Active Control Strategy Research Articles

Active disturbance rejection control of three-phase LCL power conversion system under non-ideal grid conditions

Under non-ideal grid operating conditions such as unbalanced grid voltage and harmonic grid that are commonly found in microgrid conditions, the negative sequence components of the microgrid voltage interfere with the active and reactive current controls in the power conversion system, leading to an increase in the harmonic content of the grid-side current and affecting the power quality of the microgrid system. To solve these problems, firstly, the mathematical model of the LCL-type power conversion system is analyzed, and a linear active disturbance rejection control based on model compensation is designed. Secondly, the influence of non-ideal power grid conditions on the control of the LCL-type power conversion system is analyzed, and the active disturbance rejection control strategy of the LCL-type power conversion system based on frequency-locked loops with harmonic cancellation modules (HCM-FLL) is proposed, which speeds up the system, improves the system’s robustness, and reduces the harmonic content of the network measurement current under the condition of power grid voltage unbalance and harmonic power grid. Finally, by using the verification of MATLAB/Simulink simulation, the current power quality obviously under the condition of voltage unbalance and harmonic power grid is evidently improved by the proposed control strategy. When compared to the traditional control methods, the control strategy proposed in this study features a simple control structure, making it easy to implement in engineering without requiring high controller performance or additional circuits. This reduces design costs and provides a wide range of controller parameters, ensuring strong anti-interference performance without the need for frequent controller parameter adjustments.

Active fault-tolerant control scheme for four-wheel independent drive electric vehicles under actuator faults

For chassis-by-wire in four-wheel independent drive electric vehicles (4WID-EVs), a large number of controllable actuators with control systems and electrical systems make the vehicle more sensitive to the failure of electronic components in actuators. When actuator faults occur, the stability and handling performance of 4WID-EVs will deteriorate, even affecting the driving safety. To handle this problem, the typical actuator faults of 4WID-EVs and their characteristics are firstly analyzed in detail. After that, a control-oriented uncertain 7 degrees of freedom vehicle dynamics model is established. Then, a modified sliding mode active fault tolerant control (FTC) scheme with layered architecture is proposed, which contains the upper and lower layers. In the upper layer, a modified sliding mode controller with a nonlinear extended state observer is designed to track the reference states under the influence of model uncertainty. In the lower layer, an improved torque distribution algorithm is proposed to compensate for the limited direct yaw moment caused by in-wheel motor faults. Comparison works are carried out both in simulation and experiment. Simulation results show that the proposed method improves performance by 80.5% and 70.2% compared with existing FTC method under 2 fault conditions, respectively. Furthermore, real vehicle experiments also indicate that the proposed method improves performance by 59.6% and 74.4% under two pre-set fault conditions, respectively. The proposed method might provide a theoretical reference for actual controller design in 4WID-EVs.

How to control hydrodynamic force on fluidic pinball via deep reinforcement learning

Deep reinforcement learning (DRL) for fluidic pinball, three individually rotating cylinders in the uniform flow arranged in an equilaterally triangular configuration, can learn the efficient flow control strategies due to the validity of self-learning and data-driven state estimation for complex fluid dynamic problems. In this work, we present a DRL-based real-time feedback strategy to control the hydrodynamic force on fluidic pinball, i.e., force extremum and tracking, from cylinders' rotation. By adequately designing reward functions and encoding historical observations, and after automatic learning of thousands of iterations, the DRL-based control was shown to make reasonable and valid control decisions in nonparametric control parameter space, which is comparable to and even better than the optimal policy found through lengthy brute-force searching. Subsequently, one of these results was analyzed by a machine learning model that enabled us to shed light on the basis of decision-making and physical mechanisms of the force tracking process. The finding from this work can control hydrodynamic force on the operation of fluidic pinball system and potentially pave the way for exploring efficient active flow control strategies in other complex fluid dynamic problems.

