Steady-state Deviation Research Articles

Research on 4WS Agricultural Machine Path Tracking Algorithm Based on Fuzzy Control Pure Tracking Model

This paper presents a path tracking algorithm based on a fuzzy control pure tracking model for autonomous navigation of 4WS agricultural machines. The aim of this research is to implement path tracking for unmanned 4WS agricultural machinery and to solve the problem of difficult determination of forward-looking distances in pure tracking algorithms. By using the pure tracking algorithm model and a fuzzy controller, this paper converts the heading deviation and lateral deviation in one control cycle into the sum of lateral deviation as the first input to the fuzzy controller and the vehicle travel speed as the second input to the fuzzy controller, thus outputting the actual forward-looking distance. In order to verify the practicality, accuracy, and path tracking precision of the proposed path tracking algorithm, a straight-line path tracking test under variable speed conditions and a turning path tracking test under non-fixed forward-looking distance conditions were carried out using a test platform after simulation on MATLAB/Simulink in this paper. The test results show that: in the straight-line path tracking process, the maximum overshoot is 0.123 m, and after stable driving, the maximum lateral deviation of the straight-line tracking part is 0.058 m and the steady-state deviation is 0.039 m; in the bow-turn path tracking process, the absolute value of the maximum lateral deviation of the actual driving trajectory of the farm machine from the desired path is 0.139 m, and the average tracking deviation is 0.041 m. It can be seen that the path tracking control algorithm proposed in this paper has good tracking accuracy as well as convergence, and can meet the demand for the autonomous navigation function of 4WS agricultural machinery, which has a certain application value.

Alterations in the intrinsic discharge activity of CA1 pyramidal neurons associated with possible changes in the NADPH diaphorase activity in a rat model of autism induced by prenatal exposure to valproic acid

Autism spectrum disorder is a neurodevelopmental disorder characterized by sensory abnormalities, social skills impairment and cognitive deficits. Although recent evidence indicated that induction of autism-like behavior in animal models causes abnormal neuronal excitability, the impact of autism on neuronal properties is still an important issue. Thus, new findings at the cellular level may shed light on the pathophysiology of autism and may help to find effective treatment strategies. Here, we investigated the behavioral, electrophysiological and histochemical impacts of prenatal exposure to valproic acid (VPA) in rats. Findings revealed that VPA exposure caused a significant increase in the hot plate response latency. The novel object recognition ability was also impaired in VPA-exposed rats. Along with these behavioral alterations, neurons from VPA-exposed animals exhibited altered excitability features in response to depolarizing current injections relative to control neurons. In the VPA-exposed group, these changes consisted of a significant increase in the amplitude, evoked firing frequency and the steady-state standard deviation of spike timing of action potentials (APs). Moreover, the half-width, the AHP amplitude and the decay time constant of APs were significantly decreased in this group. These changes in the evoked electrophysiological properties were accompanied by intrinsic hyperexcitability and lower spike-frequency adaptation and also a significant increase in the number of NADPH-diaphorase stained neurons in the hippocampal CA1 area of the VPA-exposed rats. Taken together, findings demonstrate that abnormal nociception and recognition memory is associated with alterations in the neuronal responsiveness and nitrergic system in a rat model of autism-like.

Enhanced DC Voltage Regulation and Transient Response for Multi-Terminal VSC-HVDC System Using Direct Power Control

This paper presents a new control strategy for enhancing the dc voltage regulation and the transient response in the multi-terminal VSC-HVDC system by ensuring swift power-sharing among converters when encountering large disturbance such as converter loss or ac fault at one of the converter stations. The quick power sharing can be realized using direct power control (DPC) since it has a merit of fast power dynamic response. On the other hand, to limit the converter current during ac fault, a new coordination strategy between DPC and vector current control (VCC) is proposed. Furthermore, a new simplified model of the MTDC system is developed to study the performance of DPC in enhancing the dc voltage dynamics response analytically. The time-domain simulation of the detailed model of the four converter stations MTDC system verify that the proposed control strategy significantly reduces the overshoot in the transient dc voltage response following an outage or ac fault. As a result, together with the droop gain selection for the maximum permissible steady-state dc voltage deviation, the proposed control strategy can help to reduce the size of the dc chopper in the MTDC grid or even avoiding it. Moreover, the comparative analysis based on time-domain simulation depicts that the proposed simplified model has the same dc voltage response compared to the detailed model of the MTDC system except for a steady-state error of 0.47% and a little bit longer settling time (1.5 ms) at transient.

