Robust Tracking Control for Self-balancing Mobile Robots Using Disturbance Observer

In this paper,a robust tracking control scheme based on nonlinear disturbance observer is developed for the self-balancing mobile robot with external unknown disturbances.A desired velocity control law is firstly designed using the Lyapunov analysis method and the arctan function.To improve the tracking control performance,a nonlinear disturbance observer is developed to estimate the unknown disturbance of the self-balancing mobile robot.Using the output of the designed disturbance observer,the robust tracking control scheme is presented employing the sliding mode method for the selfbalancing mobile robot.Numerical simulation results further demonstrate the effectiveness of the proposed robust tracking control scheme for the self-balancing mobile robot subject to external unknown disturbances.

Review of the Tuned Mass Damper Inerter(TMDI)in Energy Harvesting and Vibration Control:Designs,Analysis and Applications

Tuned mass damper inerter(TMDI)is a device that couples traditional tuned mass dampers(TMD)with an inertial device.The inertial device produces resistance proportional to the relative acceleration at its two ends through its“inertial”constant.Due to its unique mechanical properties,TMDI has received widespread attention and application in the past twenty years.As different configurations are required in different practical situations,TMDI is still active in the research on vibration control and energy harvesting in structures.This paper provides a comprehensive review of the research status of TMDI.This work first examines the generation and important vibration control characteristics of TMDI.Then,the energy harvesting performance of electromagnetic tuned mass damper inerter(EM-TMDI)is discussed.This work emphasizes the formation of a passive dynamic vibration absorber by coupling traditional TMD with inertial devices.This paper also summarizes the design and implementation of optimal vibration control and energy harvesting for TMDI.Furthermore,this paper details the applications of TMDI in the fields of bridges and building engineering.Finally,this paper summarizes the necessity of research on tuned mass-damper-inertia,the challenges faced currently,and future research directions,such as control of parameters in electromagnetic energy harvesting TMDI systems and low-cost TMDI.

Intelligent Fractional-Order Controller for SMES Systems in Renewable Energy-Based Microgrid

An autonomous microgrid that runs on renewable energy sources is presented in this article.It has a supercon-ducting magnetic energy storage(SMES)device,wind energy-producing devices,and an energy storage battery.However,because such microgrids are nonlinear and the energy they create varies with time,controlling and managing the energy inside them is a difficult issue.Fractional-order proportional integral(FOPI)controller is recommended for the current research to enhance a standalone microgrid’s energy management and performance.The suggested dedicated control for the SMES comprises two loops:the outer loop,which uses the FOPI to regulate the DC-link voltage,and the inner loop,responsible for regulating the SMES current,is constructed using the intelligent FOPI(iFOPI).The FOPI+iFOPI parameters are best developed using the dandelion optimizer(DO)approach to achieve the optimum performance.The suggested FOPI+iFOPI controller’s performance is contrasted with a conventional PI controller for variations in wind speed and microgrid load.The optimal FOPI+iFOPI controller manages the voltage and frequency of the load.The behavior of the microgrid as a reaction to step changes in load and wind speed was measured using the proposed controller.MATLAB simulations were used to evaluate the recommended system’s performance.The results of the simulations showed that throughout all interruptions,the recommended microgrid provided the load with AC power with a constant amplitude and frequency.In addition,the required load demand was accurately reduced.Furthermore,the microgrid functioned incredibly well despite SMES and varying wind speeds.Results obtained under identical conditions were compared with and without the best FOPI+iFOPI controller.When utilizing the optimal FOPI+iFOPI controller with SMES,it was found that the microgrid performed better than the microgrid without SMES.

Performance enhancement of a viscoelastic bistable energy harvester using time-delayed feedback control

This paper focuses on the stochastic analysis of a viscoelastic bistable energy harvesting system under colored noise and harmonic excitation, and adopts the time-delayed feedback control to improve its harvesting efficiency. Firstly, to obtain the dimensionless governing equation of the system, the original bistable system is approximated as a system without viscoelastic term by using the stochastic averaging method of energy envelope, and then is further decoupled to derive an equivalent system. The credibility of the proposed method is validated by contrasting the consistency between the numerical and the analytical results of the equivalent system under different noise conditions. The influence of system parameters on average output power is analyzed, and the control effect of the time-delayed feedback control on system performance is compared. The output performance of the system is improved with the occurrence of stochastic resonance(SR). Therefore, the signal-to-noise ratio expression for measuring SR is derived, and the dependence of its SR behavior on different parameters is explored.