Combined space–time reduced-order model with three-dimensional deep convolution for extrapolating fluid dynamics

There is a critical need for efficient and reliable active flow control strategies to reduce drag and noise in aerospace and marine engineering applications. While traditional full-order models based on the Navier–Stokes equations are not feasible, advanced model reduction techniques can be inefficient for active control tasks, especially with strong non-linearity and convection-dominated phenomena. Using convolutional recurrent autoencoder network architectures, deep-learning-based reduced-order models have been recently shown to be effective while performing several orders of magnitude faster than full-order simulations. However, these models encounter significant challenges outside the training data, limiting their effectiveness for active control and optimization tasks. In this study, we aim to improve the extrapolation capability by modifying the network architecture and integrating coupled space–time physics as an implicit bias. Reduced-order models via deep learning generally employ decoupling in spatial and temporal dimensions, which can introduce modeling and approximation errors. To alleviate these errors, we propose a novel technique for learning coupled spatial–temporal correlation using a three-dimensional convolution network. We assess the proposed technique against a standard encoder–propagator–decoder model and demonstrate a superior extrapolation performance. To demonstrate the effectiveness of the three-dimensional convolution network, we consider a benchmark problem of the flow past a circular cylinder at laminar flow conditions and use the spatiotemporal snapshots from the full-order simulations. Our proposed three-dimensional convolution architecture accurately captures the velocity and pressure fields for varying Reynolds numbers. Compared to the standard encoder–propagator–decoder network, the spatiotemporal-based three-dimensional convolution network improves the prediction range of Reynolds numbers outside of the training data.

Seamless Fault-Tolerant Control for Cascaded H-bridge Converters Based Battery Energy Storage System

This article presents a phase-shifted pulsewidth-modulation-based fault-tolerant approach for the cascaded H-bridge-based battery energy storage system to ride through the single switch fault. When the fault occurs, the faulty cell is bypassed first. Afterwards, the missing voltage levels of the faulty cell are compensated by the remaining healthy cells to maintain the line-to-line voltages balanced. The compensation of the missing voltage levels presented is achieved by simple logic operation without modifying three-phase voltage references and phase-shifted angles of carriers, which enables seamless operation and enhances the system stability. In addition, the detailed active power control strategy used for state-of-charge balancing of the battery units is proposed and discussed. The validity and effectiveness of the proposed method are verified by simulation and experimental results.

Robustness Optimization Through Modified Linear Active Disturbance Rejection Control for High-Voltage Load Interface in Microgrid

In microgrid, the development and utilization of renewable energy generations are usually completed by DC-DC interface converters. Nonetheless, it is difficult to continuously output high-quality electrical energy under various uncertain interferences. With this, a modified linear active disturbance rejection control (MLADRC) scheme is proposed to handle these deficiencies. In this scheme, a correction function is introduced to cope with the overall disturbance reconstruction deviation, so as to realize the timely and accurate estimation. The proposed strategy is able to treat the unknown dynamics and the external disturbance as the overall disturbance through a single structure, alongside the plant is regulated by an improved control law with reference-signal differential feedforward to optimize the traceability for the reference signal. Through performance analysis, the difference between the proposed scheme and the conventional one was discussed. Additionally, the correspondence between controller parameters and operation characteristics is analyzed theoretically, so as to provide guidance for parameters adjustment. Finally, a 40-kW test platform is built, and experimental results are presented to verify the significance and correctness of the proposed approach.

Numerical Study of Two-Stage Temperature Control Strategy for High-Temperature Stability of Satellite-Borne Fiber Optic Gyroscope

Abstract Fiber optic gyroscopes (FOGs) are widely used in attitude control systems of spacecraft such as satellites and Mars rovers for their superior spatial adaptability. However, changes in ambient temperature can cause errors in the FOG and reduce its output accuracy. In this paper, a fuzzy two-stage temperature control strategy applied to a satellite-borne three-axis integrated fiber optic gyroscope (TAIFOG) is proposed. And the control rules of the fuzzy two-stage temperature controller are described in detail. A thermodynamic model that can quickly and accurately respond to the dynamic thermal characteristics of the satellite-borne TAIFOG is also constructed based on the lumped method. The effectiveness of the proposed fuzzy two-stage temperature control strategy in improving the temperature stability of the satellite-borne TAIFOG in orbit is verified through numerical studies. Numerical results show that this fuzzy two-stage active temperature control strategy can fundamentally improve the thermal state of the satellite-borne TAIFOG and ensure that its sensitive element fiber optic coils maintain high-temperature stability while the TAIFOG is in orbit. In addition, the startup time of TAIFOG is reduced to 308 s compared to the case without active temperature control, which is a reduction of 96.27%. This active temperature control strategy is well suited for engineering applications to improve FOG output accuracy.

Radio Frequency Cavity’s Analytical Model and Control Design

Reduction or suppression of microphonic interference in radio frequency (RF) cavities, such as those used in Electron Linear Accelerators, is necessary to precisely control accelerating fields. In this paper, we investigate modeling the cavity as a cylindrical shell and present its free vibration analysis along with an appropriate control scheme to suppress vibrations. To this end, we first obtain an analytical mechanical dynamic model of a nine-cell cavity using a modified Fourier-Ritz method that provides a unified solution for cylindrical shell systems with general boundary conditions. The model is then verified using the ANSYS software in terms of a comparison of eigenfrequencies which prove to be identical to the proposed model. We also present an active observer-based vibration control scheme to suppress the dominant mechanical modes of the cavity. The control system performance is investigated using simulations.