Research on Frequency Response Modeling and Frequency Modulation Parameters of the Power System Highly Penetrated by Wind Power

Renewable energy units led by wind power participate in diversified control primary frequency modulation, making the frequency response modes and the setting of frequency modulation parameters more complex. This paper proposes a frequency response model of the power system which is highly penetrated by wind power based on the two mainstream control strategies of wind power that participate in primary frequency modulation. The model considers the influence of wind capture devices, maximum power point tracking (MPPT), and other complex control strategies on system frequency response. Based on this model, the calculation formulas of the maximum change rate of dynamic frequency, the lowest point of dynamic frequency, and the maximum steady-state frequency deviation of the system after fault disturbance are derived in the frequency domain. The influences of wind power permeability and two typical frequency response control strategies on system frequency stability are analyzed. On the one hand, it is found that the proposed model can fit the system frequency response better than the traditional system frequency response model. Beyond that, two control strategies are mainly aimed at the different frequency stability requirements. On the other hand, under the condition of meeting the system’s stability requirements, the paper calculates the control parameters of frequency response of the doubly-fed induction generator (DFIG). The time-domain simulation model of the improved IEEE three-machine nine-node system and IEEE 39-node system with high permeability of wind power are built. Through the different fault scenarios, the simulation results verify the effectiveness of the proposed model and the accuracy of control strategy parameter calculation.

An Effective Temperature Control Method for Dividing-Wall Distillation Columns

Temperature control is widely perceived to be superior to direct composition control for the control of dividing-wall distillation columns (DWDCs) due to its advantages in dynamic characteristics. However, because of the limited estimation accuracy to the controlled product purities, the former cannot eliminate the steady-state errors in the maintained product purities as completely as the latter. In order to reduce the steady-state deviations in the maintained product purities, an effective temperature control method is proposed in the current article by means of a kind of simple but effective product quality estimator (PQE). For the proposed PQE, temperatures of three stages located in the controlled column section (TI1, TI2, and TI3) are employed as inputs, and a linear sum of these three inputted stage temperatures (α × TI1 + β × TI2 + γ × TI3) is given as output. A genetic algorithm with an elitist preservation strategy is used to optimize the locations of the three stage temperatures and the values of α, β, and γ to ensure the estimation accuracy of the PQE. Concerning the controls of two DWDCs, i.e., one Petlyuk DWDC separating an ethanol/propanol/butanol ternary mixture and one Kaibel DWDC separating a methanol/ethanol/propanol/butanol quaternary mixture, the effectiveness of the PQE is assessed through comparing the performance of the temperature inferential control scheme using the PQE and the double temperature difference control scheme. According to the dynamic simulation results obtained, the former control scheme displays not only smaller steady-state deviations in the maintained product purities, but also better dynamic characteristics as compared with the latter control scheme. This result fully demonstrates that the proposed PQE can be a useful tool for the temperature inferential control of the DWDC.

Accurate Distributed Secondary Control for DC Microgrids Considering Communication Delays: A Surplus Consensus-Based Approach

The state-of-the-art dynamic consensus-based microgrid (MG) secondary controls suffer from the communication delay effect. Specifically, the system could not converge to the desired operating points with time-delayed communications. Such deviations are hard to detect in a decentralized manner and could destabilize the system. This paper proposes an accurate distributed secondary controller for DC MGs based on the surplus consensus algorithm. The proposed controller achieves accurate proportional power sharing and average voltage regulation among distributed generators (DGs) with the presence of variable and bounded communication delays. A surplus consensus-based observer is developed. The developed observer is proved robust against variable and bounded communication delays; it tracks the average of a group of dynamic states with zero steady-state deviations, which cannot be done using the conventional dynamic consensus-based observer. The convergence speed of the developed observer is analyzed and a parameter design procedure is presented. Moreover, the delay-dependent stability analysis of DC MG operation with the proposed secondary controller is derived. The marginal delay that leads the system to instability is calculated. At last, the performance of the proposed secondary controller and the developed stability analysis are validated under various scenarios using MATLAB/Simulink.

