System Dynamic Performance Research Articles

Dynamic investigation of the electromechanical coupling system in a permanent magnet direct-drive locomotive under rotor eccentricity faults

In the traction system of a direct-drive locomotive, the gearbox design is eliminated, enabling the direct transmission of output torque from the traction motor to the wheelset. Due to this unique structure, rotor eccentricity, which is a common fault in traction motors, can have a direct impact on the dynamic performance of key components such as the motor, bogie, and wheelset in locomotives. In order to investigate the dynamic response of the direct drive locomotive under rotor eccentricity faults, a comprehensive electromechanical coupling model that considers the dynamic motion of the rotor is established in this paper. The coupling effect between the mechanical system and the electrical system, as well as the dynamic forces induced by rotor eccentricity, are taken into account in the model. The simulation results reveal that ripple torque has an obvious effect on rotor dynamics behaviour, while rotor air-gap eccentricity and mass eccentricity exhibit varying degrees of influence on the dynamic performance of the vehicle system. Furthermore, the influence laws of rotor eccentric distance on the vibration responses of critical locomotive components are revealed. These findings provide valuable theoretical guidance for the operational maintenance and fault diagnosis of traction motors in direct-drive locomotives.

Global MPPT controllers for enhancing dynamic performance of photovoltaic systems under partial shading condition

This research focuses on the development and evaluation of global maximum power point tracking MPPT controllers for enhancing the dynamic performance of Photovoltaic (PV) systems under partial shading conditions. Three different controllers, namely Proportional-Integral (PI), Fractional-Order PI (FOPI), and Fuzzy Logic Controllers (FLC), are studied in conjunction with a modified Incremental Conductance (IC) and Fractional Open-Circuit Voltage (FOCV) algorithms. The proposed controllers with a novel optimization algorithm called Atom Search Optimization Algorithm (ASOA) are compared with classical control. The objective is to investigate the effectiveness of the global MPPT controllers in achieving higher tracking accuracy, faster convergence, and improved stability under varying shading conditions. The study involves extensive simulations using a representative PV system model subjected to different shading scenarios. The results demonstrate that the proposed global MPPT controllers with the ASOA algorithm, when integrated with the modified MPPT algorithms, outperform the classical control techniques in terms of dynamic performance and response to partial shading conditions. The suggested ASOA-based fuzzy IC MPPT controllers can reach the MPP more quickly with a shorter settling time and a better tracking response. Furthermore, with a reduced settling time of about 1.9 % and an average power harvesting efficiency of over 97.9 %, ASOA-based fuzzy IC MPPT controllers offer the best harvesting characteristics. The controller exhibits superior tracking accuracy and stability, mitigating the effects of shading-induced multiple peaks in the P-V curve.

Reliability Analysis for RV Reducer by Combining PCE and Saddlepoint Approximation Considering Multi-Failure Modes

Abstract RV (Rotate Vector) reducer is an essential mechanical transmission device extensively used in industrial machinery, robotics, aerospace and other fields. The dynamic transmission characteristics and strength of the cycloidal pin gear, turning arm bearing of RV reducer significantly affect the motion accuracy and reliability of the whole equipment. Uncertainties from manufacturing and assembly error, working loads add complexity to these effects. Developing effective methods for uncertainty propagation and reliability analysis for the RV reducer is crucial. In this work, the mail failure modes of RV reducer are studied, and an effective reliability analysis method for RV reducer considering the correlation between multi-failure modes by combining polynomial chaos expansions (PCE) and saddlepoint approximation method (SPA) is proposed. This paper develops an uncertainty propagation strategy for RV reducer based on dynamic simulation and PCE method with high accuracy. On this basis, a surrogated cumulant generating function (CGF) and SPA are combined to analyze the stochastic characteristic for the failure behavior. Based on the probability density function (PDF) and cumulative distribution function (CDF) calculated by SPA, copula function is employed to quantify the correlations between the multi-failure modes. Then, the system reliability with multi-failure modes is estimated by SPA and optimal copula function. The proposed method provides an effective reliability assessment technology with high-accuracy for complex system under unknown physical model and distribution characteristics. The validity of the proposed approach is illustrated RV-320E reducer reliability estimation, offering a basis to improve the performance of complex dynamic system. .

