Coordination Control Research Articles

Variable impulsive bipartite coordination control of nonlinear systems with DoS attacks

Variable impulsive bipartite coordination control of nonlinear systems with DoS attacks

Effect of a Sensorimotor Training Program for Aerial Maneuvers in Junior Surfers

The purpose of this study was to examine the impact of a sensorimotor training program on maximum ankle dorsiflexion (ankle DF), coordination, dynamic balance and postural control, and lower-limb muscle power, in competitive junior surfers, and its relation to parameters of sensorimotor control required to perform aerial maneuvers. Twelve junior competitive surfers followed a 7-week sensorimotor training program, being assessed pre- and post-program with the knee-to-wall test (KW), Y-Balance test—lower quarter (YBT-LQ), and the countermovement jump test (CMJ). Post-training assessment revealed positive effects on the KW (ankle DF) distance, which increased approximately 2 cm (p < 0.001) for both ankles, and all scores for the YTB-LQ (coordination, dynamic balance, and postural control) variables increased, being significant (p < 0.005) for some reach distances (YBT-LQ—Anterior Left, YBT-LQ—Postero-medial Left, and YTB-LQ Anterior Right). YBT-LQ Anterior Reach Asymmetry also improved by decreasing 1.62 cm (p < 0.001) and the CMJ height (lower limb muscle power) increased 2.89 cm (p < 0.001). The training program proved to effectively enhance parameters of physical performance for this sample, including ankle DF, coordination, dynamic balance, postural control, and lower limb muscle power. This tailored-made task approach can help to optimize surfing performance capabilities and contribute to reducing the risk of injuries while performing aerials.

Distributed adaptive coordinative control for virtually coupled train set with considering parametric uncertainty and state constraints

Distributed adaptive coordinative control for virtually coupled train set with considering parametric uncertainty and state constraints

A novel two-stage game theory-based data-driven coordination control for efficient power allocation and EV charging management

A novel two-stage game theory-based data-driven coordination control for efficient power allocation and EV charging management

AI-optimization operation of biomass-based distributed generator for efficient radial distribution system

This research aims to optimize the size and location of biomass-based distributed generator (BMDG) units to enhance the voltage profile, reduce electrical losses, maximize cost savings, and decrease emissions from power distribution systems. Biomass-based distributed generator (BMDG) systems offer numerous advantages to enhance the efficiency of power distribution systems. However, achieving these benefits relies on determining the optimal size and position of the BMDGs. To achieve these objectives, the metaheuristic technique called particle swarm optimization (PSO) is employed to find the optimal placement and size of BMDGs. The proposed model was validated on MATLAB's IEEE-33 bus radial distribution system (RDS), confirming the aforementioned benefits. Comparative analysis between the PSO-based technique and other algorithms from previous research revealed better results with the proposed method. The results indicate that optimal placement and sizing of BMDG units have led to a reduction of more than 67.68% in active power losses and 65.90% in reactive power losses compared to the base case. Additionally, the reduction in active power loss was 40.44%, 11.39%, 42.85%, 1.81%, 0.85%, 29.83%, 5.82% and 28.38% more than artificial bee colony, backtracking search optimization algorithm, moth-flame optimization, Coordinate control, artificial Hummingbird algorithm, variable constants PSO (VCPSO), artificial gorilla troops optimizer (AGTO), and a jellyfish search optimizer respectively. Furthermore, the reactive power losses were reduced by 38.33% and 15.68% compared to VCPSO and AGTO respectively. Furthermore, this study revealed a cost reduction of 6.38% when compared to the AGTO and 1.30% when compared to the AHA. Moreover, the voltage profile of the power distribution system was improved by 7.28%. The presented methodology has demonstrated promising results for BMDGs in RDS across various applications.

Path tracking and energy efficiency coordination control strategy for skid-steering unmanned ground vehicle

The skid steering unmanned ground vehicle (SUGV) plays an important role in extremely harsh environments. Improving the autonomous control capability and energy efficiency of SUGV is urgently needed. This article presents a skid steering-based path tracking control strategy. In the upper controller, an improved model-free sliding mode controller (APMS) is used to calculate the yaw moment for tracking control. On the lower controller, the Snow Ablation Optimizer (SAO) is used to distribute the output torque of the drive motors, taking longitudinal force, yaw moment and energy consumption into account. Finally, the designed controller is validated through simulation under different operating conditions. The results show that the proposed coordination controller achieves good control performance, increases energy efficiency and at the same time ensures tracking accuracy.

