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In response to the escalating challenges of rapid load fluctuations and intricate operating environments, supercritical power units demand enhanced control efficiency and adaptability. To this end, this study introduces a novel model predictive hybrid PID control strategy that integrates PID with model predictive control (MPC), leveraging the operational characteristics of multi-loop systems. The proposed strategy adeptly marries the swift response of PID controllers with the foresight and optimization capabilities of MPC. A dynamic model of a supercritical unit is constructed using the subspace identification method. The model's high precision is confirmed by its alignment with field data. Load change simulations demonstrate that the PID–MPC hybrid controller shows faster response times and more precise tracking capabilities compared to the feedforward-PID strategy. It achieves substantial improvements in the IAE index for three loops, with increases of 29.2%, 54.1%, and 57.3% over the feedforward-PID controller. An energy-saving performance analysis indicates that the proactive control actions of both the PID–MPC and MPC strategies lead to dynamic exergy efficiency and coal consumption rates with a broader range of dynamic process changes. The disturbance scenario simulation regarding the proposed controller achieves faster settling times and minimizes control deviation compared to the traditional controller. [ABSTRACT FROM AUTHOR]

The goal of this study is to look into a control approach for a micro-grid hybrid power conversion system that integrates multiple power sources and transformers to meet continuous load requirements under a variety of naturalistic settings. The study's key discoveries include the construction of an autonomous model with intelligent control methodologies, as well as a dynamic framework for a hybrid renewable energy system that includes photovoltaic (PV), fuel cells (FC), and wind turbines (WT). This study is unique in that it integrates alternate energy sources with FC devices using short- and long-term storage methods made possible by adaptive-intelligent power controllers. The research also focuses on improving mathematical and electrical models, which are developed in the MATLAB, Simulink, and Sim Power Systems environments. The study's key result is that an Adaptive Neuro-Fuzzy Inference System (ANFIS) is effective at adjusting load voltage in response to changing environmental and load conditions. In comparison to conventional Proportional-Integral-Derivative (PID) control, ANFIS reduces settling time by 68 %. In addition, when compared to an optimal PID controller based on the Cuckoo Search Algorithm (CSA), ANFIS reduces settling time by 60 %. In general, the study advances the area by presenting an intelligent control method for optimizing the performance of hybrid renewable energy systems, increasing efficiency, and minimizing settling time using ANFIS-based control mechanisms.

Range extender hybrid vehicles have the advantages of better dynamics and longer driving range while reducing pollution and fuel consumption. This work focuses on the control strategy of an Auxiliary Power Unit (APU) operating in power generation mode for a range-extender mixer truck. When an operating point is switched, the engine speed and generator torque of the APU will switch accordingly. In order to ensure APU fast and stable adjustment to meet the power demand of the vehicle as well as operate at the lowest fuel consumption, a fuzzy adaptive PID coordination control strategy based on particle swarm optimization (PSO) is proposed to control the APU. The optimal operating curve of APU is calculated by coupling the engine and generator first. Then, the adaptive PID algorithm is used to control the speed and torque of the APU in a dual closed loop. The PSO is used to optimize the PID control parameter. Through hardware-in-the-loop tests under different working conditions, the control strategy is verified to be effective and real-time. The results show that the proposed control strategy can coordinate the operating of engine and generator and control the APU to track target power stably and quickly under minimum fuel consumption. Compared with traditional PID control strategy, the overshoot, regulation time and steady-state error are reduced by 55.1%, 11.1% and 77.3%, respectively. [ABSTRACT FROM AUTHOR]