Modal analysis of tripod-ball type universal coupling composite transmission shaft system

Abstract In order to improve the dynamic performance of the tripod-ball type universal coupling composite transmission shaft system, ANSYS Workbench modal analysis is carried out. By modal analysis of the transmission shaft system, the vibration characteristics of the coupling have been obtained, which can avoid its natural frequency in practical situations. The figures for the first ten modes have been obtained. The results indicate that the areas with the greatest deformation are on the intermediate shaft, bell housing, and trident sleeve. This provides a theoretical basis for further research on the transmission shaft system.

Improving The Dynamic Performance of Two-area System Based Integration of RES

Improving The Dynamic Performance of Two-area System Based Integration of RES

Generation Control of Multi-Area Multi-Source Power System using Fire-Fly Algorithm

This article presents automatic generation control (AGC) of an interconnected three area power system having different production sources such as hydropower, thermal and gas power plants. The control areas are provided with single reheat turbine and generation rate constraints of 3%/min. An attempt has been made to apply a Proportional derivative–Proportional integral derivative (PD–PID) cascade controller in AGC. Controller gains are optimized simultaneously using more robust and powerful evolutionary computational technique Firefly Algorithm (FFA). Performance of classical controllers such as Proportional Integral (PI) and Proportional Integral Derivative (PID) controller are investigated and compared with PD–PID cascade controller. Investigations reveal that PI, and PID provide more or less same response where as PD–PID cascade controller provides much better response than the later. The system dynamic performances are studied with 1% and 2% step load perturbation in Area1. Sensitivity analysis reveals that the FFA optimized PD–PID Cascade controller parameters obtained at nominal condition of loading, size and position of disturbance and system parameter (Inertia constant, H) are robust and need not be reset with wide changes in system loading, size, position of disturbance and system parameters.

Model-free visual servoing based on active disturbance rejection control and adaptive estimator for robotic manipulation without calibration

PurposeVisual feedback control is a promising solution for robots work in unstructured environments, and this is accomplished by estimation of the time derivative relationship between the image features and the robot moving. While some of the drawbacks associated with most visual servoing (VS) approaches include the vision–motor mapping computation and the robots’ dynamic performance, the problem of designing optimal and more effective VS systems still remains challenging. Thus, the purpose of this paper is to propose and evaluate the VS method for robots in an unstructured environment.Design/methodology/approachThis paper presents a new model-free VS control of a robotic manipulator, for which an adaptive estimator aid by network learning is proposed using online estimation of the vision–motor mapping relationship in an environment without the knowledge of statistical noise. Based on the adaptive estimator, a model-free VS schema was constructed by introducing an active disturbance rejection control (ADRC). In our schema, the VS system was designed independently of the robot kinematic model.FindingsThe various simulations and experiments were conducted to verify the proposed approach by using an eye-in-hand robot manipulator without calibration and vision depth information, which can improve the autonomous maneuverability of the robot and also allow the robot to adapt its motion according to the image feature changes in real time. In the current method, the image feature trajectory was stable in the camera field range, and the robot’s end motion trajectory did not exhibit shock retreat. The results showed that the steady-state errors of image features was within 19.74 pixels, the robot positioning was stable within 1.53 mm and 0.0373 rad and the convergence rate of the control system was less than 7.21 s in real grasping tasks.Originality/valueCompared with traditional Kalman filtering for image-based VS and position-based VS methods, this paper adopts the model-free VS method based on the adaptive mapping estimator combination with the ADRC controller, which is effective for improving the dynamic performance of robot systems. The proposed model-free VS schema is suitable for robots’ grasping manipulation in unstructured environments.

