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Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications 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.)

Microgrids are the cornerstone for a new model of electrical generation based on renewable resources. Commonly microgrids are controlled with a centralised hierarchical structure, which is inherited from power systems. However, a time-scale separation between traditional fast frequency restoration and slow economic dispatch may be counterproductive in the long run because the slow long-term economic dispatch increases the prediction uncertainty. In an effort to improve the economical operation of microgrids, this work proposes a distributed model predictive control strategy for the operation of isolated microgrids based on a consensus strategy that tackles both the economic dispatch and frequency restoration over the same time-scale. The proposed controller can operate without knowledge of the microgrid’s topology: instead, typical local measurements and other information from neighboring generation units are required. Experimental results demonstrate that the controller is robust to load variations and communication issues, but the plug-and-play nature of the system is preserved. [ABSTRACT FROM AUTHOR]

Virtually coupled train sets (VCTS) have been proposed to increase the transportation capacity and the flexibility of railway organization. Due to the lack of reliable wireless communications and accurate perceptual information, the promotion of VCTS was challenged. With the development of industrial Internet of Things (IIoT), an IIoT-based VCTS is built in the article based on the popular communication-based train control architecture. Considering the dynamic and complex operation environment, it is difficult to achieve the efficient cooperative control of VCTS. The reason is that the traditional method is frequently trapped into a local optimization. To resolve the problem, we apply reinforcement learning (RL) to obtain an optimal policy for the IIoT-based VCTS, where the traditional artificial potential field (APF) is taken to develop the reward function. RL can thus search the global optimal policy, whereas APF can help RL to reduce the computation complexity. This can substantially increase the efficiency of the proposed approach. Simulation results confirmed that the proposed RL-based cooperative control approach would bring excellent performance in the IIoT-based VCTS. [ABSTRACT FROM AUTHOR]

This article investigates the impact of data integrity attacks (DIAs) on cooperative economic dispatch of distributed generators (DGs) in an ac microgrid. To establish resiliency against such attacks and ensure optimal operation, a localized event-driven attack-resilient scheme is proposed. Most of the existing works examine neighboring information to infer the presence of DIAs, where the detection is limited to events such as multiple link failures. Two kinds of DIAs are considered in this article—namely, fault and random attacks, which are segregated based on the final values of consensus updates. First, to improve the robustness of the detection theory, a localized resilient control update is designed by modeling each DG with a reference incremental cost. Second, event-driven control signal is generated for the local incremental cost and held upon the detection of attacks, to prevent malicious data from propagating to the neighboring nodes. The proposed strategy acts immediately upon the detection of DIA to ensure maximization in the economic profit. Furthermore, the proposed detection approach is theoretically verified and validated using simulation conditions. [ABSTRACT FROM AUTHOR]

In this paper, a set-membership filtering-based leader-follower synchronization protocol for discrete-time linear multi-agent systems is proposed, wherein the aim is to make the agents synchronize with a leader. The agents, governed by identical high-order discrete-time linear dynamics, are subject to unknown-but-bounded input disturbances. In terms of its own state information, each agent only has access to measured outputs that are corrupted with unknown-but-bounded output disturbances. Also, the initial states of the agents are unknown. To deal with all these unknowns (or uncertainties), a set-membership filter (or state estimator), having the "correction-prediction" form of a standard Kalman filter, is formulated. We consider each agent to be equipped with this filter that estimates the state of the agent and consider the agents to be able to share the state estimate information with the neighbors locally. The corrected state estimates of the agents are utilized in the local control law design for synchronization. Under appropriate conditions, the global disagreement error between the agents and the leader is shown to be bounded. An upper bound on the norm of the global disagreement error is calculated and shown to be monotonically decreasing. Finally, a simulation example is included to illustrate the effectiveness of the proposed leader-follower synchronization protocol. [ABSTRACT FROM AUTHOR]