A single-phase grounding fault often occurs in 10 kV distribution networks, seriously affecting the safety of equipment and personnel. With the popularization of urban cables, the low-resistance grounding system gradually replaced arc suppression coils in some large cities. Compared to arc suppression coils, the low-resistance grounding system features simplicity and reliability. However, when a high-resistance grounding fault occurs, a lower amount of fault characteristics cannot trigger the zero-sequence protection action, so this type of fault will exist for a long time, which poses a threat to the power grid. To address this kind of problem, in this paper, a hybrid grounding system combining the low-resistance protection device and fully controlled power module is proposed. During a low-resistance grounding fault, the fault isolation is achieved through the zero-sequence current protection with the low-resistance grounding system itself, while, during a high-resistance grounding fault, the reliable arc extinction is achieved by regulating the neutral-point voltage with a fully controlled power module. Firstly, this paper introduces the principles, topology, and coordination control of the hybrid grounding system for active voltage arc extinction. Subsequently, a dual-loop-based control method is proposed to suppress the fault phase voltage. Furthermore, a faulty feeder selection method based on the Kepler optimization algorithm and convolutional neural network is proposed for the timely removal of permanent faults. Lastly, the simulation and HIL-based emulated results verify the rationality and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This research deals with multi-UAV systems to track partially observable multi-targets in noisy threedimensional environments, which are commonly encountered in defense and surveillance systems. It is a far extension from previous research which focused mainly on two-dimensional, fully observable, and/or perfect measurement settings. The targets are modeled as linear time-invariant systems with Gaussian noise and the pursuers UAV are represented in a standard six-degree-of-freedom model. Necessary equations to describe the relationship between observations regarding the target and the pursuers states are derived and represented as the Gauss-Markov model. Partially observable targets require the pursuers to maintain belief values for target positions. In the presence of a noisy environment, an extended Kalman filter is used to estimate and update those beliefs. A Decentralized Multi-Agent Reinforcement Learning (MARL) algorithm known as soft Double Q-Learning is proposed to learn the coordination control among the pursuers. The algorithm is enriched with an entropy regulation to train a certain stochastic policy and enable interactions among pursuers to foster cooperative behavior. The enrichment encourages the algorithm to explore wider and unknown search areas which is important for multi-target tracking systems. The algorithm was trained before it was deployed to complete several scenarios. The experiments using various sensor capabilities showed that the proposed algorithm had higher success rates compared to the baseline algorithm. A description of the many distinctions between two-dimensional and three-dimensional settings is also provided. [ABSTRACT FROM AUTHOR]

Virtual coupling of urban rail train sets represents a cutting-edge frontier in urban rail transit research, with the goal of improving operational efficiency of trains on the existing lines, particularly in the starting and stopping stages. This paper proposes an efficient collaborative control system for virtual coupling. Firstly, a model was constructed to simulate relative braking between urban rail train sets and it was used to generate relative braking distances between trains virtually coupled. Next, an efficient starting and stopping objective function was constructed at the collaborative control layer, and an optimized controller was devised to solve the objective function under constraints, generating key decision-making information for the leading and following trains during the starting and stopping stages. Subsequently, this study focused on the operation sequence planning technology, yielding the executable operation sequences of the leading and following trains, respectively. Finally, an LQR controller was designed, enabling the accurate following and control of operation sequences and the generation of execution instructions. Simulation results showed that the proposed control system for virtual coupling could achieve a parking time interval of less than 1.6s between the leading and following trains in urban rail transit within a speed range of 0~60 km/h, effectively improving the operational efficiency of virtually coupled urban rail train sets during the starting and stopping stages.

• The 6-DOF attitude-orbit coupled model of SFF is established. The model has no redundant state and can be achieved globally without singularity. • A FxTDO is developed to estimate the external disturbance. Any prior knowledge of the disturbance is not required. The estimation error of the disturbance can converge to zero in fixed time regardless of the initial states. • A composite control scheme which consists of the NFFTSM surface and a feed-forward term based on the FxTDO is proposed such that each follower spacecraft can track the desired positions and attitudes in fixed time. This paper presents a distributed fixed-time control protocol for 6-DOF(degree-of-freedom) attitude-orbit coupled spacecraft formation flying with external disturbances. Firstly, the 6-DOF attitude-orbit coupled dynamics is established. The communication topology between the spacecraft in the formation is described by a directed graph. Secondly, a fixed-time disturbance observer (FxTDO) is designed to ensure that the estimation errors of the unknown external disturbances can converge to zero in fixed time. Thirdly, based on non-singular fixed-time terminal sliding mode (NFFTSM) surface, the fixed-time coordination control protocol is proposed combined with the fixed-time disturbance observer, which can guarantee that each spacecraft can track their desirable positions and attitudes in fixed time. The stability of the closed-loop system is proved through Lyapunuov method. Finally, simulation results for a formation with one virtual leader and five followers demonstrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

