Control Scheme Research Articles

A PI+R Control Scheme Based on Multi-Agent Systems for Economic Dispatch in Isolated BESSs

A PI+R Control Scheme Based on Multi-Agent Systems for Economic Dispatch in Isolated BESSs

Harmonics Suppression and Stability Improvement for Power Router in Nonideal Grid Conditions: A Multiport Passivity-Based Collaborative Control Scheme

Harmonics Suppression and Stability Improvement for Power Router in Nonideal Grid Conditions: A Multiport Passivity-Based Collaborative Control Scheme

Specified time dual-group synchronization of uncertain complex chaotic systems

Aiming at the specified time dual-group synchronization problem of multi-wing complex chaotic systems containing uncertain terms and external disturbances, a new specified-time sliding mode control scheme is proposed, which directly synchronizes the complex chaotic system without separating the real and imaginary parts of the complex chaotic system. First, a new specified time stability criterion is used to construct the integral sliding mode surface of the synchronous error system to ensure stable sliding motion within the specified time. Subsequently, a proximity controller is designed to drive the error system to reach and remain on the sliding surface within another specified time, thereby achieving specified-time synchronization. In order to realize the proposed stability concept, this paper introduces a new sliding surface and defines the corresponding control law and adaptive rate. The effectiveness of this scheme is proved through Lyapunov stability theory and specified time stability theory. Numerical simulation results show that the scheme has strong robustness to uncertainties and external disturbances, and the controller is not affected by internal uncertainties and external disturbances. Compared to other stabilization time control schemes, this scheme has a shorter synchronization time. In general, this study introduces complex variables and adopts a scheme in which sliding mode surface parameters and controller parameters can be preset to simultaneously achieve dual-group synchronization of two groups of complex chaotic systems within the complex domain. This study offers greater flexibility, presenting novel ideas and approaches for the synchronization control of complex systems. It holds significant theoretical and practical value, providing valuable references and insights for research and applications in related fields.

Adaptive Nonsingular Fast Terminal Sliding Mode Control for Shape Memory Alloy Actuated System

Due to its high power-to-weight ratio, low weight, and silent operation, shape memory alloy (SMA) is widely used as a muscle-like soft actuator in intelligent bionic robot systems. However, hysteresis nonlinearity and multi-valued mapping behavior can severely impact trajectory tracking accuracy. This paper proposes an adaptive nonsingular fast terminal sliding mode control (ANFTSMC) scheme aimed at enhancing position tracking performance in SMA-actuated systems by addressing hysteresis nonlinearity, uncertain dynamics, and external disturbances. Firstly, a simplified third-order actuator model is developed and a variable gain extended state observer (VGESO) is employed to estimate unmodeled dynamics and external disturbances within finite time. Secondly, a novel nonsingular fast terminal sliding mode control (NFTSMC) law is designed to overcome singularity issues, reduce chattering, and guarantee finite-time convergence of the system states. Finally, the ANFTSMC scheme, integrating NFTSMC with VGESO, is proposed to achieve precise position tracking for the prosthetic hand. The convergence of the closed-loop control system is validated using Lyapunov’s stability theory. Experimental results demonstrate that the external pulse disturbance error of ANFTSMC is 8.19°, compared to 19.21° for the comparative method. Furthermore, the maximum absolute error for ANFTSMC is 0.63°, whereas the comparative method shows a maximum absolute error of 1.03°. These results underscore the superior performance of the proposed ANFTSMC algorithm.

Generative AI-Enabled Energy-Efficient Mobile Augmented Reality in Multi-Access Edge Computing

This paper proposes a novel offloading and super-resolution (SR) control scheme for energy-efficient mobile augmented reality (MAR) in multi-access edge computing (MEC) using SR as a promising generative artificial intelligence (GAI) technology. Specifically, SR can enhance low-resolution images into high-resolution versions using GAI technologies. This capability is particularly advantageous in MAR by lowering the bitrate required for network transmission. However, this SR process requires considerable computational resources and can introduce latency, potentially overloading the MEC server if there are numerous offload requests for MAR services. In this context, we conduct an empirical study to verify that the computational latency of SR increases with the upscaling level. Therefore, we demonstrate a trade-off between computational latency and improved service satisfaction when upscaling images for object detection, as it enhances the detection accuracy. From this perspective, determining whether to apply SR for MAR, while jointly controlling offloading decisions, is challenging. Consequently, to design energy-efficient MAR, we rigorously formulate analytical models for the energy consumption of a MAR device, the overall latency and the MAR satisfaction of service quality from the enforcement of the service accuracy, taking into account the SR process at the MEC server. Finally, we develop a theoretical framework that optimizes the computation offloading and SR control problem for MAR clients by jointly optimizing the offloading and SR decisions, considering their trade-off in MAR with MEC. Finally, the performance evaluation indicates that our proposed framework effectively supports MAR services by efficiently managing offloading and SR decisions, balancing trade-offs between energy consumption, latency, and service satisfaction compared to benchmarks.

