes and the driver nodes, and find that the driver nodes tend to avoid the cut vertexes.However, driving cut vertexes reduce the energy required for controlling complex networks, since cut vertexes are located near the middle of the control chains. By employing three different node failure strategies, we investigate the impact of cut vertexes failure on the energy required. The results show that cut vertex failures markedly increase the control energy because the cut vertexes are larger-degree nodes. Our results deepen the understanding of the structural characteristic in network control.

Recent progress and application on seismic isolation energy dissipation and control for structures in China

China is a country where 100% of the territory is located in a seismic zone. Most of the strong earthquakes are over prediction. Most fatalities are caused by structural collapse. Earthquakes not only cause severe damage to structures, but can also damage non-structural elements on and inside of facilities. This can halt city life, and disrupt hospitals, airports, bridges, power plants, and other infrastructure. Designers need to use new techniques to protect structures and facilities inside. Isolation, energy dissipation and, control systems are more and more widely used in recent years in China. Currently, there are nearly 6,500 structures with isolation and about 3,000 structures with passive energy dissipation or hybrid control in China. The mitigation techniques are applied to structures like residential buildings, large or complex structures, bridges, underwater tunnels, historical or cultural relic sites, and industrial facilities, and are used for retrofitting of existed structures. This paper introduces design rules and some new and innovative devices for seismic isolation, energy dissipation and hybrid control for civil and industrial structures. This paper also discusses the development trends for seismic resistance, seismic isolation, passive and active control techniques for the future in China and in the world.

Energy control strategy for parallel hydrostatic transmission hybrid vehicles

Aimed at the relatively lower energy density and complicated coordinating operation between two power sources,a special energy control strategy is required to maximize the fuel saving potential.Then a new type of configuration for hydrostatic transmission hybrid vehicles(PHHV) and the selection criterion for important components are proposed.Based on the optimization of planet gear transmission ratio and the analysis of optimal energy distribution for the proposed PHHV on a representative urban driving cycle,a fuzzy torque control strategy and a braking energy regeneration strategy are designed and developed to realize the real-time control of energy for the proposed PHHV.Simulation results demonstrate that the energy control strategy effectively improves the fuel economy of PHHV.

ENERGY ABSORPTION CONTROL CHARACTERISTICS OF AL THIN-WALLED TUBES UNDER IMPACT LOAD

An experimental investigation was carried out to study the energy absorption characteristics of thin-walled square tubes subjected to dynamic crushing by impact loading to develop the optimum structural members. Here, the controller is introduced to improve and control the absorbed energy of thin-walled square tubes in this paper. When the controller were used, the experimental results of crushing of square tubes controlled by the controller＇s elements showed a good candidate for a controllable energy absorption capability in impact crushing.

A New Energy Optimal Control Scheme for a Separately Excited DC Motor Based Incremental Motion Drive

This paper considers minimization of resistive and frictional power dissipation in a separately excited DC motor based incremental motion drive （IMD）. The drive is required to displace a given, fixed load through a definite angle in specified time, with minimum energy dissipation in the motor windings and minimum frictional losses. Accordingly, an energy optimal （EO） control strategy is proposed in which the motor is first accelerated to track a specific speed profile for a pre-determined optimal time period. Thereafter, both armature and field power supplies are disconnected, and the motor decelerates and comes to a halt at the desired displacement point in the desired total displacement time. The optimal time period for the initial acceleration phase is computed so that the motor stores just enough energy to decelerate to the final position at the specified displacement time. The parameters, such as the moment of inertia and coefficient of friction, which depend on the load and other external conditions, have been obtained using system identification method. Comparison with earlier control techniques is included. The results show that the proposed EO control strategy results in significant reduction of energy losses compared to the existing ones.

Energy Management for a Residential Microgrid Using Wavelet Transform and Fuzzy Control Including a Vehicle-to-Grid System

This paper presents the design and implementation of an energy management system （EMS） with wavelet transform and fuzzy control for a residential micro-grid. The hybrid system in this paper consists of a wind turbine generator, photovoltaic （PV） panels, an electric vehicle （EV）, and a super capacitor （SC）, which is able to connect or disconnect to the main grid. The control strategy is responsible for compensating the difference between the generated power by the wind and solar generators and the demanded power by the loads. Wavelet transform decomposes the power difference into a smoothed component and a fast fluctuated component. The command approach used for fuzzy logic rules considers the state of charging （SOC） of EV, renewable production, and the load demand as parameters. Furthermore, the command rules are developed in order to ensure a reliable grid when taking into account the EV battery protection to decide the output power of the EV. The model of the hybrid system is developed in detail under Matlab/Simulink software environment.