Identification of time-varying system and energy-based optimization of adaptive control in seismically excited structure

The combination of structural health monitoring and vibration control is of great importance to provide components of smart structures.While synthetic algorithms have been proposed,adaptive control that is compatible with changing conditions still needs to be used,and time-varying systems are required to be simultaneously estimated with the application of adaptive control.In this research,the identification of structural time-varying dynamic characteristics and optimized simple adaptive control are integrated.First,reduced variations of physical parameters are estimated online using the multiple forgetting factor recursive least squares(MFRLS)method.Then,the energy from the structural vibration is simultaneously specified to optimize the control force with the identified parameters to be operational.Optimization is also performed based on the probability density function of the energy under the seismic excitation at any time.Finally,the optimal control force is obtained by the simple adaptive control(SAC)algorithm and energy coefficient.A numerical example and benchmark structure are employed to investigate the efficiency of the proposed approach.The simulation results revealed the effectiveness of the integrated online identification and optimal adaptive control in systems.

Adaptive linear active disturbance-rejection control strategy reduces the impulse current of compressed air energy storage connected to the grid

The merits of compressed air energy storage(CAES)include large power generation capacity,long service life,and environmental safety.When a CAES plant is switched to the grid-connected mode and participates in grid regulation,using the traditional control mode with low accuracy can result in excess grid-connected impulse current and junction voltage.This occurs because the CAES output voltage does not match the frequency,amplitude,and phase of the power grid voltage.Therefore,an adaptive linear active disturbance-rejection control(A-LADRC)strategy was proposed.Based on the LADRC strategy,which is more accurate than the traditional proportional integral controller,the proposed controller is enhanced to allow adaptive adjustment of bandwidth parameters,resulting in improved accuracy and response speed.The problem of large impulse current when CAES is switched to the grid-connected mode is addressed,and the frequency fluctuation is reduced.Finally,the effectiveness of the proposed strategy in reducing the impact of CAES on the grid connection was verified using a hardware-in-the-loop simulation platform.The influence of the k value in the adaptive-adjustment formula on the A-LADRC was analyzed through simulation.The anti-interference performance of the control was verified by increasing and decreasing the load during the presynchronization process.

Multi-Time Scale Optimal Scheduling of a Photovoltaic Energy Storage Building System Based on Model Predictive Control

Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.

The Development of Self-Balancing Controller for One-Wheeled Vehicles

The purpose of this study is to develop a self-balancing controller (SBC) for one-wheeled vehicles (OWVs). The composition of the OWV system includes: a DSP motion card, a wheel motor, and its driver. In addition, a tilt and a gyro, for sensing the angle and angular velocity of the body slope, are used to realize self-balancing controls. OWV, a kind of unicycle robot, can be dealt with as a mobile-inverted-pendulum system for its instability. However, for its possible applications in mobile carriers or robots, it is worth being further developed. In this study, first, the OWV system model will be derived. Next, through the simulations based on the mathematical model, the analysis of system stability and controllability can be evaluated. Last, a concise and realizable method, through system pole-placement and linear quadratic regulator (LQR), will be proposed to design the SBC. The effectiveness, reliability, and feasibility of the proposal will be con- firmed through simulation studies and experimenting on a physical OWV.

Research on Self-balancing Two Wheels Mobile Robot Control System Analysis

The paper presents the research on self-balancing two-wheels mobile robot control system analysis with experimental studies.The research problem in this work is to stabilize the mobile robot with self-control and to carry the sensitive things without failing in a long span period.The main objective of this study is to focus on the mathematical modelling of mobile robot from laboratory scale to real world applications.The numerical expression with mathematical modelling is very important to control the mobile robot system with linearization.The fundamental concepts of dynamic system stability were utilized for maintaining the stability of the constructed mobile robot system.The controller design is also important for checking the stability and the appropriate controller design is proportional,integral,and derivative-PID controller and Linear Quadratic Regulator(LQR).The steady state error could be reduced by using such kind of PID controller.The simulation of numerical expression on mathematical modeling was conducted in MATLAB environments.The confirmation results from the simulation techniques were applied to construct the hardware design of mobile robot system for practical study.The results from simulation approaches and experimental approaches are matched in various kinds of analyses.The constructed mobile robot system was designed and analyzed in the control system design laboratory of Yangon Technological University(YTU).