Composite control based on FNTSMC and adaptive neural network for PMSM system

In this paper, a novel fixed-time non-singular terminal sliding mode control (NFNTSMC) method with an adaptive neural network (ANN) is proposed for permanent magnet synchronous motor (PMSM) system to improve PMSM performance. For nominal PMSM system without disturbance, a novel fixed-time non-singular terminal sliding mode control is designed to achieve fixed-time convergence property to improve the dynamic performance of the system. However, parameters mismatch and external load disturbances generally exist in PMSM system, the controller designed by NFNTSMC requires a large switching gain to ensure the robustness of the system, which will cause high-frequency sliding mode chattering. Therefore, an adaptive radial basis function (RBF) neural network is designed to approximate the unknown nonlinear lumped disturbance including parameters mismatch and external load disturbances online, and then the output of the neural network can be compensated to the NFNTSMC controller to reduce the switching gain and sliding mode chattering. Finally, the fixed-time convergence property and stability of the system are proved by Lyapunov method. The simulation and experimental results show that the presented strategy possesses satisfactory dynamic performance and strong robustness for PMSM system. And the proposed control scheme also provides an effective and systematic idea of the controller design for PMSM.

Dual-function of energy harvesting and vibration isolation via quasi-zero stiffness piezoelectric mechanism

Industry 4.0 realizes intelligent interconnection through the sensor group of the Internet of Things. A key challenge is to achieve the self-powering of sensors and stable operation of precision instruments. This paper introduces a dual-functional structure (VIPEH) integrating energy harvesting (EH) and vibration isolation (VI) based on the quasi-zero stiffness (QZS) piezoelectric mechanism. The paper analyzes the nonlinear statics of piezoelectric flexible beams under large deformations and conducts parametric analysis. A nonlinear dynamic model with electromechanical coupling was developed to investigate the impact of mechanical and electrical parameters on the system's dynamic bifurcation behavior, EH, and VI performance. Finally, an experimental setup is created to evaluate the VIPEH's characteristics. Sweep frequency excitation experiments demonstrate that the initial isolation frequency of VIPEH is lower than 1.4 Hz. The important thing is that VIPEH can still power the sensor based on the isolation frequency, and the output power of a single piezoelectric material can reach 3.19 mW. This not only enables the isolation of low-frequency vibrations but also presents a highly promising application for achieving self-powering in sensor clusters within the context of Industry 4.0 and the IoTs.

Study of dynamic performance of PEMFC-based CCHP system in a data center based on real-time load and a novel synergistic control method with variable working conditions

In this paper, the dynamic performance of Proton Exchange Membrane Fuel Cell-based Combined Cooling Heating and Power (PEMFC-based CCHP) system combined with a data center real-time load is studied. A novel synergistic control method is proposed to achieve optimization of energy flow between system units under fluctuating load. First, the off-design working condition models of PEMFC-based CCHP system are constructed. The delay in the changes of data center temperature is considered because of the thermal inertia under dynamic conditions. Second, the dynamic performance of PEMFC-based CCHP system to step changes of data center load is analyzed. Third, to further reveal the energy flow between units, the units output under varying load conditions are compared under the constraints of power and refrigeration supply. Finally, the dynamic performance of PEMFC-based CCHP system under the traditional control method of following electric load are revealed. A novel synergistic control method for the PEMFC-based CCHP system is proposed by refining the traditional method to optimize the energy flow between units. The result presents that the average energy efficiency reaches 78.29 %. Compared with the following electric load method, the energy efficiency is increased by 6.02 %. The response time of synergistic control method is 27.0 ms. Improved energy efficiency and fast response have been achieved.

Fault-Tolerant Control of Autonomous Underwater Vehicle Actuators Based on Takagi and Sugeno Fuzzy and Pseudo-Inverse Quadratic Programming under Constraints.