This article is concerned with the problem of the containment control with respect to continuous-time semi-Markovian multiagent systems with semi-Markovian switching topologies. Two kinds of classical control schemes, which are dynamic containment control and static containment control schemes, are utilized to address the proposed synthesis problem. Based on the linear matrix inequality (LMI) method, the dynamic containment controller and static containment controller are designed to plunge into the studied semi-Markovian multiagent systems, respectively. Moreover, the random switching topologies with the semi-Markovian process, the partly unknown transition rates, and the generally uncertain transition rates are taken into account, which can be applicable to more practical situations. Finally, the simulation results are provided to illustrate the effectiveness of the proposed theoretical results. [ABSTRACT FROM AUTHOR]

This paper investigates the cooperative target enclosing of multiple unicycle-type mobile robots subject to input disturbances. The objective is to make all robots orbit around a given stationary target, and maintain evenly spaced along a common circle. The network of the multirobot systems is set in a cyclic pursuit manner. A dynamic control law is developed for the cooperative target enclosing of the multirobot systems, while tackling the heterogeneous input disturbances generated by linear exogenous systems. The proposed control law requires each robot to use the relative displacement measurements with respect to the target and its neighbors. It is shown that global asymptotic stability of the closed-loop multirobot systems can be guaranteed in the presence of a large class of input disturbance signals. Finally, simulation results illustrate the effectiveness of our approach. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications 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.)

The improper use of synthetic pesticides has caused adverse effects on global ecosystems and human health. As a part of sustainable pest management strategy, natural predators, along with nano-pesticides, have made significant contributions to ecological agriculture. The cooperative application of both approaches may overcome their limitations, substantially reducing pesticide application while controlling insect pests efficiently. Herein, the current study introduced a cationic star polymer (SPc) to prepare two types of nano-pesticides, which were co-applied with predatory stinkbugs Picromerus lewisi to achieve perfect cooperative pest control. The SPc exhibited nearly no toxicity against predatory stinkbugs at the working concentration, but it led to the death of predatory stinkbugs at extremely high concentration with the lethal concentration 50 (LC 50) value of 13.57 mg/mL through oral feeding method. RNA-seq analysis revealed that the oral feeding of SPc could induce obvious stress responses, leading to stronger phagocytosis, exocytosis, and energy synthesis to ultimately result in the death of predatory stinkbugs. Then, the broflanilide and chlorobenzuron were employed to prepare the self-assembled nano-pesticides via hydrogen bond and Van der Waals force, and the complexation with SPc broke the self-aggregated structures of pesticides and reduced their particle sizes down to nanoscale. The bioactivities of prepared nano-pesticides were significantly improved toward common cutworm Spodoptera litura with the corrected mortality increase by approximately 30%. Importantly, predatory stinkbugs exhibited a strong predation selectivity for alive common cutworms to reduce the exposure risk of nano-pesticides, and the nano-pesticides showed negligible toxicity against predators. Thus, the nano-pesticides and predatory stinkbugs could be applied simultaneously for efficient and sustainable pest management. The current study provides an excellent precedent for perfect cooperative pest control via nano-pesticide and natural predator. Synopsis: SPc was employed to self-assemble with broflanilide into nano-pesticide, which was co-applied with predatory stinkbugs to achieve perfect cooperative pest control. The SPc had no adverse impacts on predatory stinkbugs at the working concentration, but the oral feeding of SPc at extremely high concentration could increase the phagocytosis, exocytosis and energy synthesis to result in death. The co-application of nano-pesticide and predator could control common cutworms efficiently, and the advantages were derived from the high predation selectivity of predators and negligible toxicity of nano-pesticides against predators. [Display omitted] • Star cationic polymer (SPc) shows negligible toxicity against predatory stinkbug. • The SPc at high concentration can induce stress responses in predator to result in its death. • The contact and stomach toxicity of SPc-loaded broflanilide is improved against common cutworm. • Predator displays a strong predation selectivity, and the nano-pesticide shows no adverse impacts on predator. • Co-application of nano-pesticide and predator can achieve perfect cooperative pest management. [ABSTRACT FROM AUTHOR]