Adaptive Deep-Learning-Based Steady-State Modeling and Fast Control Strategy for CLLC DC-DC Converter in Highly Renewable Penetrated System

The CLLC DC-DC converter offers highly efficient DC voltage conversion for the highly renewable penetrated system. The modeling significantly influences the performance of CLLC DC-DC converters. However, both the current FHA-based and time-domain analysis methods are incapable to incorporate different switching frequencies and load conditions. Moreover, due to the inevitable non-monotonic voltage gain, the PI controller with these models leads to the uncontrolled steady-state voltage deviation. As a novel modeling method, deep learning implicitly builds extensively accurate and arbitrary mappings, which can solve the aforementioned modeling problems. This paper proposes an adaptive steady-state modeling method for the CLLC converter based on deep learning. Precise voltage gain can be provided over a wide range of switching frequencies and load conditions. Besides, a fast control strategy based on the proposed modeling method is developed. This strategy searches the optimal operating point using particle swarm optimization, which rapidly adjusts voltage gain and suppresses the steady-state voltage deviation even in non-monotonic situations. Finally, a 400V/300V, 2.4kW SiC-based CLLC converter prototype with distributed heterogeneous controllers is implemented to verify the proposed methods. The experimental results show the accuracy of the proposed adaptive modeling and the effectiveness of the fast control strategy. The proposed method improves the stability and extends the operating range of the CLLC converter, which benefits the development of highly renewable penetrated systems.

Оптимальне керування режимами розподільних електричних мереж з сонячними електростанціями при несиметричному навантаженні

The article is devoted to improving the system of automatic control of modes of distribution electric networks containing solar power plants in order to achieve a simultaneous reduction of steady-state voltage deviations, voltage asymmetry at the terminals of consumers while maximizing the level of electricity generation by solar power plants. Ensuring normal permissible levels of electricity quality indicators in distribution networks is one of the most pressing issues that arise in the design and operation of modern distribution networks. Deterioration of the quality of electricity in electrical networks leads to the appearance of such negative phenomena, increase in additional losses in the elements of the electrical network, reduce the service life of electrical equipment, reduce the productivity of production equipment and others. The most significant negative impact on the functioning of the elements of electrical distribution networks, including electricity consumers, is observed with increasing levels of steady-state deviation and voltage asymmetry above the normative values. Modern solar inverters allow you to control the level of steady voltage deviation at the point of their connection to the mains. The design features of the construction of inverters of solar power plants allow them to change (within certain limits) not only the level of steady-state voltage deviation, but also to affect the level of voltage asymmetry and the parameters of the reactive power mode. In view of this, the task of improving automatic control systems for the distribution of electric networks with solar power plants, the implementation of which will take into account the multifunctional influence of solar inverters on the parameters of these networks is quite relevant. For the research, a fragment of a typical distribution electrical network with a nominal voltage of 10 kV was used, which contains a solar power plant that connects directly to the 10 kV busbars. The authors of the article set the problem of controlling the parameters of the mode of distribution electric network with solar power plants in the form of the problem of multicriteria optimization. An approach to solving this problem is also proposed, which is based on the method of solving problems of multicriteria optimization by approaching the utopian point in the space of criteria. Approximate calculations are carried out, which confirm the possibility of applying the proposed approach to the construction of systems for automatic control of the parameters of the mode of distribution electrical networks with solar power plants

Study on Reward Multidimensionality in Deep Reinforcement Learning of Spherical Synchronous Actuators

The spherical synchronous actuator can be driven in multiple-degrees-of-freedom by a single unit. This simplifies the mechanism and is expected to be applied to industrial robots. The position of the actuator is controlled using a torque map which is a torque data at each posture. However, there is a problem that the positional accuracy is degraded by measurement errors in the torque map and friction. To solve this problem, we propose a novel attitude control system for the spherical actuator using a deep reinforcement learning algorithm. The simulation results showed that the control system was successfully implemented without a torque map. The system was able to follow the step response within 0.1 seconds, and the steady-state deviation was less than 0.1 degrees.