Optimal control of wireless energy transfer system via decreasing frequency

In order to solve the multiple power extreme value point problem caused by system frequency splitting during wireless energy transmission at short distances a transmission model of the system is established.With the comprehensive consideration of the resonance frequency load parameters and the coupling between coils the internal factors of frequency splitting and boundary conditions are discussed.The results show that under the condition of the fixed load the higher the natural resonance frequency the easier the frequency splitting. As the frequency splitting occurs the frequency of the maximum power transfer is no longer with the natural resonance frequency which can make the system unstable and the transfer power more difficult to control. Therefore a decreasing-frequency method is proposed to avoid the system frequency splitting. And decreasing the system resonance frequency can make the system successfully withdraw the frequency splitting area at a short-distance range.Under the fixed load condition the transmission power of the system can be increased by 400% and the transmission efficiency is reduced by only 14% which greatly improves the transmission performance of the system.

Bias Momentum Attitude Control System Using Energy/Momentum Wheels

The integrated power and attitude control for a bias momentum attitudecontrol system is investigated. A pair of counter-spinning wheels is used to provide the biasangular momentum and store/ discharge energy for power requirement of the devices on the spacecraft.The roll/yaw motion is controlled by pitch magnetic dipole moment. The torque-based control law ofthe wheels is designed, so that the desired pitch control torque is provided and the operation ofcharging/discharging energy is carried out based on the given power. System singularity in thecontrol law of wheels is fully avoided by keeping the wheels counter-spinning. A power managementscheme using kinetic energy feedback is proposed to keep energy balance, which can avoid wheelsaturation caused by superfluous energy. The minimum moment of inertia of the wheels is limited bythe maximum bias angular momentum and the minimum energy, such constrains are analyzed incombination with the geometrical method. Numerical simulation results are presented to demonstratethe effectiveness of the control scheme.

A PSO based Energy Efficient Coverage Control Algorithm for Wireless Sensor Networks

Wireless Sensor Networks(WSNs)are large-scale and high-density networks that typically have coverage area overlap.In addition,a random deployment of sensor nodes cannot fully guarantee coverage of the sensing area,which leads to coverage holes in WSNs.Thus,coverage control plays an important role in WSNs.To alleviate unnecessary energy wastage and improve network performance,we consider both energy efficiency and coverage rate for WSNs.In this paper,we present a novel coverage control algorithm based on Particle Swarm Optimization(PSO).Firstly,the sensor nodes are randomly deployed in a target area and remain static after deployment.Then,the whole network is partitioned into grids,and we calculate each grid’s coverage rate and energy consumption.Finally,each sensor nodes’sensing radius is adjusted according to the coverage rate and energy consumption of each grid.Simulation results show that our algorithm can effectively improve coverage rate and reduce energy consumption.

Distributed Power Control for Energy Conservation in Hybrid Cellular Network with Device-to-Device Communication

Device-to-Device(D2D) communication has been proposed as a promising implementation of green communication to benefit the existed cellular network.In order to limit cross-tier interference while explore the gain of short-range communication,we devise a series of distributed power control(DPC) schemes for energy conservation(EC)and enhancement of radio resource utilization in the hybrid system.Firstly,a constrained opportunistic power control model is built up to take advantage of the interference avoidance methodology in the presence of service requirement and power constraint.Then,biasing scheme and admission control are added to evade ineffective power consumption and maintain the feasibility of the system.Upon feasibility,a non-cooperative game is further formulated to exploit the profit in EC with minor influence on spectral efficiency(SE).The convergence of the DPC schemes is validated and their performance is confirmed via simulation results.

Simulation on a Car Interior Aerodynamic Noise Control Based on Statistical Energy Analysis

How to simulate interior aerodynamic noise accurately is an important question of a car interior noise reduction. The unsteady aerodynamic pressure on body surfaces is proved to be the key effect factor of car interior aerodynamic noise control in high frequency on high speed. In this paper, a detail statistical energy analysis （SEA） model is built. And the vibra-acoustic power inputs are loaded on the model for the valid result of car interior noise analysis. The model is the solid foundation for further optimization on car interior noise control. After the most sensitive subsystems for the power contribution to car interior noise are pointed by SEA comprehensive analysis, the sound pressure level of car interior aerodynamic noise can be reduced by improving their sound and damping characteristics. The further vehicle testing results show that it is available to improve the interior acoustic performance by using detailed SEA model, which comprised by more than 80 subsystems, with the unsteady aerodynamic pressure calculation on body surfaces and the materials improvement of sound/damping properties. It is able to acquire more than 2 dB reduction on the central frequency in the spectrum over 800 Hz. The proposed optimization method can be looked as a reference of car interior aerodynamic noise control by the detail SEA model integrated unsteady computational fluid dynamics （CFD） and sensitivity analysis of acoustic contribution.