Dynamic Analysis and Optimal Control of a Fractional Order Fishery Model with Refuge and Protected Area

In this paper, a mathematical analysis of fractional order fishery model with stage structure for predator is carried out under the background of prey refuge and protected area. First, it is demonstrated that the solution exists and is unique. The paper aims to analyze predator-prey dynamics in a fishery model through the application of fractional derivatives. It is worth emphasizing that we explicitly examine how fractional derivatives affect the dynamics of the model. The existence of each equilibrium point and the stability of the system at the equilibrium point are proved. The theoretical results are proved by numerical simulation. Alternatively, allocate harvesting efforts within an improved model aimed at maximizing economic benefits and ecologically sustainable development. The ideal solution is obtained by applying Pontryagin’s optimal control principle. A large number of numerical simulations show that the optimal control scheme can realize the sustainable development of the ecosystem.

Robust Control Scheme for Optimal Power Sharing and Selective Harmonic Compensation in Islanded Microgrids

In power systems, nonlinear loads cause harmonic distortion, adversely affecting sensitive equipment such as induction motors, power electronics, and variable-speed drives. This paper presents a novel control strategy that integrates with existing hierarchical control systems to mitigate voltage imbalances and harmonic disturbances in AC-islanded microgrids. The proposed method utilizes selective harmonic order filtering through multiple second-order generalized integrators (MSOGI) to extract negative, positive, and harmonic order components. The distributed generation (DG) unit control mechanism is designed to immediately correct voltage imbalances and harmonic disruptions, distributing the compensatory load evenly to rectify real and reactive power imbalances and harmonic disturbances. The microgrid’s control architecture primarily includes droop controllers for real and reactive power of positive sequences, voltage and current regulation inner control loops, an additional loop for correcting imbalances and harmonics, and secondary controllers to maintain voltage magnitude and frequency at nominal levels, ensuring high-quality voltage at the point of common coupling (PCC). The effectiveness of this approach is demonstrated through simulation results on the MATLAB/Simulink platform, proving its ability to effectively mitigate voltage imbalances and harmonic issues with the total harmonic of voltage reduced to approximately THDv = 0.5% and voltage unbalance factor (VUF) within approximately 0.1%.

Low Vibration Control Scheme for Permanent Magnet Motor Based on Resonance Controllers

For an electric locomotive traction motor, it is necessary to maintain relatively low vibration and noise due to the higher design standards. By using effective motor control strategies and implementing current harmonic suppression schemes, motor efficiency and vibration and noise suppression can be effectively improved. This study investigates the current harmonic suppression strategy for permanent magnet synchronous motors by (1) constructing a mathematical model of the permanent magnet motor to explore the sources of low-order harmonics currents such as fifth and seventh harmonics, as well as high-order harmonics at switch frequencies and their multiples, and analyzing the electromagnetic force characteristics generated by the current, and (2) establishing a vector control system for the permanent magnet motor. To suppress the fifth and seventh harmonic components in the current, a resonance controller is constructed, which utilizes the parallel connection of a resonator and PI controller to achieve low-order harmonic suppression. The factors affecting the effectiveness of the resonance controller’s suppression are also analyzed. The experiments are conducted, and the current harmonic suppression scheme constructed in this study can effectively reduce the harmonics in the current, thereby reducing motor vibration and noise.

Adaptive finite time command filtered backstepping control scheme of uncertain strict-feedback nonlinear systems

This paper proposes an adaptive finite time command filtered backstepping control scheme for single‐input and single‐output (SISO) uncertain strict-feedback nonlinear systems. The problem of the explosion of complexity existing in the adaptive backstepping control design and the singularity problem are solved by using the proposed adaptive finite time control method. In addition, the compensating signals are introduced to deal with the effect of the known filtering errors caused by the command filters. By using the finite time Lyapunov stability theory, the proposed adaptive finite time control strategy guarantees that all the signals in the closed-loop system are practical finite time stable, and the tracking errors converge to an arbitrarily small neighbourhood of the origin in finite time. Simulation and experimental results of the DC-DC buck converter are given to illustrate the effectiveness of the proposed adaptive finite time control scheme.