This paper studies the cooperative control problem of flywheel energy storage matrix systems (FESMS). The aim of the cooperative control is to achieve two objectives: the output power of the flywheel energy storage systems (FESSs) should meet the reference power requirement, and the state of FESSs must meet the relative state-of-energy (SOE) variation rate constraints. When the above objectives are reached, the FESSs are able to track reference power command while ensuring that all flywheels are fully charged or discharged at the same time. To achieve these two objectives, a distributed power allocation strategy is proposed. A distributed estimator is designed to estimate the global state information required for each FESS in the allocation strategy. In addition, a fixed-time estimator based on a dynamic average consensus algorithm is designed, which is capable of quickly estimating the global average information. The convergence of the fixed-time estimator under the boundedness assumption of the time derivative of input signal is analyzed by the Lyapunov stability theory. The simulation results show that the FESSs interact with neighbors through local information such that the evolution of the SOE among the FESSs satisfies the constraints and the total power tracks the total reference power. Furthermore, compared with the existing methods, the proposed dynamic average consensus estimators achieve an accurate tracking of the global state information in a fixed time, regardless of the initial conditions. • Existing control strategies of flywheels mainly address energy balancing problem. • An allocation strategy is proposed to address the cooperative problem of flywheels. • The proposed strategy avoids the mutual charge and discharge among flywheels. • A fixed-time estimator is proposed to improve the performance of the allocation strategy. [ABSTRACT FROM AUTHOR]

This paper studies a distributed state estimation problem for both continuous- and discrete-time linear systems. A simply structured distributed estimator {comprising interconnected local estimators} is first described for estimating the state of a continuous and multi-channel linear system whose sensed outputs are distributed across a fixed multi-agent network. The estimator is then extended to non-stationary networks whose graphs switch according to a switching signal. The estimator is guaranteed to solve the problem, provided a network-widely shared high gain condition achieving a form of spectrum separation is satisfied. As an alternative to sharing a common gain across the network, a fully distributed version of the estimator is also studied in which each agent adaptively adjusts a local gain, though the practicality of this approach is subject to a robustness issue common to adaptive control. A discrete-time version of the distributed state estimation problem is also studied, and a corresponding estimator based again on spectrum separation, but not high gain, is proposed for time-varying networks. For each scenario, it is explained how to construct the estimator so that the state estimation errors in the local estimators all converge to zero exponentially fast at a fixed but arbitrarily chosen rate, provided the network's graph is strongly connected for all time. The proposed estimators are inherently resilient to abrupt changes in the number of agents and communication links in the inter-agent communication graph upon which the algorithms depend, provided the network is redundantly strongly connected and redundantly jointly observable. [ABSTRACT FROM AUTHOR]

This article studies a distributed consensus law to achieve a coordinated trochoidal formation among a team of mobile agents. The mobile agents are modeled as double integrators. We generalize an existing consensus algorithm for double-integrator dynamics (1) to achieve trochoidal patterns under a general network topology and (2) to extend the pattern formation in a 3-D plane. Since the trochoidal patterns are 2-D curves, the proposed control law allows us to specify the 2-D plane in the 3-D space on which the patterns will be formed. We modify the standard consensus protocol and manipulate the gains to create trochoidal motion through local information exchange by appropriately placing the eigenvalues of the system. Trochoids have been used in multifaceted robotic applications such as area coverage, hurricane sampling, and orbit designs for satellites, apart from their aesthetic appeal. Computer simulations and multi-robot experiments are presented to validate the theoretical findings. [ABSTRACT FROM AUTHOR]