Impacts of Total Energy Consumption Control and Energy Quota Allocation on China′s Regional Economy Based on A 30-region Computable General Equilibrium Analysis

This paper examined the impacts of the total energy consumption control policy and energy quota allocation plans on China′s regional economy. This research analyzed the influences of different energy quota allocation plans with various weights of equity and efficiency, using a dynamic computable general equilibrium(CGE) model for 30 province-level administrative regions. The results show that the efficiency-first allocation plan costs the least but widens regional income gap, whereas the outcomes of equity-first allocation plan and intensity target-based allocation plan are similar and are both opposite to the efficiency-first allocation plan′ outcome. The plan featuring a balance between efficiency and equity is more feasible, which can bring regional economic losses evenly and prevent massive interregional migration of energy-related industries. Furthermore, the effects of possible induced energy technology improvements in different energy quota allocation plans were studied. Induced energy technology improvements can add more feasibility to all allocation plans under the total energy consumption control policy. In the long term, if the policy of the total energy consumption control continues and more market-based tools are implemented to allocate energy quotas, the positive consequences of induced energy technology improvements will become much more obvious.

Internet of Things Enabled Intelligent Energy Management and Control System for Heavy Equipment Industrial Park and Fuzzy Assessment of Its Schemes

In order to solve the problems of poor informationflow,low energy utilization rate and energy consumption data reuse in the heavy equipment industrial park,the Internet of Things(IoT)technology is applied to construct the intelligent energy management and control system(IEMCS).The application architecture and function module planning are analyzed and designed.Furthermore,the IEMCS scheme is not unique due to the fuzziness of customer demand and the understanding deviation of designer to customer demand in the design stage.Scheme assessment is of great significance for the normal subsequent implementation of the system.A fuzzy assessment method for IEMCS scheme alternatives is proposed to achieve scheme selection.Fuzzy group decision using triangular fuzzy number to express the vague assessment of experts is adopted to determine the index value.TOPSIS is modified by replacing Euclidean distance with contact vector distance in IEMCS scheme alternative assessment.An experiment with eight IEMCS scheme alternatives in a heavy equipment industrial park is given for the validation.The experiment result shows that eight IEMCS scheme alternatives can be assessed.Through the comparisons with other methods,the reliability of the results obtained by the proposed method is discussed.

Guest Editorial for Special Issue on Control and Optimization in Renewable Energy Systems

I.I NTRODUCTION W ITH the advent of low-carbon economy,there has been a growing interest in harnessing renewable energy resources particularly for electricity generation.Renewable energy resources are advocated for the economic and environ-

Low Carbon Building Design Optimization Based on Intelligent Energy Management System

The construction of relevant standards for building carbon emission assessment in China has just started,and the quantitative analysis method and evaluation system are still imperfect,which hinders the development of low-carbon building design.Therefore,the use of intelligent energy management system is very necessary.The purpose of this paper is to explore the design optimization of low-carbon buildings based on intelligent energy management systems.Based on the proposed quantitative method of building carbon emission,this paper establishes the quota theoretical system of building carbon emission analysis,and develops the quota based carbon emission calculation software.Smart energy management system is a low-carbon energy-saving system based on the reference of large-scale building energy-saving system and combined with energy consumption.It provides a fast and effective calculation tool for the quantitative evaluation of carbon emission of construction projects,so as to realize the carbon emission control and optimization in the early stage of architectural design and construction.On this basis,the evaluation,analysis and calculation method of building structure based on carbon reduction target is proposed,combined with the carbon emission quota management standard proposed in this paper.Taking small high-rise residential buildings as an example,this paper compares and analyzes different building structural systems from the perspectives of structural performance,economy and carbon emission level.It provides a reference for the design and evaluation of low-carbon building structures.The smart energy management system collects user energy use parameters.It uses time period and time sequence to obtain a large amount of data for analysis and integration,which provides users with intuitive energy consumption data.Compared with the traditional architectural design method,the industrialized construction method can save 589.22 megajoules(MJ)per square meter.Based on 29270 megajoules(MJ)per ton of standard coal,the construction area of the case is about 8000 m2,and the energy saving of residential buildings is 161.04 tons of standard coal.This research is of great significance in reducing the carbon emission intensity of buildings.