An active swing suppression control scheme of overhead cranes based on input shaping model predictive control

An input shaper-based model predictive control scheme is proposed for an overhead crane to suppress the swing of the payload. A control-oriented mathematical model of the crane is firstly derived based on the small angle hypothesis. Furthermore, three kinds of commonly used shapers are discussed and a zero vibration derivative shaper is selected for the crane. Then, a model predictive swing suppression controller is designed for the crane based on the selected shaper. Constraints on the control input and its slew rate are respected. Besides, the constraint on the swing angle of the payload is also respected as an output constraint. The constrained solution is given in the form of standard quadratic programming. The designed control scheme combines open-loop and closed-loop control techniques, achieving accurate positioning of the trolley and good swing suppression of the payload. A series of simulation demonstrates the effectiveness and advantages of the proposed scheme.

Active power control strategy of DFIGs in flexible interconnected distribution network

In the development of new-type power system, the flexible interconnected distribution network becomes a better inclination. With the continuous increase of wind power generation in the flexible interconnected distribution network, the frequency stability issue caused by the high randomness of wind power generation has become increasingly prominent. This paper suggests an advanced active power strategy of double-fed induction generators (DFIGs) based on modifying power tracking curves in the interconnected distribution network for smoothing out the fluctuations of the system frequency. To this end, the various power tracking operation is used to participate in power smoothing instead of maximum power tracking operation so as to fully utilize the large rotor inertia of the double-fed induction generators for smoothing out the fluctuations of the power output of double-fed induction generators and system frequency. The control gain for the various power tracking operation is determined by the instantaneous system frequency deviation and rotor speed of the DFIG. Based on the modified IEEE 14 power system, simulation results successfully proved that the suggested advanced active power strategy is benefit for reducing the fluctuations of the output power of the DFIG and suppressing the maximum system frequency deviations with the scenario of continuously varying wind speed conditions.

Active Disturbance Rejection-Based Performance Optimization and Control Strategy for Proton-Exchange Membrane Fuel Cell System

In this paper, to maximize the net output power and realize better performance optimization and control of the oxygen excess ratio, a complete dynamic model of the proton-exchange membrane fuel cell system is developed and an active disturbance rejection control strategy is proposed. The active disturbance rejection control drives the uncertainties and perturbations of the system to an extended state, which is predicted and eliminated by real-time input–output data. The simulation results indicate that, compared with the proportion–integral–differential and fuzzy proportion–integral–differential control, the active disturbance rejection control strategy can effectively improve the control performance with a lower control cost and less wear on the compressor, and the integral absolute error of the oxygen excess ratio control is reduced by up to 50%. In addition, the output voltage is improved and the power generation efficiency of the proton-exchange membrane fuel cell under the active disturbance rejection-based oxygen excess ratio control is 1.84% and 0.95% higher than that of the proportion–integral–differential and fuzzy proportion–integral–differential control, respectively. Moreover, the proposed optimal-reference control strategy increases the net power by up to 1.85% compared with the fixed-reference control strategy.

Spring damping based control for a novel lower limb rehabilitation robot with active flexible training planning.

During neurological rehabilitation training for patients with lower limb dysfunction, active rehabilitation training based on interactive force recognition can effectively improve participation and efficiency in rehabilitation training. This study proposes an active training strategy for lower-limb rehabilitation robots based on a spring damping model. The active training strategy included a kinetic model of the human-machine system, calculated and verified using a pull-pressure force sensor We used a dynamic model of the human-machine system and tensile force sensors to identify the human-machine interaction forces exerted by the patient Finally, the spring damping model is used to convert the active interaction force into the offset angle of each joint, obtaining the active interaction force followed by the active movement of the lower limbsRESULTS:The experimental results showed that the rehabilitation robot could follow the active interaction force of the subject to provide assistance, thus generating the following movement and effectively helping patients improve joint mobility. The active flexibility training control strategy based on the virtual spring damping model proposed in this study is feasible, and motion is stable for patients with lower limb dysfunction after stroke Finally, the proposed active training method can be implemented in future work in other rehabilitation equipment and combined virtual reality technology to improve rehabilitation training experience and increase patient participation.