For problems such as low control accuracy, poor coordination and uneven pushing of hydraulic support in fully-mechanized coal mining face, an intelligent cooperative control method of hydraulic support is proposed based on driverless car technology . Each hydraulic support is regarded as a 'car' in fully mechanized mining face. The 'car' moves forward by moving support and adjusts driving direction by bottom adjustment and side guard plate adjustment. The group of hydraulic support is like a row of 'cars' moving forward in a certain order and maintaining alignment. Each hydraulic support has a fixed target travel, and is constrained by position of left and right side supports, so it can pay attention to operation of shearer in front and take into account status of the neighboring support, so as to realize intelligent cooperative control of hydraulic support. The method discusses intelligent cooperative control of hydraulic support from aspects of hydraulic support precise pushing control, parallel advancing control, protection plate control and closed-loop control of automatic following, which provides an idea for solving the control problems of hydraulic support in fully-mechanized coal mining face.

In view of the problems that influence of viscoelasticity of conveyor belt on starting process is neglected in current research on driving and control of belt conveyor, and belt conveyor starting process cannot be simulated well, mechanical properties and viscoelastic model of the conveyor belt were analyzed and Voigt model was selected for modeling of conveyor belt. Simulink and AMESim co-simulation platform was used to establish model of the mechanical part and motor control part of the belt conveyor separately. Three-point driving and control system of long distance belt conveyor was designed according to principle of direct torque control and the idea of cooperative control. The system adopts master-slave control strategy, takes head driving motor as main driver and the rest as slave drivers to control output speed and torque of the three drivers at the head part, middle part and tail part of the belt conveyor, which enables the belt conveyor to start and run smoothly with the preset speed curve. The simulation results show that although load torque of the conveyor is constantly changing due to viscoelastic effect of conveyor belt and the change of acceleration of the conveyor, the three drivers at the head part, middle part and tail part of the belt conveyor can track the preset starting speed well, which indicates that the three-point driving and control system can control the start-up and operation of the belt conveyor well.

In view of problems of low efficiency of manual registration management and poor cooperative control of coal mine electromechanical equipments, an intelligent management platform for coal mine electromechanical equipments based on Internet of things was designed. Real-time display of equipments operation status, fault classification alarm, quick fault location and cooperative control among equipments are realized by real-timely collecting operation data of coal mine electromechanical equipment. Preparation of inspection plan, work order management, routine inspection and fault handling are realized through process management of electromechanical equipments inspection. Equipments fault diagnosis, equipments utilization rate analysis, personnel on-duty performance assessment, preparation of maintenance plan and energy efficiency analysis are realized by integrating and analyzing real-time monitoring data and daily inspection data. The application of the platform can improve collaboration efficiency among electromechanical equipments, effectively reduce probability of equipments fault, improve level of equipments fine management, and achieve full life cycle management of equipments.

With the ever-growing complexity of a modern power system, decentralized control is becoming a more advantageous framework for maintaining its stable operation. Recently, some research work has been done on decentralized control for mitigating inter-area oscillations based on dynamic state estimation. This paper illustrates that in the decentralized control scheme, the use of dynamic state estimation can compromise controller performance and decrease the damping of inter-area oscillations. To address this problem, this paper proposes a cooperative-based supplementary excitation control strategy for damping inter-area oscillations using dynamic state information. By eigenvalue analysis, this paper reveals the relationship between the estimator's parameter and inter-area modes. Furthermore, communication is utilized in the proposed controller to neutralize the adverse impact of using dynamic state estimation on damping performance. The connection between the communication structure and inter-area modes is also analytically given. Finally, the well-known New England test system with 10 generators and 39 buses is employed to demonstrate the analytical results.

This paper studies the distributed cooperative H∞ control problem of multiple high-speed trains with input saturation constraints, external disturbances and nonlinear running resistance. Based on the local information, a new distributed control algorithm is proposed for each train to enable all trains to move in a stable mode while tracking a desired velocity. To attenuate the effects of external disturbances on the cooperative control, the H∞ control technology is used and some sufficient conditions are then obtained to guarantee that the cooperative control under a desired performance is realized. Finally, simulations are provided to show the effectiveness of the results.