Autonomous Underwater Vehicles (AUVs) play a significant role in ocean-related research fields as tools for human exploration and the development of marine resources. However, the uncertainty of the underwater environment and the complexity of underwater motion pose significant challenges to the fault-tolerant control of AUV actuators. This paper presents a fault-tolerant control strategy for AUV actuators based onTakagi and Sugeno (T-S) fuzzy logic and pseudo-inverse quadratic programming under control constraints, aimed at addressing potential actuator faults. Firstly, considering the steady-state performance and dynamic performance of the control system, a T-S fuzzy controller is designed. Next, based on the redundant configuration of the actuators, the propulsion system is normalized, and the fault-tolerant control of AUV actuators is achieved using the pseudo-inverse method under thrust allocation. When control is constrained, a quadratic programming approach is used to compensate for the input control quantity. Finally, the effectiveness of the fuzzy control and fault-tolerant control allocation methods studied in this paper is validated through mathematical simulation. The experimental results indicate that in various fault scenarios, the pseudo-inverse combined with a nonlinear quadratic programming algorithm can compensate for the missing control inputs due to control constraints, ensuring the normal thrust of AUV actuators and achieving the expected fault-tolerant effect.

Adaptive backstepping sliding mode compensation control for electro‐hydraulic load simulator with backlash links

AbstractWhen a mechanical backlash between the loading piston rod and the steering gear piston rod connection of the electro‐hydraulic load simulator (EHLS), it will lead to poor loading accuracy. To solve this problem, an adaptive backstepping sliding mode controller based on the backlash feedforward compensation and state observer is proposed. First, the mechanism of surplus force generation in the EHLS is analyzed, and a mathematical model containing position disturbance and backlash nonlinearity is established based on the analysis results. Second, a state observer is designed to estimate the system state and the parameter adaptive law is designed to estimate the system parameters. Third, the adaptive backstepping method is combined with the non‐singular terminal sliding mode control (NTSMC) strategy to deal with the position disturbance and parameter uncertainty and to enhance the system's dynamic performance. Finally, a backlash feed‐forward compensator is engineered to restrain the detrimental effects caused by the backlash nonlinearity, and the simulation experimental results show that the designed new method can realize the precise loading of the EHLS under different working conditions, and the surplus force is suppressed better at the same time.

A thrust vector control test system of large range solid rocket engine utilizing a four-point support piezoelectric dynamometer and a deflected flange structure

The accurate measurement of thrust vector is very important to improve the life and safety of aircraft engine. In order to meet the requirements of thrust vector test of a solid rocket engine and overcome the contradiction between large thrust (>50 kN) and high-frequency response (≫30 Hz)/high precision measurement (<3%), a thrust vector control test system utilizing a four-point support piezoelectric dynamometer (FSPD) and a deflected flange structure was proposed. The test system mainly consists of a four-point support piezoelectric dynamometer and some vector force simulation loading devices. The theoretical mechanical model and the thrust vector control test system was set up to study the performance of solid rocket engine. Firstly, the piezoelectric elements and four-point support piezoelectric dynamometer were calibrated by the three-direction force calibration loading device. Secondly, the rationality and feasibility of the thrust vector control test system were proved by the simulated loading experiment. The research results show that the static and dynamic performance of the test system meet the test requirements, and it has good linearity and repeatability, errors are less than 1.00 %, and interphase interference is less than 2.00 %. The measuring system proposed in this paper provides a new idea for the accurate measurement of vector force with large load and high-frequency response.

Activation of peracetic acid by a magnetic biochar-ferrospinel AFe2O4 (A = Cu, Co, or Mn) nanocomposite for the degradation of carbamazepine − A comparative and mechanistic study