A rolling optimization method of reserve capacity considering wind power frequency control

Wind power participating in frequency control with reserve capacity is an inevitable requirement for the system with a high proportion of wind power in the future. The existing reserve allocation methods, which consider the wind farm frequency control with reserve often only considered the economy or efficiency of the wind farm to set reserve capacity in fixed percentage, failed to follow the principle of optimal system efficiency and cannot optimize the system frequency regulation economy and frequency stability at the same time. The proposed method from the perspective of the system allocates reserve capacity among wind power, thermal power, and hydropower, who participate in system frequency control. Multi-objective chance constrained programming takes the economy and frequency stability as the optimization objectives. A rolling optimization method of reserve capacity is carried out periodically according to fluctuating wind power and load, making the calculation results in real time. A hybrid intelligent algorithm is adopted to improve the calculation efficiency. The simulation in the IEEE 39-bus test network shows that the proposed method can effectively improve the frequency control effect and system economy. Compared with the reserve allocation method considering wind farm participating in frequency control with reserve capacity in fixed percentage, the proposal can at most reduce the RoCoF by 9.5%, the maximum frequency deviation by 4.3%, and the steady-state frequency deviation by 4.1%, and when the system frequency stability is the only objective, at most 79.4% coal consumption reserve cost in the system can be saved.

Fast Frequency Support from Grid-forming Converters Under dc- and ac-side Current Limits

A decentralized nonlinear feedback controller is proposed for droop-based grid-forming converters (GFCs) with both dc-side current limitation and ac-side current limit to provide fast frequency support from renewable resources after a large generation trip or load increase. The controller is designed to guarantee asymptotic stability for a generic grid with multiple synchronous generators and GFCs represented by a reduced-order model. The controller is based on the integral sliding mode approach and requires frequency information of the neighboring buses if GFCs are connected to them. The proposed approach also leads to a quantifiable frequency support mechanism that aims to maximize the improvement in frequency nadir and minimize the steady-state frequency deviation. In addition, it allows a GFC to refrain from participating in frequency support if it chooses to do so. Simulations on the electromagnetic transient (EMT) model of a 4-machine 2-area system with 1 GFC and a detailed phasor model of the modified IEEE 16-machine system with 4 GFCs equipped with inner control loops demonstrate the effectiveness of the suggested control.

Designing thermoelectric self-cooling system for electronic devices: Experimental investigation and model validation

Thermal management of electronic devices is encountering a bottleneck due to the continuously increased heat flux generated from equipment. Fortunately, the development of thermoelectric self-cooling (TESC) technology provides new opportunities for cooling electronic devices passively. In this paper, a practical application of the TESC technology on an ultra-high performance (UHP) lamp used in commercial projectors is investigated both experimentally and numerically. Experimental results show that once the TESC system is carefully designed, it can perform better than conventional forced cooling systems with no power consumed. A numerical model is further established based on the thermal resistance-capacitance network. The comparison between experimental and simulation results proves the accuracy of the proposed model. The dynamic deviation of the numerical model is within 9%, and the steady-state deviation is within 2%. Furthermore, a parametric study is conducted to analyze the influence of different physical properties and structures of thermoelectric materials. Results indicate that choosing an appropriate configuration of physical properties is more important than purely improving the dimensionless figure of merit. Additionally, about 70% of the thermoelectric materials can be saved if a suitable fill factor and thickness of thermoelectric pairs were utilized.