A vehicle-to-vehicle (V2V) cooperative trajectory-planning algorithm for connected vehicles driven on a winding road considering characteristics of human drivers is presented in this paper. The algorithm of cooperative game is introduced to plan collision-free trajectories for the involved encountering vehicles, with satisfaction of the safety requirements including vehicle stability and road-departure avoidance. The trajectory-planning algorithm is then converted to a Model Predictive Control (MPC) problem and solved with the concept of Pareto Optimality. The algorithm is compared with a V2V trajectory-planning algorithm with non-cooperative game. Simulations are conducted in the scenarios of lane-exchange on arc shaped roads with different radius to verify the proposed algorithm. Results show that the algorithm can accomplish the task of trajectory-planning on either winding road or straight road successfully, considering the driver's characteristics. The difference of collaboration tendency in V2V driving between using cooperative algorithm and non-cooperative algorithm is also studied and described.

This paper presents an approach and analysis for performing decentralized cooperative control of a team of decoys to achieve the Honeypot Ambush tactic. In this tactic, the threats are successfully lured into a designated region where they can be easily defeated. The decoys learn to cooperate by incorporating a game-theory-based online-learning method, known as regret minimization, to maximize the team's global reward. The decoy agents are assumed to have physical limitations and to be subject to certain stringent range constraints required for deceiving the networked threats. By employing an efficient coordination mechanism, the agents learn to be less greedy and allow weaker agents to catch up on their rewards to improve team performance. Such a coordination solution corresponds to achieving convergence to coarse correlated equilibrium. The numerical results verify the effectiveness of the proposed solution to achieve a global satisfaction outcome and to adapt to a wide spectrum of scenarios.

When an unexpected obstacle occupies some of the lanes on a multi-lane highway, connected vehicles (CVs) may be able to avoid it cooperatively. For example, a CV that detects the obstacle first can immediately notify the following vehicles of the obstacle by using vehicle-to-vehicle (V2V) communication. In turn, the following vehicles can take action to avoid the obstacle smoothly using wide range behind the obstacle without sacrificing safety and ride comfort. In this study, we propose a method to realize safe, smooth, and fair wide-range cooperative lane changing, reacting to a sudden obstacle on the road. The proposed method is based on the authors’ previous work, which utilizes multi-hop communication to share the obstacle position and controls the inter-vehicular distance of vehicles away from the obstacle to assist in a smooth lane changing operation, while existing lane-changing methods for CVs focus on microscopic operation around the obstacle. Though the previous work treats only a two-lane road, the proposed method is extended to work on a three- or more lane road assuming only one lane is blocked. In the proposed scheme, each vehicle approaching the obstacle selects a lane to change to in accordance with the obstacle’s location and the vehicle density in each lane estimated from the beacon messages broadcast by each CV, thereby improving traffic fairness among all lanes without degrading safety or ride comfort. We confirmed the effectiveness of the proposed scheme on realizing fairness among lanes, safety, ride comfort, and traffic throughput through comprehensive simulations of a two-lane road and a three-lane road with various traffic scenarios.

The entrances and exits of underground parking lots of large complexes are the key nodes for the conversion between ground-level dynamic traffic and underground static traffic. Since congestion is caused by a large number of vehicles leaving parking lots at peak hours, the departure control strategy can effectively manage vehicle departure and reduce the congestion of ground-level traffic. In this study, we introduce cooperative control in ramp control into parking lot exit management. The frequency of parking lot exit gate lever lift is used as the control and optimization variable. To ensure the efficiency of regional traffic, we designed timing and inductive control strategies to control the speed of departing vehicles. In an experimental model, we took Shanghai Jinding super-large underground parking lot as an example. The changes in the external road network were simulated when different strategies were implemented on the Simulation of Urban Mobility (SUMO) simulation platform. The experimental results show that the proposed control strategies can significantly ease the congestion of the regional road network, improve the average speed of dynamic traffic, and reduce the queue length at intersections.