With the development of distribution generation (DG) technology, large amount of renewable energy connected to the microgrid, which has a significant impact on the consumption of renewable energy. The nonlinear load connected to the microgrid leads to the reduction of power quality, and the line impedance between the distribution generation and the point of common coupling (PCC) is different, resulting in the harmonic current cannot be reasonably shared, and the transmission of redundant information brings enormous pressure to communication system. To solve these problems, this paper proposed a microgrid harmonic power-sharing method based on an event-triggered consensus algorithm. Firstly, the hierarchical coordination control architecture of the microgrid is established. Then, when designing distributed frequency and harmonic power controllers based on event-triggered consensus, the impact of communication network time delay on system performance is considered. The status information is exchanged between distributed controllers only when the event is triggered, and the actual value is replaced by the estimated value at other times, which can effectively reduce the transmission of redundant information. Finally, this paper uses the Lyapunov method to prove the stability of the proposed control method, analyzes the event-triggered interval, and avoids the Zeno phenomenon. The effectiveness of the proposed power-sharing method is verified by the hardware-in-the-loop experiment. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper investigates the coordination control of large-scale systems (LSSs) with unknown external disturbances. The disturbances exist in the channels from the controllers to the actuators. To compensate the impact of disturbances, an extended observer using the output states is constructed, and an observer-based event-triggered controller is designed to save communication resources. Moreover, based on the event-triggering strategy, a controller using dynamic information estimation is designed, and Zeno behavior is further excluded. Finally, a DC micro-grid model is used for simulations to verify the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the procedure of carbon peaking and carbon neutrality energy revolution, large-scale renewable energy is aggrandizing frequency regulation capacity of power grid. How to make the best use of new rapid resources, represented by battery energy storage systems (BESS), in the secondary frequency regulation is the key to solve the problem. Firstly, a three-layer frame is designed, embodying area, cluster and plant, which can satisfy the needs for access monitoring and classification decision of various regulation resources in automatic generation control (AGC) system. Secondly, a coordination control strategy including BESS is proposed, and so is the strategy of regulation requirements assignment based on state of charge (SOC) effecting factor in BESS group. Finally, simulations are conducted for continuous disturbance cases from an actual power system, as well as simulations for tripping fault disturbances. The results show that the proposed strategy can improve the SOC consistency between the respective BESS, promoting the availability of BESS, and improve the performance of network frequency response characteristics either.

The connection of single-phase AC loads to a DC microgrid not only large secondary currents flowing into energy storage units with droop control cause, but also lead to secondary voltage ripples appeared on the DC bus, which seriously affects the normal operation of DC microgrids. In this paper, the secondary currents and voltages can be suppressed simultaneously by means of reconstructing the output impedances of energy storage converter and active capacitor converter. The main characteristics, impedance model, control strategies, and system stability in terms of secondary ripples are comprehensively investigated. Particularly, it is shown that the output impedance of the energy storage converter with droop control is relatively small and the input impedance DC loads buck converter are relatively large, so the secondary currents mainly flow into energy storage units and DC bus capacitor. Based on this, the output impedance of the energy storage converter and active capacitor converter are reconstructed relatively larger and smaller respectively, so the secondary currents mainly flowing into the active capacitor. Therefore, the secondary ripple currents flowing into energy storage units and the secondary ripple voltages appeared on the DC bus can be suppressed. Finally, the proposed methods are varied through simulations results.

Summary: Coordination control of multiple autonomous underwater vehicles (AUVs) has attracted considerable attention owing to its widespread applications in deep‐sea exploration, marine environment monitoring, regional searches, and detector recovery. In addition, finite‐time control theory is applied to ensure that the system achieves its control goal as soon as possible. To the authors' knowledge, few studies have systematically summarized the finite‐time coordination control of multiple AUV systems. Thus this review aims to systematically and completely introduce the research progress into the coordination control methods for multi‐AUV systems and their combination with finite‐time theory. The primary areas of focus are the research significance, present state, and prospects of coordination control and finite‐time control theory in multiple AUV systems, as well as their applications. [ABSTRACT FROM AUTHOR]

In this paper, a distributed cooperative control protocol is presented to deal with actuator failures of multi-agent systems in the presence of connectivity preservation. With the developed strategy, each agent can track the reference trajectory of the leader in the presence of actuator failures, disturbances and uncertainties. The connectivity of the multi-agent system can always be ensured during the control process. To achieve the aforementioned control objectives, a potential function is introduced to the distributed adaptive fault-tolerant control algorithm to preserve the initial connected network among the agents. The uncertainty of the multi-agent system, which is allowed to be described by discontinuous functions, is approximated and compensated using the fuzzy logic system. The asymptotic stability of the closed-loop system is demonstrated through the use of Cellina's approximate selection theorem of nonsmooth analysis. Due to the developed adaptive laws, the upper bound of the disturbance is allowed to be uncertain, which facilitates the implementation of the control scheme. Finally, simulation results are provided to verify the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Engineering Technology is the property of Editorial Department of Electric Power Engineering Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Summary Coordination control of multiple autonomous underwater vehicles (AUVs) has attracted considerable attention owing to its widespread applications in deep‐sea exploration, marine environment monitoring, regional searches, and detector recovery. In addition, finite‐time control theory is applied to ensure that the system achieves its control goal as soon as possible. To the authors' knowledge, few studies have systematically summarized the finite‐time coordination control of multiple AUV systems. Thus this review aims to systematically and completely introduce the research progress into the coordination control methods for multi‐AUV systems and their combination with finite‐time theory. The primary areas of focus are the research significance, present state, and prospects of coordination control and finite‐time control theory in multiple AUV systems, as well as their applications.