Cyber attacks detection and mitigation in hybrid power system using type-2 fuzzy controller

Abstract This paper presents a novel control technique using Fuzzy Type-2 controller for regulating the frequency deviations in an independent Hybrid Power System (HPS). The HPS comprises of a wind system and a solar photovoltaic (PV) system as primary energy sources, along with Fuel Cells (FCs) as additional generation systems and Double Layer Capacitor (DLC) Banks as storage devices to meet the load demand. The frequency variations occur in the HPS due to the intermittency in power outputs from the primary sources, the load changes as well as any attacks in the system. The frequency regulation is achieved by effective coordination control of FC and DLC with the aid of a Fuzzy Type-2 controller and a high pass filter (HPF). The DLC technology adequately satisfies the residual power of hybrid systems resulting from the slow dynamics of FCs. The Fuzzy Type-2 controller is trained using an input-output data set of a PID controller whose gains are tuned to their optimal values using Monte-Carlo state estimators. The proposed system is simulated using real weather data to validate the capability of the Hybrid Power System (HPS) in supplying isolated loads while maintaining power frequency balance conditions. Also the HPS is subjected to attacks in daily load variation and the results are compared with the system without attacks. The simulation results show that the peak over shoots are reduced considerably but the settling time is 0.2 seconds in the system with no attacks where as the settling time is prolonged to 1.2 seconds with the attacks. This paper demonstrates the effectiveness of the Fuzzy Type-2 controller for the coordination control of DLC and FC to achieve generation-load balance condition in comparison with that of the PID controller for HPS system with and without attacks.

Torque balancing and coordination control based on improved deviation coupling for multi-motor rigid connection systems

Torque balancing and coordination control based on improved deviation coupling for multi-motor rigid connection systems

Short-term sensorimotor training incorporating cognitive tasks for pediatric survivors of posterior fossa tumors: a pilot study.

Posterior fossa tumors account for half of all childhood brain tumors, prompting the search for effective and affordable interventions to combat the neurocognitive and motor sequelae of the tumor and its treatment. The main aim of this pilot study was to evaluate the feasibility and effects of sensorimotor training incorporating cognitive tasks for a group of pediatric survivors of posterior fossa tumors. A total of 48 participants (Mage= 12.3 ± 3.25 years, 41.7% female; 56% with malignant tumors) in remission after completing treatment for posterior fossa tumors were enrolled. Participants received 3 weeks of sensorimotor training targeting visual-motor and cognitive abilities on a FitLight Trainer™. The protocol consisted of 2-3 15-minute training sessions per week, with each session including tasks designed to promote: (1) eye-hand and eye-foot coordination and motor control (simple sensorimotor reaction task); (2) inhibitory control (inhibition task); (3) inhibitory control and working memory (color task). Participants completed an average of six sessions, indicating a moderate adherence rate. Results showed a significant reduction in visuomotor reaction time across age and tumor subgroups in nearly all tasks, which might indicate improvement in the targeted functions, with performance characteristics varying across subgroups. The results suggest that training might be a feasible intervention to promote visual-motor performance in pediatric survivors of posterior fossa tumors across age and tumor type groups, however, further research should address the assessment issues and other limitations of the present study, to provide a more substantial justification for the use of this training.

A comprehensive analysis of India’s electric vehicle battery supply chain: barriers and solutions

This study investigates challenges and solutions for India’s battery supply chain in the growing electric vehicle (EV) market. Key obstacles include raw material dependency, supply chain complexity, production costs, environmental impacts, rapid technological changes, and skilled workforce shortages. Methods involve reviewing current supply chains, evaluating government policies like the FAME and PLI schemes, and analyzing strategic partnerships with countries rich in lithium, cobalt, and nickel. Results show heavy reliance on imports exposes India to geopolitical risks and price volatility, while a fragmented supply chain hinders coordination and quality control. Establishing gigafactories is crucial but requires substantial investment. The study recommends enhancing domestic production, securing raw materials through exploration and international partnerships, investing in R&D for advanced technologies and alternative chemistries, and developing a skilled workforce through specialized training. Implementing these strategies will ensure a robust and sustainable battery supply chain, supporting EV market growth and positioning India as a leader in electric mobility. Further research should focus on long-term environmental impacts and the economic implications of a localized supply chain.

A Fuzzy Adaptive PID Coordination Control Strategy Based on Particle Swarm Optimization for Auxiliary Power Unit

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.