On the validity of steady-state for nebular phase kilonovae

ABSTRACT The radioactively powered transient following a binary neutron star merger, known as a kilonova (KN), is expected to enter the steady-state nebular phase a few days after merger. Steady-state holds until thermal reprocessing time-scales become long, at which point the temperature and ionization states need to be evolved time-dependently. We study the onset and significance of time-dependent effects using the non-local thermodynamic equilibrium spectral synthesis code sumo. We employ a simple single-zone model with an elemental composition of Te, Ce, Pt, and Th, scaled to their respective solar abundances. The atomic data are generated using the Flexible Atomic Code (fac), and consist of energy levels and radiative transitions, including highly forbidden lines. We explore the KN evolution from 5 to 100 d after merger, varying ejecta mass and velocity. We also consider variations in the degree of electron magnetic field trapping, as well as radioactive power generation for alpha and beta decay (but omitting fission products). We find that the transition time, and magnitude of steady-state deviations are highly sensitive to these parameters. For typical KN ejecta, the deviations are minor within the time-frame studied. However, low density ejecta with low energy deposition show significant differences from ∼10 d. Important deviation of the ionization structure solution impacts the temperature by altering the overall line cooling. Adiabatic cooling becomes important at t ≥ 60 d which, in addition to the temperature and ionization effects, lead to the bolometric light-curve deviating from the instantaneous radioactive power deposited.

Enabling hybrid energy storage systems in VSC‐based MTDC grids for decentralized fast frequency response control in low‐inertia AC/DC systems

This paper studies the hybrid energy storage system to provide frequency support for the interconnected AC grid through MTDC systems interfacing renewable resources. A hybrid energy storage structure was created using a supercapacitor (SC) and battery storage systems (BESs). To coordinate the sharing of power between SC and BESS, an improved droop controller based on virtual inductance, capacitance, and resistance gain (VICRC) is suggested. Meanwhile, the droop controller's steady-state deviation of the DC link voltage is immediately suppressed. The SC will be in charge of compensating the high-frequency demand, whereas the BESS will be in charge of compensating the low-frequency power demand, thanks to a decentralized energy management process. In addition, the suggested method aids in the rehabilitation of the SC's SOC. Finally, the simulation results with detailed models of the wind farms and AC–DC grid converters are performed on IEEE tests systems in Simulink/SPS and the results extensively discussed to evaluate the proposed structure.

Countering the Deleterious Effects of Electromagnetic Pulse

Robot systems like automated shipping swinging robots, wire transducer sensors and even computer indigenous time sensors (amongst others) often use oscillating circuits such as the famous van der Pol system, while this manuscript investigates protection of such sensor circuitry to spurious voltage spikes accompanying an electromagnetic pulse. These spurious voltages can lead to uncontrolled robot motion and even debilitation. A very brief discussion of electromagnetic pulses yields design parameters to evaluate circuit responses to realistic disturbing pulses. Recent research in nonlinear-adaptive methods to protect circuits are described to highlight the proposed novelty: utilization of feedback rules as adaptive mechanisms to modify the otherwise nonlinear feedforwards systems improving the results in recent literature. Feedback is iterated to select adaption parameters that simultaneously produce favorable circuit performance in addition to effective parameter identification inherent in the adaption (to provide meaningful parameter estimates to unspecified future applications). Spurious voltages were rapidly rejected with a mere 0.3% trajectory deviation, stabilizing quickly with a final (steady state) deviation of 0.01%. The demonstrated abilities to reject the deleterious spurious effects are compared to nominal figures of merit for timing accuracy of various computer systems to conclude the proposed methods are effective for some applications, but insufficient for others.

New Stable Non-Vector Control Structure for Induction Motor Drive

The article focuses on a design and experimental verification of continuous nonlinear systems control based on a new control structure based on a linear reference model. An application of Lyapunov’s second method ensures its asymptotic stability conditions. The basic idea in the development of the control structure consists of utilizing additional information from a newly introduced state variable. The structure is applied for angular speed control of an induction motor (IM) drive representing a higher-order nonlinear system. The developed control algorithm helps to achieve the zero steady-state control deviation of the IM drive angular speed. Simulations and experiments performed in various operating states of the IM drive confirm the advantages of the new control structure. Except for set dynamics, the method ensures that the system is stable, invariant to disturbances, and is robust against variations of the parameters. When comparing the obtained control structure of the IM control with the classical vector control, the proposed control structure is simpler. In addition, the proposed control structure is linear, robust against variation in important parameters and invariant against external disturbances. The main advantage over conventional control techniques consists of the fact that the controller design does not require any exact knowledge of the system parameters and, moreover, it does not suffer from system stability problems. The method will find a wide applicability not only in the field of AC controlled drives with IM but also generally in control of industry applications.

Real-Time Control of Nanoparticle-Mediated Thermal Therapy Using Photoacoustic Imaging.