Non‐linear coordinated control of LPMG‐based direct drive wave energy conversion system with supplementary energy storage system based on feedback linearization

AbstractThe linear permanent magnet generator (LPMG)‐based direct drive wave energy conversion system (DDWECS) works under perpetual fluctuations of ocean waves. Short‐term energy storage, such as electrochemical energy storage, is usually adopted in a supplementary energy storage system (SESS) to buffer power fluctuations. Since the investigated DDWECS consists of various non‐linear components such as insulated gate bipolar transistors (IGBTs)‐based power electronic converters, the unremitting changes of system working conditions caused by ocean wave effects will degrade the dynamic performance with conventional linear controllers which are implemented via local linearization around a single working condition. This paper proposes the multiple feedback linearization based non‐linear coordinated control (MFLNCC) scheme for coordinating non‐linear plants in DDWECS with SESS such as the machine‐side converter (MSC), the grid‐side converter (GSC) and DC/DC converter in SESS. The enhanced dynamic performance of the proposed MFLNCC in DDWECS with SESS is validated under different scenarios.

Adaptive dynamic programming–based fault-tolerant control of multi-UAV formation system

With the increasing utilization of unmanned aerial vehicle (UAV) swarms in civilian and military field applications, it is crucial to eliminate the potential impacts of UAV faults on task completion and efficiency. To address this issue, the present paper investigates a fault-tolerant control scheme based on the adaptive dynamic programming (ADP) method and fault observer. The whole closed-loop system is composed of a position loop and an attitude loop. An ADP-based position-tracking controller is established with an improved cost function that can simultaneously represent actuator faults, control inputs, and tracking errors. In addition, a single-layer critic neural network is constructed to estimate the cost function and approximate control inputs. In the process of adjusting the weights of the neural network, a unique adjustment method combining policy gradient and prioritized experience replay is adopted to improve the data usage efficiency and speed up the weight convergence. Furthermore, a sliding mode–based attitude controller is utilized for the inner-loop attitude subsystem. The significant feature of this scheme is that it has the ability to self-learn and self-adapt. A Lyapunov stability analysis is performed to verify whether the signals are uniformly ultimately bounded. Finally, simulation experiments are conducted to demonstrate the effectiveness of the proposed scheme.

[formula omitted] load frequency control of multi-area power systems with multi-time-varying delays against deception attacks via a sliding mode control strategy

This article mainly addresses the H∞ load frequency control issue for multi-area power systems with multi-time-varying delays, where a sliding mode control scheme is developed to make the objective system more robust. Considering that the data transmission from the sensor to the controller in the channel may be vulnerable to malicious attacks, the deception attacks are taken into account in the controller design to ensure data authenticity while maintaining the system performance. By constructing a system model regarding multi-time-varying delays in multi-area power systems, this article aims to design a reliable sliding mode controller that guarantees the objective system asymptotic stability with an expected H∞ performance. Then, through the linear matrix inequality technology, sufficient conditions with less conservativeness maintaining the system asymptotic stability with a set of proper controller gains are established.Finally, a two-area interconnected power system is used to validate the presented method.

An efficient tracking differentiator based active disturbance rejection control for flight environment simulation system

The flight environment simulation system plays a crucial role in aeroengine testing, replicating real mission pressure and temperature conditions. However, existing systems face challenges in handling strong measurement noises and total disturbances during transient tests, leading to inaccurate simulations and potential actuator damage. To address these gaps, an enhanced tracking differentiator based active disturbance rejection control scheme is proposed and implemented. Our method introduces two key innovations: a discrete-time optimal control law that dynamically adjusts control inputs based on state transition and sampling times, and a phase-advancing method that mitigates filtering phase delays by incorporating derivative signals to predict input trends. These components are integrated into a novel tracking differentiator, enhancing the estimation capability of the extended state observer in active disturbance rejection control. Frequency-domain analysis demonstrates the proposed tracking differentiator's superior filtering performance and phase quality. Simulations of intake environment pressure during aeroengine transient tests reveal that, compared to traditional tracking differentiator-based active disturbance rejection control, the proposed approach significantly reduces both control signal oscillations and setpoint deviations by 75.44% and 53.9%, respectively. These improvements effectively address environment simulation deviations and unnecessary actuator wear, thereby enhancing the accuracy and reliability of aeroengine testing.