This paper is concerned with designing a dynamical synchronization (via a robust cooperative control) of an electromechanical system network (EMSN), consisting of nonidentical brushed DC motors, where only the motors’ angular velocity measurements are available. The challenge of the proposed approach is that the actuation provided by the motor needs to handle external disturbances to achieve the velocity tracking task and handle the interaction between both motors cooperatively to share the load and the disturbance rejection. The control’s basis involves differential flatness and an active disturbance rejection control (ADRC) framework augmented using ideas from the graph theory analysis and multi-agent networks. Experimental results verify the theoretical developments and show the effectiveness of the proposed control strategy despite unexpectedly changing load disturbance and parameters uncertainties. The proposed algorithm is suitable for embedded use due to its simplicity. It can be applied to a broad spectrum of mechatronic systems where dual-motor drive arrangements are necessary.

The paper considers the problem of cooperative control synthesis for a complex of N underwater vehicle–manipulator systems (UVMS) to perform the work of moving a cargo along a given trajectory. Here, we used the approach based on the representation of nonlinear dynamics models in the form of state space with state-dependent coefficients (SDC-form). That allowed us to apply methods of suboptimal control with feedback based on the state-dependent differential Riccati equation (SDDRE) solution at a finite time interval, providing the change in control intensity with the transient effect of the system matrices in SDC form. The paper reveals two approaches to system implementation: a general controller for the whole system and a set of N independent subcontrollers for UVMSs. The results of both approaches are similar; however, for the systems with a small number of manipulators, the common structure is recommended, and for the systems with a large number of manipulators, the approach with independent subcontrollers may be more acceptable. The proposed method of cooperative control was tested on the task of cooperative control for two UVMSs with six-link manipulators Orion 7R. The simulation results are presented in the article and show the effectiveness of the proposed method.

This article proposes a predictive coordinated and cooperative voltage control method in a power distribution system with high penetration of photovoltaic (PV) units. First, an integrated coordinated voltage control of voltage regulators (VRs) tap positions and cooperative distributed control of the reactive power output from PV inverters are used to maintain system voltages within an appropriate bandwidth. Next, solar power forecasting is applied to predict voltage changes, which are used to set the VR tap positions and capacitor switch status to prevent large voltage fluctuations. The fine tuning of voltage adjustment is then achieved by cooperative control of PV inverters to maintain a uniform voltage profile across the system. The proposed method is tested on a modified IEEE 123-node test feeder with high penetration of PVs using real measurement data and compared with the base case. Simulation results demonstrate the effectiveness of the integrated voltage control, as well as the enhancement from the predictive control through solar power forecasting-enabled voltage change estimates. Comparison to previous work in the literature shows significant improvement in terms of voltage deviation and reduction in excessive tap changes. [ABSTRACT FROM AUTHOR]

This paper considers the spacecraft formation flying (SFF) with a desired attitude. Two control problems are studied. One is the formation control of multiple spacecraft and the other is the attitude synchronization of multiple spacecraft. To solve the two problems, a 6-DOF model is adopted for each spacecraft. In the 6-DOF model, it is assumed that the inertia parameters are not well known and there are perturbations of orbitals, gravity, etc. With the aid of the backstepping technique and the algebraic graph theory, distributed robust control laws are proposed for the formation flying and attitude synchronization problems, respectively. The effectiveness of the proposed controllers is shown by simulation. [ABSTRACT FROM AUTHOR]