Energy Efficiency Optimization for D2D Communications Based on SCA and GP Method

In this paper, we propose an energy-efficient power control scheme for device-to-device(D2D) communications underlaying cellular networks, where multiple D2D pairs reuse the same resource blocks allocated to one cellular user. Taking the maximum allowed transmit power and the minimum data rate requirement into consideration, we formulate the energy efficiency maximization problem as a non-concave fractional programming(FP) problem and then develop a two-loop iterative algorithm to solve it. In the outer loop, we adopt Dinkelbach method to equivalently transform the FP problem into a series of parametric subtractive-form problems, and in the inner loop we solve the parametric subtractive problems based on successive convex approximation and geometric programming method to obtain the solutions satisfying the KarushKuhn-Tucker conditions. Simulation results demonstrate the validity and efficiency of the proposed scheme, and illustrate the impact of different parameters on system performance.

Fully Decoupled Branch Energy Balancing Control Method for Modular Multilevel Matrix Converter Based on Sequence Circulating Components

The modular multilevel matrix converter(M3C)is a potential frequency converter for low-frequency AC transmission.However,capacitor voltage control of high-voltage and largecapacity M3C is more difficult,especially for voltage balancing between branches.To solve this problem,this paper defines sequence circulating components and theoretically analyzes the influence mechanism of different sequence circulating components on branch capacitor voltage.A fully decoupled branch energy balancing control method based on four groups of sequence circulating components is proposed.This method can control capacitor voltages of nine branches in horizontal,vertical and diagonal directions.Considering influences of both circulating current and voltage,a cross decoupled control is designed to improve control precision.Simulation results are taken from a low-frequency transmission system based on PSCAD/EMTDC,and effectiveness and precision of the proposed branch energy balancing control method are verified in the case of nonuniform parameters and an unbalanced power system.

Power-balancing Instantaneous Optimization Energy Management for a Novel Series-parallel Hybrid Electric Bus

Energy management（EM） is a core technique of hybrid electric bus（HEB） in order to advance fuel economy performance optimization and is unique for the corresponding configuration. There are existing algorithms of control strategy seldom take battery power management into account with international combustion engine power management. In this paper, a type of power-balancing instantaneous optimization（PBIO） energy management control strategy is proposed for a novel series-parallel hybrid electric bus. According to the characteristic of the novel series-parallel architecture, the switching boundary condition between series and parallel mode as well as the control rules of the power-balancing strategy are developed. The equivalent fuel model of battery is implemented and combined with the fuel of engine to constitute the objective function which is to minimize the fuel consumption at each sampled time and to coordinate the power distribution in real-time between the engine and battery. To validate the proposed strategy effective and reasonable, a forward model is built based on Matlab/Simulink for the simulation and the dSPACE autobox is applied to act as a controller for hardware in-the-loop integrated with bench test. Both the results of simulation and hardware-in-the-loop demonstrate that the proposed strategy not only enable to sustain the battery SOC within its operational range and keep the engine operation point locating the peak efficiency region, but also the fuel economy of series-parallel hybrid electric bus（SPHEB） dramatically advanced up to 30.73% via comparing with the prototype bus and a similar improvement for PBIO strategy relative to rule-based strategy, the reduction of fuel consumption is up to 12.38%. The proposed research ensures the algorithm of PBIO is real-time applicability, improves the efficiency of SPHEB system, as well as suite to complicated configuration perfectly.

Self-adapting radiation control method for RFS in tracking

The aim of this paper is to achieve the radio frequency stealth(RFS) during the course of tracking by controlling the radiation energy and the interval of a radar. Firstly, we build the model of probability of interception with the once radiation during the course of tracking. Secondly, we establish the model of the cumulative probability of interception to describe the effect of RFS throughout the tracking process and obtain two solutions that are minimizing the probability of interception and the radiation times to reduce the cumulative probability of interception. Thirdly, we propose a self-adapting radiation energy control method(SARE)to minimize the probability of interception. Fourthly, we propose a self-adapting radiation interval control method(SARI) to minimize radiation times. Fifthly, combining SARE with SARI, we propose a SARE-SARI control method(SAEI) during the course of tracking.Finally, we compare SAEI with two others by simulation, and the results show the effect of RFS of SAEI is better than the other two,but we have to make a trade-off between the ability of RFS and the effect of tracking.