An active fault tolerance framework for uncertain nonlinear high-order fully-actuated systems

This paper presents a novel active fault tolerance framework for uncertain high-order fully-actuated systems (HOFASs). Starting from the uncertain faulty HOFAS model with nonlinear measurement, the advantages of this description are revealed via Lie Derivatives. A HOFAS adaptive observer and controller integration is established and further a closed-loop HOFAS dynamic data modeling structure is derived. This structure uncovers the dynamic characteristics including fault features, and naturally yields a fault detectability condition. Based on the fault information from the dynamic data model, an active fault tolerant control strategy for HOFASs is proposed, which enriches HOFAS control theory. The uniformly bounded stability of the HOFAS model is proved theoretically and illustrated experimentally.

Decoupling active power control scheme of doubly-fed induction generator for providing virtual inertial response

Virtual inertial control (VIC) is implemented in the controller of doubly-fed induction generators (DFIGs) to compensate for the reduction in capability of the frequency regulation. However, the conventional VIC might give negative impacts on improve the frequency nadir due to the coupling power dynamics between the variation of the power references of the maximum power tracking operation (MPTO) and VIC. In addition, when regaining the rotor speed, a double frequency drop (DFD) trends to produce due to the sudden output drop. This paper suggests a decoupling active power control scheme of a wind power plant to improve the frequency nadir and minimize the DFD. To improve the frequency nadir, the proposed VIC suggests various operating power tracking operations to improve the frequency nadir. The variable-coefficient-PI-control based rotor speed recovery strategy (RSRS) is suggested to minimize the DFD and automatically switches to the MPTO. Test results demonstrate that the suggested decoupling active power control scheme with proposed RSRS and VIC strategy can minimize the DFD and reduce mechanical stresses on the wind turbine while enhancing the frequency nadir.

A practical approach to evaluate periodic rods composed of cells with geometric and material periodicity

The use of a periodic structure is an useful alternative for suppressing vibrations without requiring strategies of active control. The main characteristic of this type of strategy is to conveniently define the geometry and material of the structure. Although there are different techniques for designing periodic structures, these methods typically require a candidate structure for computing the desired band gap. Thus, if a specific target frequency (or frequency range or band gap) is required, these methods need to be solved repetitively for different candidate structures, until the desired result is achieved. In this context, the present article introduces an approach for designing periodic rods considering both geometric and material periodicity. A new equation is derived from the state vector notation and the longitudinal transmitted wave is examined in computing the vibration transmissibility. The proposed equation allows one to define a target frequency, for which the band gap is specified, and its solution provides two parameters which are used to design the periodic rod. Alternatively, the proposed approach allows verification of the frequency of minimum transmissibility for a pre-defined candidate structure. Numerical simulations and experimental tests are presented to demonstrate the approach. The results show that the proposed approach is a useful strategy for designing periodic structures.

A self-adaptive local diversity-preserving NSGA-II for the multidisciplinary design optimization of a miniaturized supersonic rocket

The miniaturized supersonic rocket or missile is an innovative concept most notably characterized by its small caliber, short length, and high flight speed. Tightly coupled design parameters and constrained objectives bring high complexity to launch safety assessments. The commonly used heuristic algorithm NSGA-II cannot address this complexity with its original density estimation strategy. In this paper, a multidisciplinary design optimization (MDO) based on a multidisciplinary feasible (MDF) architecture is established and simplified according to specific design requirements. The design system includes one coupled numerical model, two drivers, and six disciplines. As an optimizer for an MDO problem, multi-objective evolutionary algorithms (MOEAs) with heuristic features are very conducive to exploring the performance of complex rocket systems. The coupling relationship between the design variables of a small dual-chamber rocket is complex, and its optimal design is challenging to obtain empirically by traditional methods. Optimizing its propulsion performance and launch safety is imperative. For engineering designs, the convergence process of algorithms is often passive with a high degree of randomness, and the diversity of the final results is difficult to guarantee. This paper improves the Pareto front's diversity in designing a miniaturized supersonic rocket by using a self-adaptive local diversity-preserving NSGA-II (SLDNSGA-II) in an MDO framework with an active control strategy.