A Clustering-tree Topology Control Based on the Energy Forecast for Heterogeneous Wireless Sensor Networks

How to design an energy-efficient algorithm to maximize the network lifetime in complicated scenarios is a critical problem for heterogeneous wireless sensor networks (HWSN). In this paper, a clustering-tree topology control algorithm based on the energy forecast (CTEF) is proposed for saving energy and ensuring network load balancing, while considering the link quality, packet loss rate, etc. In CTEF, the average energy of the network is accurately predicted per round (the lifetime of the network is denoted by rounds) in terms of the difference between the ideal and actual average residual energy using central limit theorem and normal distribution mechanism, simultaneously. On this basis, cluster heads are selected by cost function (including the energy, link quality and packet loss rate) and their distance. The non-cluster heads are determined to join the cluster through the energy, distance and link quality. Furthermore, several non-cluster heads in each cluster are chosen as the relay nodes for transmitting data through multi-hop communication to decrease the load of each cluster-head and prolong the lifetime of the network. The simulation results show the efficiency of CTEF. Compared with low-energy adaptive clustering hierarchy (LEACH), energy dissipation forecast and clustering management (EDFCM) and efficient and dynamic clustering scheme (EDCS) protocols, CTEF has longer network lifetime and receives more data packets at base station. © 2014 Chinese Association of Automation.

Decentralized Control for Residential Energy Management of a Smart Users' Microgrid with Renewable Energy Exchange

This paper presents a decentralized control strategy for the scheduling of electrical energy activities of a microgrid composed of smart homes connected to a distributor and exchanging renewable energy produced by individually owned distributed energy resources. The scheduling problem is stated and solved with the aim of reducing the overall energy supply from the grid, by allowing users to exchange the surplus renewable energy and by optimally planning users' controllable loads. We assume that each smart home can both buy/sell energy from/to the grid taking into account time-varying non-linear pricing signals. Simultaneously, smart homes cooperate and may buy/sell locally harvested renewable energy from/to other smart homes. The resulting optimization problem is formulated as a non-convex non-linear programming problem with a coupling of decision variables in the constraints. The proposed solution is based on a novel heuristic iterative decentralized scheme algorithm that suitably extends the Alternating Direction Method of Multipliers to a non-convex and decentralized setting. We discuss the conditions that guarantee the convergence of the presented algorithm. Finally, the application of the proposed technique to a case study under several scenarios shows its effectiveness.

Distributed Cooperative Control of Battery Energy Storage Systems in DC Microgrids

The control of battery energy storage systems(BESSs)plays an important role in the management of microgrids.In this paper,the problem of balancing the state-ofcharge(SoC)of the networked battery units in a BESS while meeting the total charging/discharging power requirement is formulated and solved as a distributed control problem.Conditions on the communication topology among the battery units are established under which a control law is designed for each battery unit to solve the control problem based on distributed average reference power estimators and distributed average unit state estimators.Two types of estimators are proposed.One achieves asymptotic estimation and the other achieves finite time estimation.We show that,under the proposed control laws,SoC balancing of all battery units is achieved and the total charging/discharging power of the BESS tracks the desired power.A simulation example is shown to verify the theoretical results.

Power Maximization of A Point Absorber Wave Energy Converter Using Improved Model Predictive Control

This paper considers controlling and maximizing the absorbed power of wave energy converters for irregular waves. With respect to physical constraints of the system, a model predictive control is applied. Irregular waves’ behavior is predicted by Kalman filter method. Owing to the great influence of controller parameters on the absorbed power, these parameters are optimized by imperialist competitive algorithm. The results illustrate the method’s efficiency in maximizing the extracted power in the presence of unknown excitation force which should be predicted by Kalman filter.

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.

Optimized model-based control of main mine ventilation air flows with minimized energy consumption

In early 2018,the Boliden Garpenberg operation implemented an optimized control strategy as an addition to the existing ventilation on demand system.The purpose of the strategy is to further minimize energy use for main and booster fans,whilst also fulfilling airflow setpoints without violating constraints such as min/max differential pressure over fans and interaction of air between areas in mines.Using air flow measurements and a dynamical model of the ventilation system,a mine-wide coordination control of fans can be carried out.The numerical model is data driven and derived from historical operational data or step changes experiments.This makes both initial deployment and lifetime model maintenance,as the mine evolves,a comparably easy operation.The control has been proven to operate in a stable manner over long periods without having to re-calibrate the model.Results prove a 40%decrease in energy use for the fans involved and a greater controllability of air flow.Moreover,a 15%decrease of the total air flow into the mine will give additional proportional heating savings during winter periods.All in all,the multivariable controller shows a correlation between production in the mine and the ventilation system performance superior to all of its predecessors.