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract Background Coordinated control between the bilateral ankle joints plays an important role in performing daily life functions, such as walking and running. However, few studies have explored the impact of stroke on movement disorders that decrease the coordination control of the bilateral extremities and may decrease daily activities that require coordination control of the bilateral ankles. This study aimed to investigate the coordination control of the bilateral ankles using a novel bilateral ankle measurement system and evaluate the relationship of bilateral movement coordination control deficits with motor and functional performances of the lower extremities in patients with stroke. Methods Twenty-one healthy adults (36.5 ± 13.2 y/o) and 19 patients with chronic stroke (58.7 ± 10.5 y/o) were enrolled. A novel measurement device with embedded rotary potentiometers was used to evaluate bilateral ankle coordination control. Participants were asked to move their dominant (non-paretic) foot from dorsiflexion to plantarflexion position and non-dominant (paretic) foot from dorsiflexion to plantarflexion position (condition 1) simultaneously, and vice versa (condition 2). Alternating time and angle for coordination control with movements of both ankles were calculated for each condition. Motor and functional performance measurements of the lower extremities included the lower-extremity portion of the Fugl-Meyer assessment (FMA-LE), Berg Balance Test (BBS), Timed Up and Go Test (TUG), and Barthel Index (BI). Results Compared with the healthy group, alternating time was shorter in the stroke group by 8.3% (p = 0.015), and the alternating angles of conditions 1 and 2 were significantly higher than those of the healthy group by 1.4° (p = 0.001) and 2.5° (p = 0.013), respectively. The alternating angle in condition 2 showed moderate correlations with TUG (r = 0.512; p = 0.025), 10-m walk (r = 0.747; p

This paper is concerned with the anti-saturation control problem of a permanent magnet synchronous wind power system. By virtue of adaptive sliding mode control method and port-controlled Hamiltonian (PCH) control method, a new coordination controller is designed, which removes the input saturation effects and compensates the uncertainties of system model parameters. The controller takes the exponential function with parameters as the coordination function. By adjusting the parameters of coordination function, the designed coordination controller can respond to input saturation more quickly and improve the system’s dynamic performance. The effectiveness of the proposed strategy is demonstrated through simulations. The comparison results with the traditional control approach are also presented. It is shown that the proposed strategy can realize the speed tracking control of the generator and improve the maximum wind energy capture of wind turbine, so as to further improve the utilization efficiency of wind energy.

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Copyright of Electric Power is the property of Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Under the condition of unbalanced grid voltage, the non-off grid operation of photovoltaic system will lead to the fluctuation of system output power and obvious harmonic distortion of grid connected current. Because stable output power and better grid connected current quality cannot be realized at the same time, a coordinated control strategy of power fluctuation suppression and current balance is proposed. The harmonic component in the output current is adjusted by using the adjustment coefficient, and the proposed strategy is realized based on reduced order resonance control. The voltage/current positive and negative sequence separation link and phase-locked loop are not needed in this method so that the control structure is simpler, and instantaneous power is used to calculate the reference command value of grid connected current. The coordinated control of power/current is realized by MATLAB simulation, which verifies the feasibility and effectiveness of the proposed strategy.

This paper presents an adaptive coordination control strategy for path-following of distributed drive autonomous electric vehicles (DDAEV). A model predictive control (MPC) algorithm is used to realize path-following through autonomous steering, where the prediction time is adaptive in relation to different driving conditions. Due to the dynamic characteristic of distributed drive vehicle, the differential torque control is also utilized based on the deviation of path to realize path-following. In order to make full use of the advantages of these two path-following methods, coordination control of autonomous steering and differential steering is adopted to improve the transient response speed, flexibility of steering system and path-following performance by setting moving weight coefficients based on neural network. Results of CarSim-Simulink co-simulation and real vehicle experiment both verify that the proposed coordination control can obtain steering flexibility, as well as tracking accuracy and reliability under various driving conditions. [ABSTRACT FROM AUTHOR]