Peracetic acid (PAA)-based advanced oxidation processes (AOPs) are promising technologies for the efficient treatment of persistent contaminants in wastewater. In this study, three different magnetic biochar (BC)-ferrospinel AFe2O4 (A = Cu, Co, or Mn) nanocomposites were synthesized through a combined sol–gel/pyrolysis process for the activation of PAA to degrade carbamazepine (CBZ). The following order of efficiency was observed for CBZ degradation in the presence of PAA: BC-CoFe2O4 (100 %) > BC-MnFe2O4 (7 %) ≈ BC-CuFe2O4 (7 %). In addition, 0.8 mM PAA, 0.3 g/L catalyst, nearly neutral pH, and 333 K were identified as the optimal operating parameters for the degradation of 1 mg/L CBZ in the BC-CoFe2O4/PAA system. Mechanistic studies revealed that CH3C(O)OO radicals are the dominant active species for the degradation of CBZ in the BC-CoFe2O4/PAA system, and the continuous conversion of Co(II) to Co(III) in this system is responsible for the generation of these radicals. In addition, the water matrices (e.g., humic acid (20 mg/L), NaCl (0.05 M), and NaNO3 (0.01 M)) played negligible roles in the degradation of CBZ in the BC-CoFe2O4/PAA system. This system exhibited highly selective and reactive degradation of organic pollutants with electron-rich groups (e.g., CBZ (0.36 min−1), sulfamethoxazole (0.12 min−1), and diclofenac (0.28 min−1)). Furthermore, the degradation products of CBZ were identified, and possible degradation pathways and toxicity of these transformation products were proposed. The BC-CoFe2O4/PAA system demonstrated outstanding degradation performance in dynamic systems and real wastewater treatment applications. This study describes the performance of an efficient and easy-to-separate catalyst for the activation of PAA. This study facilitates the development and application of PAA-based AOPs for wastewater treatment.

Joint non-fragile automatic generation control and multi-event driven mechanism co-design for wind integrated power system under denial of services attacks

Denial of services (DoS) attacks exist in wind integrated power system. DoS attacks can cause network-induced delay and packages loss in information transmission. Meanwhile, considering the parameter perturbation of controller and system model uncertainty in wind integrated power system, these may cause the system dynamic performances degradation or even instability. Based on the above considerations, the joint non-fragile automatic generation robust control of wind integrated power system under DoS attacks is studied in this paper. In order to ensure the expected system performance and more effectively utilize the limited network communication resources under DoS attacks, a novel dynamic multi-event driven mechanism based joint non-fragile H∞ automatic generation control method is proposed. By constructing a suitable Lyapunov-Krasovskii functional and utilizing the Shur complement lemma to handle nonlinear matrix inequality, the sufficient conditions are derived to guarantee the asymptotic stability of wind integrated power system under DoS attacks. Furthermore, the performance of the proposed non-fragile regulator is demonstrated through a four-area wind integrated power system to show the feasibility and applicability. The analysis result indicates that the proposed scheme provides stronger robustness, higher wind energy utilization efficiency and more efficient communication mechanism.

Vibro-acoustic coupling analysis of dynamic performance of the double panel system with mechanical links

The theoretical prediction model for the dynamic performance of a double panel system that takes into account the effect of mechanical links is developed in this paper. The double panel system is established considering both the vibro-acoustic coupling and the effect of the mechanical links between two flexible panels. Firstly, the modal characteristics of the double panel system are analyzed and compared with the results calculated by the finite element method. The accuracy and efficiency of the proposed model have been validated. Subsequently, the forced response of the double panel system under different external excitations is studied. It is shown that the mechanical link resulted in less response level of the double panel system in in low frequency range due to the structural path in the energy transmission of the double panel system. Finally, the effect of the mechanical link parameters on the dynamic performance of the double panel system is discussed. The results reveal that the stiffness coefficients, location distributions, and number of mechanical links can significantly influence the dynamic behavior of the double panel system. Therefore, the theoretical model can be used in optimization techniques to improve the sound transmission characteristics of the double panel system.

Stability analysis of delayed load frequency control system based on a novel augmented functional

This article is concerned with the stability issue of PI-based load frequency control (LFC) systems with time-varying delays and load interference. Firstly, a novel augmented Lyapunov–Krasovskii functional (LKF) is developed, in which the single integral term includes the augmented s-dependent integral term of delay-partition. For the purpose of coordinating with the constructed LKF effectively, a generalised free-matrix-based integral inequality and quadratic inequality are utilised to estimate the functional derivatives accurately, so that the stability criterion of less conservative is obtained. Finally, the relationship between the PI gains and the delay margins is presented, and the effects of time delays and PI gains on the system dynamic performance are discussed simultaneously by simulation. The simulation results verify the validity of the proposed method.