This work aims to determine whether photoacoustic (PA) thermometry from a commercially available PA imaging system can be used to control the temperature in nanoparticle-mediated thermal therapies. The PA imaging system was interfaced to obtain PA images while scanning ex-vivo tissue. These images were then used to obtain temperature maps in real-time during heating. Validation and calibration of the PA thermometry were done using a fluoroptic thermometer. This thermometer was also used to develop and tune a software-based proportional integral derivative (PID) controller. Finally, a PA-based PID closed-loop controller was used to control gold nanorod (GNR) mediated laser therapy. The use of GNRs substantially enhanced laser heating; the temperature rise increased 7-fold by injecting a GNR solution with a concentration of 0.029 mg/mL. The control experiments showed that the desired temperature could be achieved and maintained at a targeted location in the ex-vivo tissue. The steady-state mean absolute deviations (MAD) from the targeted temperature during control were between 0.16 [Formula: see text] and 0.5 [Formula: see text], depending on the experiment. It was possible to control hyperthermia treatments using a software-based PID controller and a commercial PA imaging system. The monitoring and control of the temperature in thermal-based therapies are important for assuring a prescribed temperature to the target tissue while minimizing the temperature of the surrounding healthy tissue. This easily implemented non-invasive control system will facilitate the realization of a broad range of hyperthermia treatments.

A novel method for constructing a dynamics model with the flexible characteristics

An accurate dynamics model is an essential part of ensuring the effectiveness of constructing flexible dynamical systems in the simulation. Finite element method is an effective method to build a flexible structural dynamics model, but this method will cause the model to have too many orders to increase the difficulty in the simulation. The reduction method based on the finite element principle is an effective method to build a streamlined model. This paper proposes a method that combines the critical modes of the structure and the reduction method based on the finite element model to construct an effective flexible dynamics model. Firstly, the determination of primary and secondary degrees of freedom is provided by the judgment of critical modes. Then, an adequate simulation model and an experimental setup are established respectively based on a flexible structure as an example. Finally, through the simulation comparison, the reduction model and the full-order model keep the same simulation results, but the simulation time consumed by the latter is 13 times of the former. In terms of experimental and simulation comparison, the simulation and the experimental results have the same transient oscillation frequency, and the steady-state angle deviation is 2 mrad.

Research on Optimization of Flow Field of Denitration System of 600MW Unit and Modification of Fine Ammonia Injection

Aiming at the uneven distribution of flow field in the denitration system of coal-fired power plant boilers, poor mixing of ammonia and nitrogen, increased ammonia escape, and easy blockage of the air preheater, a flow field optimization and transformation plan was proposed through numerical simulation and added in the flue of the denitration system. Equipped with baffles and static mixers, modified the ammonia injection pipeline in zones, implemented ammonia injection total control and grid balance automatic adjustment control. After the transformation of precise ammonia injection for denitrification, the NOx emission of the unit is stably controlled at 40 mg/Nm3, the steady-state deviation value and other indicators are better than the acceptance standard, and the air preheater differential pressure is effectively controlled.

Dynamic modelling and stability analysis of the articulated tracked vehicle considering transient track-terrain interaction

Articulated tracked vehicles (ATVs) exhibit enhanced steerability but reduced yaw stability. Apart from the track-terrain contact, the dynamics of the articulated frame steering (AFS) system strongly influences the stability of ATVs. We developed a detailed hydraulic steering system and a yaw-plane ATVs model for vehicle stability research. The transient characteristic of track-ground contact was considered. The multibody dynamics model by Recurdyn/Track software was compared with the established model to verify the model correctness at time-domain and frequency-domain. The result suggests that the vehicle yaw stability can be evaluated in terms of the oscillation frequency, damping ratio, overshoot, and steady-state deviation of articulation angle response. A multi-objective optimization is proposed to obtain the optimized structural parameters of AFS system by employing response surface method (RSM) and non-dominated sorting genetic algorithm II (NSGA-II). The optimal solutions revealed that more compact mechanism design of AFS system contributes to a compromise stability performance with 4.44 % decrease in the oscillation frequency and 10.3 % decrease in the damping ratio.