When the Parallel Hybrid Vehicle (PHV) wheel's torque is coordinated and controlled, the issue of coordination control of wheel torque under mode switching has some limitations. Therefore, the experiment proposed a novel wheel torque coordination control technique for parallel hybrid vehicles. The feedforward and feedback joint control technique of the Wheel Drive Torque (WDT) control algorithm may be used to implement the wheel torque drive control. The technique for the wheel braking Torque Control (TC) is applied to obtain the wheel braking torque through the Fuzzy PID controller (F-PID). A Dynamic Coordination Controller (DCC) is created and the engine output torque is adjusted using the PID control technique of wheel angular velocity difference. The motor provides the compensation torque. The deviation of the intended angular velocity from the actual angular velocity is adjusted intime to realize the wheel's dynamic coordination while being controlled by a mode switch. The results demonstrates that the reaction time of the proposed algorithm can be reduced to 0.08s; The overall output TC precision is improved by 11.1%. The precision of the predicted velocity of vehicle speed tracking has risen by 8.0%. The vehicle dynamics during the transition procedure is improved by 4.4%, which enhances the ride comfort and the PHV's power. [ABSTRACT FROM AUTHOR]

Background: Coordinated control between the bilateral ankle joints plays an important role in performing daily life functions, such as walking and running. However, few studies have explored the impact of stroke on movement disorders that decrease the coordination control of the bilateral extremities and may decrease daily activities that require coordination control of the bilateral ankles. This study aimed to investigate the coordination control of the bilateral ankles using a novel bilateral ankle measurement system and evaluate the relationship of bilateral movement coordination control deficits with motor and functional performances of the lower extremities in patients with stroke. Methods: Twenty-one healthy adults (36.5 ± 13.2 y/o) and 19 patients with chronic stroke (58.7 ± 10.5 y/o) were enrolled. A novel measurement device with embedded rotary potentiometers was used to evaluate bilateral ankle coordination control. Participants were asked to move their dominant (non-paretic) foot from dorsiflexion to plantarflexion position and non-dominant (paretic) foot from dorsiflexion to plantarflexion position (condition 1) simultaneously, and vice versa (condition 2). Alternating time and angle for coordination control with movements of both ankles were calculated for each condition. Motor and functional performance measurements of the lower extremities included the lower-extremity portion of the Fugl-Meyer assessment (FMA-LE), Berg Balance Test (BBS), Timed Up and Go Test (TUG), and Barthel Index (BI). Results: Compared with the healthy group, alternating time was shorter in the stroke group by 8.3% (p = 0.015), and the alternating angles of conditions 1 and 2 were significantly higher than those of the healthy group by 1.4° (p = 0.001) and 2.5° (p = 0.013), respectively. The alternating angle in condition 2 showed moderate correlations with TUG (r = 0.512; p = 0.025), 10-m walk (r = 0.747; p < 0.001), gait speed (r = − 0.497 to − 0.491; p < 0.05), length (r = − 0.518 to − 0.551; p < 0.05), and BI (r = − 0.457; p = 0.049). Conclusion: Stroke decreases alternating time, increases alternating angle, and shows bilateral ankle coordination control deficits temporally and spatially. A higher alternating angle is moderately to highly associated with motor function and lower limb function in patients with stroke. [ABSTRACT FROM AUTHOR]

The coordinated control method of Unmanned Electric Formula Racing (UEFC) was studied to improve the handling stability of UEFC. The UEFC's mechanical structure, which is based on the driving system and transmission system, was designed. In accordance with mechanical structure of the designed racing car, a seven-degree of freedom mathematical model of the UEFC was established. In accordance with the built mathematical model of racing car, the lateral controller of racing car was designed by using a fuzzy neural network method. The longitudinal controller of the racing car was designed by using the method of incremental PID control, and the coordination controller of the racing car was designed by combining the lateral controller and the longitudinal controller so as to realize the lateral and longitudinal coordination control of the UEFC. The experimental results showed that the output parameters such as yaw rate, vehicle speed and heading angle were slightly different from the expected output. It was confirmed that the research method can enhance the handling stability of the UEFC. [ABSTRACT FROM AUTHOR]

Human intelligence, cognition, and skills can be applied to robots to accomplish challenging tasks through cooperative control between humans and robots. In this article, we propose two control frameworks for the human teleoperation of multiple robots under undirected and directed graphs. The two control laws are considered for two cases: 1) when both the relative positions and velocities of the robots are available, and 2) when only the relative positions are available. In this article, we first propose a controller that integrates adaptive neural networks, task-space synchronization, and robust control to address several practical issues related to uncertainty in robotic systems, (e.g., model inaccuracy, time delay, and disturbance). Second, another control algorithm using only the relative position information is addressed by using distributed observers on the remote side. As a result, the system is proven to be stable, and the tracking errors of position and velocity are uniformly and ultimately bounded. Finally, the effectiveness of the proposed control algorithms is verified by experimental demonstration. [ABSTRACT FROM AUTHOR]