Gas rudder 2DOF FOPID position control based on CSFLA optimisation

Aiming at the problems of parameter variety, rigid-flexible coupling and external unknown factors interference in the process of spacecraft propulsion, a two-degree-of-freedom fractional-order PID (2DOF FOPID) controller based on a coevolutionary shuffled frog leaping algorithm (CSFLA) is designed for the high-precision control of the gas rudder servo control system. The anti-interference and target tracking capabilities of 2DOF PID is combined with the advantage of FOPID, which is insensitive to the parameters of the controlled object, to improve the performance of the control system as a whole. CSFLA is formed by integrating the self-learning evolution of elite populations and the interactive learning strategy among populations into the SFLA to enhance the global searching ability and searching accuracy of SFLA, and CSFLA is used to optimize the parameters of the 2DOF FOPID controller. The simulation results show that the designed CSFLA-2DOF FOPID controller has the advantages of fast response speed, small overshoot, strong tracking performance and strong anti-disturbance ability, which improves the dynamic and static performance and anti-disturbance ability of the gas rudder servo control system.

A fast relay feedback auto-tuning tilt-integral-derivative (TID) controller method with the fractional-order Ziegler–Nichols approach

The relay feedback auto-tuning method, which was an early commercialized approach, has maintained its popularity due to its simplicity and robustness. However, the classical proportional integral derivative (PID) controller auto-tuning method often results in unacceptable overshoot, especially for integrating and higher-order processes. By integrating the TID controller with the relay feedback technique, we significantly enhance dynamic control performance without relying on prior knowledge of the system. However, the direct application of the classical auto-tuning method to the TID controller encounters challenges due to the additional fractional-order transfer function s−1n. Therefore, we have developed a fractional-order Ziegler–Nichols (FOZ-N) approach, specifically designed to adjust the parameters of the TID controller. The proposed FOZ-N method is fast, simple, and capable of achieving the desired performance. In contrast to the previous Ziegler–Nichols tuning method, the TID controller parameters Kt and Ki are determined to shift the critical point (−1/Ku,j0) to the FOZ-N point (−0.5,−j0.7) on the Nyquist curve, ensuring system robustness and dynamic performance. The impact of the fractional order parameter s−1n and ratio r is explored through time-domain analysis, where these parameters are determined to ensure optimal dynamic performance. Additionally, we provide a detailed tuning procedure along with a helpful example. To demonstrate the advantages of the proposed auto-tuning TID controller over the Ziegler–Nichols PID controller, Optimal PID controller, simple internal model control (SIMC) PID controller, and Ziegler–Nichols FOPID controller, we present a simulation illustration involving multiple different systems. To validate the practical outcomes of this paper, we present experimental results on the temperature control of a Peltier cell.

Modelling and analysis of nuclear reactor system coupled with a liquid metal battery

AbstractTraditionally, nuclear power plants in the U.S. provide baseload power to the power grid because they have less flexibility for ramping their output power than natural gas peaking plants. However, achieving climate goals to reduce the consumption of fossil‐based natural gas places pressure on nuclear power plants and other power generators to ramp up their power output to balance grid generation with demand. This paper presents the modelling and performance analysis of a nuclear reactor system (NRS) coupled to a liquid‐metal battery (LMB) to improve its dynamic response and enable its black start capability. The NRS and LMB thermal behaviour are modelled in Dymola, while the electrical dynamics of the LMB and power grid are modelled in RTDS‐RSCAD. Both simulation platforms are coupled and share their thermal and electrical data using a Transmission Control Protocol/Internet Protocol (TCP/IP) communication protocol. The dynamic performance of the NRS‐LMB integration is tested on the IEEE 9 bus, which demonstrates its ability to respond and provide frequency and voltage regulation. The black start capability of the NRS‐LMB is also evaluated by simulating a grid outage and using the LMB to supply the auxiliary loads required to bring the NRS back online as soon as possible. The results show that coupling an NRS to an LMB improves the system dynamic performance and enables it to black start after being disconnected from the grid for several days.