Backlash size identification for servomechanisms with gear transmission devices

Backlash refers to the spaces between the gear teeth in a transmission device for the purpose of lubrication and accommodating thermal expansion of the gears. This space gets wider with time due to wear on machine components, leading to tracking errors on the load side as well as vibration within the system. If the backlash size can be identified by known information, it can not only be used as an index of a maintenance strategy, but also used in a control scheme to compensate for the effects of the backlash. As a result, this paper proposes an approach for identifying the backlash size using actuator-side information only. In the proposed approach, the timing of a backlash event is determined by a Hilbert-Huang Transform-based method to find the instant in time wherein the actuator side and the load side disengage, while the inertia and friction are identified by a 2-step method. Backlash size can be estimated by integrating the velocity difference between the actuator side and the load side. Experimental results verify the effectiveness of the proposed backlash size estimation method.

Comparison of Configurable Modular Two-Level and Three-Level Isolated Bidirectional DC–DC Converters for Super-Capacitor Charging in DC Shore Power Systems

Compared to the AC counterpart, the DC shore power system provides a significant advantage of efficient power supply from renewable sources to ships and onshore loads. Super-capacitors serve as key energy storage units in such a system to buffer the power fluctuations and collect the regenerative energy. However, the ultra-wide voltage range of super-capacitors imposes a significant challenge in the topology selection and efficiency optimization of the interfacing isolated bidirectional DC–DC converter. To tackle this challenge, this paper analyzes and compares two promising converter topologies, which are a configurable modular two-level dual-active bridge (CM-2L-DAB) and a three-level dual-active bridge (3L-DAB). To facilitate an ultra-wide voltage range, extended phase-shift (EPS) modulation in conjunction with the topology reconfiguration is analyzed for the CM-2L-DAB, while a hybrid modulation scheme is proposed for the 3L-DAB. A unified design approach is provided for both topologies, which also yields to the power loss modeling. On this basis, the CM-2L-DAB and 3L-DAB are thoroughly compared in terms of the modulation schemes, current stress, soft-switching operation, power conversion efficiency, material usage, closed-loop control scheme, and reliability. A prominent conclusion can be drawn that the CM-2L-DAB provides a higher efficiency than the 3L-DAB over the whole voltage range, but it relies on additional relays to reconfigure its topology which results in lower reliability and dynamic performance than the 3L-DAB.

Dynamical analysis, control, boundedness and prediction for a fractional-order financial risk system

Abstract This paper delves into the dynamical analysis, chaos control, Mittag-Leffler Boundedness (MLB) and forecasting a Fractional-Order Financial Risk (FOFR) system through an absolute function term. To this end, the FOFR system is first proposed, and the Adomian Decomposition Method (ADM) is employed to resolve this fractional-order system.The stability of equilibrium points and the corresponding control schemes are assessed, and several classical tools such as Lyapunov Exponents (LE), Bifurcation Diagrams, Complexity Analysis (CA), and 0-1 test are further extended to analyze the dynamical behaviors of FOFR. Then the global Mittag-Leffler Attractive Set (MLAS) and Mittag-Leffler Positive Invariant Set (MLPIS) for the proposed Financial Risk (FR) system are discussed. Finally, a proficient reservoir-computing (RC) method is applied to forecast the temporal evolution of the complex dynamics for the proposed system, and some simulations are carried out to show the effectiveness and feasibility of present scheme.

Urban environmental regulation, firms’ emission reduction strategies and labor demand: Evidence from China

Air pollution affects people's livelihoods, and China's environmental governance is a defensive battle that must be fought. Combining several comprehensive datasets, this study uncovers the underlying mechanisms of urban environmental regulation that affect labor demand from the perspective of firms’ choice of emission reduction strategies. Utilizing a difference-in-differences method, this study finds that on average, the Key City Demarcation Scheme for Air Pollution Prevention and Control (KCDS) has a drive-out effect on employment while improving urban environmental quality, making it difficult to achieve the double-dividend of de-pollution and employment promotion. These conclusions still hold after considering various specification checks, including the instrumental variable method. Underlying mechanisms indicate that manufacturing firms strengthen both front-end productive “changes-in-process” and non-productive “end-of-pipe” treatment to respond to stricter urban environmental enforcement, and ultimately, KCDS has triggered a drive-out effect on employment. Heterogeneous effects investigate that firms’ emission reduction strategies have path dependence and that the drive-out effect on employment is particularly pronounced for large-scale, technology- and capital-intensive domestic firms in large cities. This study provides policy insights for the smooth realization of the urban green transformation while safeguarding the livelihood of society.