Accurate pattern transfer in wafer scanners necessitates the wafer stage and the reticle stage executing a coordinated motion with the synchronization error in terms of nanometers. In an attempt to cope with this challenging issue, a cross-coupling iterative learning control (ILC) with two inputs and two outputs is proposed and then decomposed into two ILC with the same convergence condition, a master–slave ILC for the reticle stage and an independent ILC for the wafer stage. To handle the inevitable stochastic disturbance, which inhibits the achievable ILC performance, an adaptive gain is involved in the proposed method for the sake of accelerated convergence as well as enhanced robustness. It remains constant or is decreased adaptively along the iteration axis, depending on the proportion that the stochastic term accounts for in the error signal. Moreover, a phase leader is chosen as the learning filter and tuned along with the initial learning gain by a frequency-domain approach. Experimental comparisons with existing close yet distinctive approaches highlight the effectiveness and superiority of the proposed method. [ABSTRACT FROM AUTHOR]

The present work describes a control methodology for a hybrid energy storage system (HESS) to improve its transient performance under dynamic load conditions. The proposed coordination control enhanced life cycle performance by segregating the power between battery energy storage systems (BESS) and a supercapacitor (SC). The BESS and SC are connected parallel to each other, and two individual DC–DC bidirectional converters connect them to a common DC bus. The coordination control is established between the controllers of BESS and the SC of HESS, which helps to utilise the usable energy capacity of the HESS. The charging/discharging current of the BESS is controlled within the allowable safety range based on the slope and magnitude of the BESS current. The high-frequency power component is handled by the SC, which helps to reduce the extra exhaustion on the BESS during operation with a higher current. The proposed coordination control of HESS is validated through simulation and the results show the effectiveness of the proposed controller.

The goal of “carbon peaking and carbon neutrality” puts forward higher requirements for low-carbon operation of power system considering security and stability. The large-scale access of new energy easily leads to problems such as uneven distribution of power flow and electromechanical oscillation. As the representative device of the third-generation flexible AC transmission system (FACTS), interline power flow controller (IPFC) is greatly capable of power flow control, damping control and transient stability control, but the main objectives of IPFC vary considerably under different working conditions, and there is contradiction between the goals. First, based on the improved relative gain matrix (MRGA) theory, the system state equation with IPFC was linearized, the interaction between targets was quantitatively analyzed, the superposition position of the additional controller was selected, and the interaction between steady-state control and dynamic control was weakened. Then, for the transient process, combined with fuzzy logic theory, the IPFC multi-objective coordinated controller was designed. Finally, the controller parameters were optimized using the particle swarm algorithm. While improving the transient stability and small disturbance stability, the controller reduced the power flow overshoot during the transient process and enhanced the coordinated control ability of IPFC under different system operating conditions. It was helpful to solve the problems of energy transmission and consumption, safety and stability control caused by the large load, low inertia, and random fluctuations of the power system under the “dual carbon” background.

In order to improve the traffic capacity of the intersection and shorten the traffic delay, a new urban intelligent traffic signal coordination control system based on machine learning is proposed in this paper. The hardware of the system is designed, including annunciator, vehicle detection module, traffic flow statistics module and signal control module. The reinforcement learning algorithm in machine learning is used to train and learn the traffic vehicle data, so as to extract the spatial characteristics of the traffic environment state. Under the constraint of the minimum loss function, the training objective is solved and the output result of the optimal coordinated control of traffic signals is output. The experimental results show that compared with the traditional control system, the maximum traffic capacity of the intersection under the control of this system is 2400 vehicles/hour, and the maximum traffic delay is no more than 30s. [ABSTRACT FROM AUTHOR]

This paper proposes a novel coordination control strategy through reinforcement learning approach for human-machine cooperative steering of intelligent vehicles, so as to realize a more flexible and efficient way for the human driver and the automated driving system to jointly complete the path-following. Firstly, the human-machine cooperative steering is modeled by the optimal preview driver model with adaptive preview time and the MPC lateral tracking model with adaptive prediction horizon and step, as well as the steering system with a realistic dual-motor steering-by-wire structure is also built into the human-machine cooperative steering system. Then, the human-machine coordination control strategy is designed and trained based on two reinforcement learning agents to further optimize the allocation of cooperative steering weights. Finally, the strategy is fully verified in lane departure simulation scenarios and also in real-world Steering-in-the-Loop experiments with real-time controller, which shows that both agents can effectively keep the vehicle with the small lateral and yaw errors in the simulation scenarios, and also can be successfully applied in the realistic human-machine cooperative system to maintain the lateral and yaw errors within a safe range during path-following. [ABSTRACT FROM AUTHOR]