Optimal yaw strategy and fatigue analysis of wind turbines under the combined effects of wake and yaw control

Yaw control is one of the most important farm-level active control strategies with the aim of power maximization and load mitigation. However, improper yaw strategies may induce a significant load increase on wind turbines (WTs) although a power enhancement can be achieved. Therefore, it is essential to conduct a comprehensive fatigue analysis of wind turbines under yaw control before proposing an optimal yaw control strategy. In this study, fatigue analysis of WTs under shear flow is conducted first under various environmental and yaw conditions. Bending moments at not only blade root and yaw bearing, but also non-rotating component like tower base are investigated. Furthermore, various wake conditions including both full wake and partial wake are generated to explore the combined effects of wake flow and yaw control. Different load trends and variation rates are obtained in the analysis. To determine the optimal yaw angle at different practical inflow and yaw conditions, a cost function is proposed by using resultant bending moments and further integrating loads at different components together. The results show that efficient yaw ranges all appear in the positive yaw direction and optimal yaw angle increases with the increase of inflow speeds. The comprehensive fatigue analysis and the proposed cost function for optimal yaw control in this work are expected to contribute to the research and applications of multi-objective active yaw control strategies and therefore to increase total power output while extending operation lifetime of wind turbines.

Analytical modelling of transient thermal characteristics of precision machine tools and real-time active thermal control method

Thermal error is one of the primary factors affecting the machining accuracy of precision machining tools. Therefore, it is important to study the transient thermal characteristics of machine tools and the thermal-error control strategies. Thus far, a transient analytical modelling method for characterising the thermal characteristics of machine tools was proposed and an active error control strategy was provided. First, temperature-field modelling was conducted using an analytical method based on the Fourier series method and partial differential equations of heat conduction. Second, using the derived temperature field, the thermal deformation field was calculated based on finite element theory. Subsequently, the continuous real-time effect of the thermal power per unit heat source on the temperature and deformation fields of precision machine tools was studied. The proposed analytical modelling method not only predicts the machine tool heat deformation based on the working conditions of the heat source, but also matches the thermal control source power with the demand of the machine tool heat deformation. The optimal real-time power of the thermal control source is dynamically iterated and matched, such that the thermal deformation caused by the heat and thermal control sources can be balanced in real time at the displacement control point. Finally, the volumetric thermal error was actively controlled by adjusting the temperature field of the machine tool.The simulated and experimental results indicate that the transient analytical model can accurately predict the real-time thermal characteristics of the machine tool and that the real-time active thermal control method can effectively reduce volumetric thermal errors. Using active thermal control, the squareness error in the YZ-plane was reduced by approximately 45%, the spindle thermal elongation was reduced from 23 μm to 7 μm, and the volumetric thermal error in the X, Y, and Z directions were reduced by approximately 16, 14, and 17 μm, respectively.

Adaptive Backstepping Integral Sliding Mode Control for 5DOF Barge-Type OFWT under Output Constraint

This article presents a new control solution for a dynamical model of a translational oscillator with a rotational actuator (TORA) based on multi-body dynamics for a barge-type offshore floating wind turbine (OFWT). TORA has been employed as an active structural control strategy. The solution of bounding the output movements of platform pitch and tower bending angle to a certain limit, along with mitigating the OFWT vibrations due to environmental disturbances and uncertainties, is presented in this novel control framework. This new control algorithm consists of a high-gain observer (HGO)-based adaptive backstepping integral sliding mode control (ISMC) and a barrier Lyapunov function (BLF). This guarantees satisfying the constraints on the states and effectively resolves the problem of the unavailability of the system states. The proposed control law based on the BLF has been compared with an adaptive backstepping ISMC to show the efficiency of the output-constraint control scheme. Through MATLAB/SIMULINK numerical simulations and their numeric error table, the effectiveness of the proposed control scheme has been examined. The results confirm the validity and efficiency of the proposed control approaches.

Decoupling active disturbance rejection trajectory-tracking control strategy for X-by-wire chassis system

Abstract. Due to the inherent dynamic coupling between mechanical components such as the steering system and suspension system, the vertical external input will affect the lateral movement of the chassis, which makes it difficult to track the ideal trajectory when complex excitation conditions exist. To solve the abovementioned problems, the X-by-wire chassis is taken as the research object in this work, and the coupling dynamic model is established. Then, based on proving the reversibility of the coupling dynamic model, a pseudo-linear composite system is proposed to decouple the lateral and vertical signals of the chassis system. Next, the decoupling active disturbance rejection (DADR) trajectory-tracking control strategy is proposed. And a multi-objective optimization method of the bandwidth parameters of the DADR trajectory-tracking controller is proposed according to its convergence conditions. Experiments show that the proposed control strategy can effectively suppress the vehicle roll and yaw motion caused by the lateral–vertical dynamic coupling in the process of trajectory tracking to realize the accurate tracking of the ideal trajectory.