AC loss optimization of high temperature superconducting magnetic energy storage considering energy management strategies in a hydrogen-battery system

Hydrogen-battery systems have great potential to be used in the propulsion system of electric ships. High temperature superconducting magnetic energy storage (HTS-SMES) has the advantages of high-power density, fast response, and high efficiency, which greatly reduce the dynamic power response of hydrogen-battery systems. Although a superconductor has zero-resistance during direct current operation, considerable alternating current (AC) loss is generated in superconducting coils during charging and discharging operations, which reduces the overall efficiency of the system and increases the quench risk of superconducting coils. Therefore, it is essential to analyze and optimize the AC loss of SMES during the design and optimization of a hydrogen-battery-SMES system. In this work, the AC losses of SMES in a hydrogen-battery-SMES system is studied under three energy management strategies, proportional-integral (PI) control, fuzzy logic, and the equivalent hydrogen consumption minimization strategy. The results show that the high fluctuation of load power can cause significant increases of AC losses in SMES. The fuzzy logic management method has the lowest AC loss among the three strategies. An orthogonal experimental method is presented to optimize the SMES structure. A control strategy based on a neural network is proposed to minimize the AC loss in SMES. Compared with PI control, the SMES AC loss can be reduced by up to 64.2 % using the proposed control scheme.

Distributed-observer-based adaptive fault tolerant formation maneuver for autonomous surface vehicles under stochastic cyber-attack

This paper investigates the distributed adaptive fault-tolerant formation maneuver control strategy for multiple autonomous surface vehicles (ASVs) systems subject to stochastic cyber-attack and actuator failures. Existing works have provided solutions against continuous attacks on communication channels while ignoring the increasingly prevalent intermittent attacks. Compared to the former, the latter are more challenging to detect, having been insufficiently described and addressed. Motivated by this observation, this article is concerned with the stochastic intermittent injection attacks, which are modeled as stochastic impulsive sequences, characterized by stochastic injection instant and intensity, leading to unpredictable changes in the state information transmitted by the neighbors. Taking this dilemma into consideration, a novel distributed observer is proposed, capable of effectively observing the target formation even in the presence of stochastic intermittent injection attacks. Meanwhile, a large feedback gain is incorporated into the observer to reduce the impact of attacks on system stability. A linear sliding manifold, together with the adaptive algorithm, is utilized to construct a fault tolerant control architecture for each follower ASV without employing model parameters which can confront the embarrassing scenario of actuator failures. Eventually, theoretical deduction and numerical simulations are conducted to confirm the feasibility of the proposed collaborative control scheme.

Force-Field based assisted control for upper-limb rehabilitation robots

Robot-assisted training with an assist-as-needed (AAN) control strategy has been used in clinical investigations to effectively enhance the subject’s active effort and promote the rehabilitation of individuals with upper-limb motor impairment. In this paper, a force field-based AAN control scheme is proposed for robot-assisted upper limb rehabilitation training and then implemented in a robot-assisted rehabilitation training system (RaRTS). A spatial varying assistance force field is constructed around the predetermined trajectory in this scheme, and then a varying force field coefficient based on the subject’s motor performance is adopted to deliver the AAN features with temporal freedom. The normal force field, tangential force field, and viscous force field are the three components of the constructed spatial varying assistance force field. Furthermore, the proposed scheme contains three training modes that are switched according to the subject’s trajectory tracking error. Finally, task-oriented continuous training experiments with different force field factors are conducted on able-bodied subjects to evaluate and validate the performance and feasibility of the proposed scheme. Preliminary experimental results and statistics analysis suggest that the subjects were able to keep much closer to the predetermined trajectory through an appropriate selection of force-field assistance factors. Furthermore, the robot would apply an assistance force as needed as the motor performance deteriorate, which could prevent the subject from losing confidence due to poor performance.