Compliant capture of the space non-cooperative targets is a key technology in on-orbit services. A great challenge is that the multi-dimensional contact force generated by the tumbling space target can destabilize the spacecraft-manipulator system (SMS), which may eventually cause failure of the capture task. A full-dimensional controllable damping mechanism (FDCDM) with gyroscopic structure is introduced into the joint of the SMS to buffer the multi-dimensional contact forces during capture. The six-dimensional damping force outputs by the FDCDM can be equivalent to the actuator outputs in the end joint, which could form a coordinated control system with the torque of base flywheel and active joints. The whole-body dynamic model of SMS with FDCDM is established using the Kane method. Furthermore, a backstepping non-singular sliding mode control is proposed to optimize the momentum distribution and impact absorption. The characteristics of collision process for the above SMS-FDCDM system is analyzed in the ADAMS workspace, and the experiments performed in MATLAB demonstrate that the full-dimensional damping mechanism and coordinated control can greatly reduce the vibration caused by the impact force, and the attitude of SMS is quickly stabilized after capture, which proves the feasibility of its application in non-cooperative target capturing tasks. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Guangdong University of Technology is the property of Journal of Guangdong University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article is concerned with both consensus and coordinated path-following control for multiple nonholonomic wheeled mobile robots. In the design, the path-following control is decoupled into the longitudinal control (speed control) and the lateral control (heading control) for the convenience of implementation. Different from coordinated trajectory tracking control schemes, the proposed control scheme removes the temporal constraint, which greatly improves the coordination robustness. In particular, two new coordinated error variables describing a chasing-and-waiting strategy are introduced in the proposed coordinated path-following control for injective paths and circular paths, respectively. All the closed-loop signals have proved to be asymptotically stable in the Lyapunov sense. Finally, simulation results under three typical paths are presented to verify the proposed coordination controllers. [ABSTRACT FROM AUTHOR]

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In this paper, a novel decentralized adaptive coordinated control approach is proposed for human–robot mooring system (HRMS) under the communication topology of the network. First, to achieve output feedback control of multiple robots and ensure uniform, exponential, and global convergence of estimation errors, a distributed filter is proposed for HRMS to eliminate the need for velocity measurement information. Then, instead of modifying the control structure, a universal time-varying asymmetric barrier function (UTABF) is designed to directly confine the system output. It can handle both constrained and unconstrained instances equally. Moreover, adaptive neural networks (NNs) backstepping controllers are proposed to handle the nonlinearities and uncertainties of the system dynamics. The goal of achieving globally uniformly ultimately bounded (GUUB) is achieved by introducing a switch function. Finally, simulation experiments of HRMS composed of a ship model (60,000DWT bulk carrier) are provided to verify the effectiveness of the proposed control algorithms. [ABSTRACT FROM AUTHOR]

In view of unknown Bilateral Teleoperators, the simultaneous satisfaction of not only synchronous control problem between two sides, but also optimal control performance under time-varying delays and external disturbance is a difficult task. Initially, in order to address this challenge, we proposed two control approaches including On-Policy and Off-Policy strategies after employing the sliding variable to reduce the order of dynamic model. Additionally, since the development of the unification between synchronous control problem and optimal control performance, it requires the consideration of discount factor addition to guarantee the bound of the infinite horizon cost function. In order to handle the dynamic uncertainties and the exponential cost function, by fully considering data collection technique in model-free On-Policy and Off-Policy strategies, Reinforcement Learning control schemes are proposed to guarantee the optimality effectiveness. Consequently, the Robust Integral of the Sign of the Error term is integrated into two proposed optimal control frames to improve the synchronous control performance and estimation capability of dynamic uncertainties. Moreover, the convergence of control policies and synchronous control problem of two proposed control frames are rigorously analyzed by Lyapunov stability theory. Finally, simulation results and the comparisons with the existing controller demonstrate the effectiveness of two proposed control frameworks. [ABSTRACT FROM AUTHOR]

In this paper, the coordination control problem of multi-agent systems (MASs) subjected to stealthy attacks and uncertainties is considered, where the uncertainties refer to unknown external disturbances and initial states. We consider a scenario in which the sensors are maliciously attacked, rendering the traditional interval observer's bounds ineffective for estimating the system states. By solving the linear programming problem, the maximum destructive attack sequences are generated. A distributed resilient interval observer composed of a resilient framer and a control protocol is designed, in which the construction of control protocol for each agent depends on the framer information of its own and its neighbors. It is demonstrated by the cooperativity theory and the Lyapunov stability theory that the distributed resilient interval observer can not only realize interval-valued state estimation for each agent but also drive the cooperative behavior of MASs. In addition, the observer gain matrix is selected and optimized by solving a semi-definite programming problem to provide tighter bounds for each agent. Meanwhile, the bounds of stealthy attacks are calculated. Finally, through a simulation example, the superiority of the distributed resilient interval observer and the effectiveness of the resilient interval observer-based consensus control algorithms are validated. [ABSTRACT FROM AUTHOR]