Dynamical network-based evaluation for neuromuscular dysfunction in stroke-induced hemiplegia during standing

BackgroundA given movement requires precise coordination of multiple muscles under the control of center nervous system. However, detailed knowledge about the changing characteristics of neuromuscular control for multi-muscle coordination in post-stroke hemiplegic patients during standing is still lacking. This study aimed to investigate the hemiplegia-linked neuromuscular dysfunction during standing from the perspective of multi-muscle dynamical coordination by utilizing a novel network approach – weighted recurrence network (WRN).MethodsTen male hemiplegic patients with first-ever stroke and 10 age-matched healthy male adults were instructed to stand on a platform quietly for 30 s with eyes opened and eyes closed, respectively. The WRN was constructed based on the surface electromyography signals of 16 muscles from trunk, hips, thighs and calves. Relevant topological parameters, including clustering coefficient (C) and average shortest path length (L), were extracted to evaluate the dynamical coordination of multiple muscles. A measure of node centrality in network theory, degree of centrality (DC), was innovatively introduced to assess the contribution of single muscle in the multi-muscle dynamical coordination. The standing-related assessment metric, center of pressure (COP), was provided by the platform directly.ResultsResults showed that the post-stroke hemiplegic patients stood with remarkably higher similarity of muscle activation and more coupled intermuscular dynamics, characterized by higher C and lower L than the healthy subjects (p < 0.05). The DC values and rankings of back, hip and calf muscles on the affected side were significantly decreased, whereas those on the unaffected side were significantly increased in hemiplegia group compared with the healthy group (p < 0.05). Without visual feedback, subjects exhibited enhanced muscle coordination and increased muscle involvement (p < 0.05). A decrease in C and an increase in L of WRN were observed with decreased COP areas (p < 0.05).ConclusionsThese findings revealed that stroke-induced hemiplegia could significantly influence the neuromuscular control, which was manifested as more coupled intermuscular dynamics, abnormal deactivation of muscles on affected side and compensation of muscles on unaffected side from the perspective of multi-muscle coordination. Enhanced multi-muscle dynamical coordination was strongly associated with impaired postural control. This study provides a novel analytical tool for evaluation of neuromuscular dysfunction and specification of responsible muscles for impaired postural control in stroke-induced hemiplegic patients, and could be potentially applied in clinical practice.

Enhancing Stability in Wind‐Integrated Power Systems Through Coordinated Control of POD, PSS, and SVC With Fuzzy Logic: A Comprehensive Study Under Various Operating Conditions

Enhancing Stability in Wind‐Integrated Power Systems Through Coordinated Control of <scp>POD</scp>, <scp>PSS</scp>, and <scp>SVC</scp> With Fuzzy Logic: A Comprehensive Study Under Various Operating Conditions

Leader-follower control and APF for Multi-USV coordination and obstacle avoidance

To overcome the limitations of a single USV in task execution, this paper investigates the issues of cooperative motion and obstacle avoidance for USV swarm. The leader-follower control approach is chosen as the strategy for coordinating the formation of multiple USVs. Kinematic and kinetic controllers are designed using sliding mode control, with a saturation function replacing the sign function to avoid chattering. The validity of the kinematic and kinetic controllers is demonstrated using the Lyapunov stability theorem. To tackle the problem of goal reachability when obstacles are nearby in the artificial potential field method for obstacle avoidance, the repulsive potential field function is modified by including the distance factor between the USV and the target point. To address the problem of local minimum, the simulated annealing algorithm is incorporated into the traditional artificial potential field method. Multi-condition simulation experiments are conducted using MATLAB. The experimental results demonstrate that multiple USVs can form a formation in a short time and maintain the formation while navigating, exhibiting high robustness. Furthermore, they are able to effectively navigate through complex marine environments, successfully avoiding obstacles and ultimately reaching their target destination.

Gait coordination control of bipedal modular reconfigurable robot based on adaptive neural network

This paper proposed an adaptive neural network (NN) control method to track the desired trajectory of a bipedal modular reconfigurable robot (MRR), which can solve the gait coordination problem of bipedal MRR. The leg dynamic model and the body dynamic model of bipedal MRR are established based on the Newton–Euler iterative method, and the global dynamic model is subsequently established. Aiming at the gait coordination problem between double support phase (DSP) and single support phase (SSP), the desired trajectory is generated based on the zero-moment point (ZMP) method. The adaptive NN controller is designed to track the generated desired trajectory, which also compensates interconnected dynamic coupling (IDC) effects of the bipedal MRR. The stability of bipedal MRR system is proved by Lyapunov theory. In the end, the effectiveness of the control method is verified by comparative simulation. The simulation results show that the proposed adaptive NN method reduces the position tracking error by [Formula: see text] and the control torque by [Formula: see text] compared with the existing control methods.