The force-controlled end-effectors for industrial robots usually face the problems of low output force, poor control accuracy, or slow dynamic response. This paper presents a pneumoelectric force-controlled end-effector (PFE) for industrial robots to perform continuous contact operations. The end-effector possesses the advantages of both the pneumatic drive having large force-mass ratio and the electric direct drive having high force control accuracy and fast dynamic response. Through dynamic modeling and analyses, a force coordination control method based on impedance control is proposed for the PFE. The pneumatic cylinder is actuated by a semi-closed loop, while the voice coil motor (VCM) is controlled through a closed loop to improve the output force, accuracy, and dynamics. Impedance controller is utilized to reduce the impact caused by the critical contact between the tool and workpiece. Simulation analyses show that the force-mass ratio has increased, while the friction influence and overshoot has been reduced. In addition, prototype experiments verify the effectiveness of force control method and demonstrate that the PFE is able to achieve good performances such as control accuracy, step response, and dynamic bandwidth. Compared with the traditional pneumatic end-effector, the force control hysteresis is almost reduced from 41.9 to 0% without apparent creeping phenomenon. The rise time of the step response also decreases from 435 to 6.5 ms, and the bandwidth reaches 47 Hz. The PFE with force coordination control shows great potential in robotic deburring, grinding, and polishing applications. [ABSTRACT FROM AUTHOR]

Service coordination among hospitals is a crucial strategy to improving care outcomes and operational efficiency of healthcare delivery systems. This article proposes a referral cooperation system where patients can be referred from one upper-level hospital (ULH) to one lower-level hospital (LLH) for services provided in both types of hospitals with similar service qualities. For multitype patients with different disease conditions, a method for determining the types and quantities of patients that should be referred is explored based on ensuring the interests of the ULH and LLH simultaneously. This article proposes a threshold control method to address these issues along with the Pareto-based negotiation process to implement referral. The control decisions of both ULH and LLH can be achieved by the developed Pareto optimization based on particle swarm optimization-optimal computing budget allocation (POPSO-OCBA) simulation optimization method. To implement the threshold control easily, we further propose a simplified referral control method and conclude that when the flow variability is small, the method can approach similar effects as the previously proposed control while significantly reducing the administrative costs. The methodologies are studied using numerical investigation and a real case exploration in Shanghai. The results show that the methodologies are effective in helping to make the decisions in practice. Note to Practitioners—Under the tide of the sharing economy, healthcare providers are more ready to coordinate on delivering integrated care to patients, especially on care transition operations. With the government’s promotion of hospital alliances, hospitals should pay increasing attention to dynamic care transition control at the operational level to ensure better quality of service. This article investigates an easily implementable threshold control policy for patient referral coordination, which is expected to aid hospitals in dealing with imbalanced resource utilization to share service requests based on their respective resource availability. More importantly, we expect that the derived Pareto frontier of control thresholds can help the hospitals with the presentation of quantitative evidence for facilitating the negotiation on the control agreement of patient referral coordination. At the same time, the control-based methodology proposed can help hospitals to make decisions on their implementation strategy. A case study on negotiating the control agreement between a representative urban-area comprehensive hospital and its partner is provided in this article. We emphasize the importance of applying system engineering and mathematical modeling to study the referral cooperation system and real-time patient control decisions through our analyses. [ABSTRACT FROM AUTHOR]

A new kind of 18 degrees of freedom gantry robot with multiple manipulators could be used to complete the double-sided laser beam welding of stringer–skin T-shape structure for aircraft skin. The coordination control combined with error allocation model analysis is proposed to improve the stability and accuracy of the robot in this article. Firstly, the error model of the stringer–skin T-shape structure welding robot end effectors is analyzed. The score of the robot end effectors position error caused by each joint is obtained. Secondly, according to the path-points transformation matrix of the local coordinate system relative to the base coordinate system, the desired position of stringer–skin T-shape structure welding robot end effectors is calculated to be the input of the control model aiming at the dual-beam laser welding process. Then, the double closed-loop control strategy is proposed for stringer–skin T-shape structure welding robot coordinated motion on the basis of the end error analysis results and proportional-integralderivative (PID) method. Finally, ADAMS and MATLAB are used to establish a co-simulation platform to verify the effectiveness of the proposed coordination control strategy. [ABSTRACT FROM AUTHOR]