Efficient power management strategies for AC/DC microgrids with multiple voltage buses for sustainable renewable energy integration

This study proposes a distinct coordination control and power management approach for hybrid residential microgrids (MGs). The method enhances the feasibility of hybrid MGs by reducing power loss on ILBCs. The MG has been modeled with solar and wind generators. The MG comprises multiple direct current (DC) and alternating current (AC) sub-microgrids (SMGs) with varying voltage levels. The coordination control and power management strategies for autonomous hybrid MGs with primary and secondary control levels. A novel technique is proposed to ensure seamless and precise power transfer among SMGs while minimizing the constant operation of ILBCs in islanded mode, with a focus on the secondary control level. The study uses MATLAB/Simulink to analyze on-grid, off-grid, and transient mode power transfer among MG. The MG has been operative during transient/faulty conditions. The results indicate that the proposed method demonstrates excellent adaptability in managing power flow.

Multi-Objective optimization for stable and efficient cargo transportation of partial space elevator

This paper proposed a new libration decoupling analytical speed function (LD-ASF) in lieu of the classic analytical speed function to control the climber’s speed along a partial space elevator to improve libration stability in cargo transportation. The LD-ASF is further optimized for payload transportation efficiency by a novel coordinate game theory to balance competing control objectives among payload transport speed, stable end body’s libration, and overall control input via model predictive control. The transfer period is divided into several sections to reduce computational burden. The validity and efficacy of the proposed LD-ASF and coordinate game-based model predictive control are demonstrated by computer simulation. Numerical results reveal that the optimized LD-ASF results in higher transportation speed, stable end body’s libration, lower thrust fuel consumption, and more flexible optimization space than the classic analytical speed function.

A control strategy of DC transmission system for offshore wind power based on hybrid converters

Abstract As the DC transmission system of modular multilevel converters for offshore wind power suffers problems like large volume, heavy weight, difficulty in platform transportation, and high cost, a DC transmission scheme for offshore wind power based on diode rectifier units and modular multilevel converters is put forth in the present work; Meanwhile, the features of active-power coordination, the DC harmonic current, and the AC harmonic current of the hybrid converter in this proposed scheme are analyzed to propose control strategies for active power coordination control, DC harmonic current suppression, and AC harmonic current suppression of the hybrid converter, respectively. The performance and feasibility of the proposed strategies are verified by testing the hardware in the loop real-time simulation system for transmission of offshore wind power through hybrid converters based on RTDS. It is found that the proposed strategies could improve the stability, flexibility, and reliability of the system.

Semi-Peer-to-Peer Safety Coordination Control for Distributed Battery Energy Storage System in DC Microgrids via Saturated Limitation

Semi-Peer-to-Peer Safety Coordination Control for Distributed Battery Energy Storage System in DC Microgrids via Saturated Limitation

Формування траєкторії керованих літальних апаратів

Currently, there is an increased interest in the creation of flight control systems for unmanned aerial vehicles, which, taking into account real conditions, would ensure its trajectory and thereby determine the effectiveness of the use of the aerial vehicle. Aircraft navigation, in particular ballistic cruise missiles, requires the formation of high-precision control in order to achieve both final results and local optimization tasks at each of the flight stages: take-off, departure to set trajectories, maneuvering, etc. The development of admissible control and its optimization by computer-mathematical methods of modeling and optimization is a time-consuming process and requires significant expenditures of various types of resources. An element of the effectiveness of such a mathematical apparatus for guaranteeing and increasing the reliability and effectiveness in achieving the set goal is the speed of calculations, which, in turn, requires the simplification of the mathematical model by obtaining functional dependencies for calculating the flight trajectory, avoiding complex mathematical calculations. The complete working model for calculating the desired trajectory of the aircraft will be determined by the specified control functions and will be provided by a system of partial differential equations with time, and the necessary parameters for calculating all aerodynamic forces and moments are tabular data in most cases. A mathematical model for solving the task of forecasting navigation for such complex controlled systems is proposed to be carried out using two coordinate systems: starting and speed. Moreover, all calculations of the velocity vector, which depends on the net effect of three aerodynamic forces acting on the aircraft, should be carried out in the speed coordinate system, and coordinate control of the flight along the entire dynamic trajectory should be determined in the starting system