Intelligent robot system has become an essential development direction for managing a farm in the whole-process, all-day, and unmanned environment in smart agriculture. Therefore, it is necessary to cooperate with the harvester and grain truck to realize the autonomous operation in the harvest link. In this study, a longitudinal relative position cooperative control system was designed in the process of master-slave navigation harvesting and co-unloading grain, suitable for the trailer drive system with high nonlinearity. A parallel cooperative model of two machines was established to calculate the deviation of longitudinal relative position, where the relative position of harvester and grain truck was geometrically represented. A linear tracking was also utilized to control the transverse distance deviation, due to the fact that the harvester and grain truck separately planned the operation path. In longitudinal distance error, the throttle of the grain truck was used to adjust the longitudinal relative distance and further control the forward speed. A position-velocity coupling controller was designed to calculate the desired throttle, including a speed feedback Proportional Derivative(PD) controller and a position-velocity integrated decision bang-bang controller. The switch function of the bang-bang controller was derived from the dynamic features with good robustness. An open-loop second-order transfer function of throttle speed was generated from area identification to optimize the parameters of the controller. A simulated model of longitudinal relative position control was constructed to optimize the parameters of position-velocity coupling controller, according to the transfer function. A field experiment was conducted to verify the reliability of the model. Additionally, a comparison was also performed on the designed control system and traditional PD control. The simulation results showed that the designed control was fully adapted to the change of host speeds in practical operation, indicating better adaptability than the traditional PD. A two-machine cooperative navigation test was set to determine the adaptability and accuracy of longitudinal relative position control of position-velocity coupling in field operation. Both the harvester (Lovol Heavy Industry GE80S-H) and grain truck (Lovol Heavy Industry M1104) were installed on an electrically controlled chassis, to realize electronic steering and speed control of engines. Real-time kinematic and global navigation satellite systems (RTK-GNSS, K728 of Si Nan Company) were used to locate modules, with the location acquisition frequency of 10 Hz, and the accuracy of horizontal positioning ± (10+D×10-6) mm, where D is the distance between the base station and the mobile station, km. A wheel corner sensor (BEI-9902120CW) was used with the nonlinearity of ±2%, and A/D sampling accuracy of 12 bits. The switch actuator was Rexroth HT801053. Two sets of communication modules with 2.4 GHz frequency were used for the dual-machine communication (EBYTE company E34-DTU (2G4D20)), where module and control terminal were communicated via RS-232, and the control terminals were AGCS-I controllers with touch screens. The CAN bus was adopted to connect the control terminal with the chassis electronic control unit of the dual machine. This position-velocity coupling longitudinal relative position control was transplanted into the AGCS-I controller. Metrowerks CodeWarrior was adopted for ARM Developer Suite v1.2 development. Collaborative system experiments were conducted in a pilot field at the Lovol Arbos Intelligent Agriculture Demonstration Base. The experiment result showed that the longitudinal relative position deviation converged rapidly under the initial longitudinal deviation of 3, 7, and 10 m when the speed of the main engine was 1 m/s. The average adjustment time of system response was 7.73, 17.2, and 23.2 s, respectively. The average steady-state longitudinal relative position deviation was 0.091 8 m, and the standard deviation of steady-state longitudinal relative position deviation was 0 m, while the control accuracy of 1 173 suitable for the requirement of co-unloading grain, indicating excellent initial deviation adaptability. In addition, a wheat harvest test of the dual-machine cooperative system was carried out in Jinchang, Gansu Province of China. The performance of longitudinal relative position control with position-velocity coupling was obtained in the actual harvest operation. The field experimental results showed that the average steady-state longitudinal relative position deviation was 0.077 8 m, and the standard deviation of steady-state longitudinal relative position deviation was 0.091 3 m, indicating high cooperative accuracy in the need of harvest cooperative grain unloading. The finding can provide sound support for the high-precision independent system of harvest operation in smart farming. [ABSTRACT FROM AUTHOR]

We study the application of cooperative control and game theoretic approaches to wind farm optimization. The conventional (greedy) wind farm control strategy seeks to individually maximize each turbine power. However, this strategy does not maximize the overall power production of wind farms due to the aerodynamic interactions (wake effect) between the turbines. We formulate the wind farm power optimization problem as an identical interest game which can also be used to solve other cooperative control problems. Two model‐free learning algorithms are developed to obtain the optimal axial induction factors of the turbines and maximize power production. The algorithms are simulated for a four‐turbine wind farm and the Princess Amalia wind farm and are compared to a learning algorithm that uses a game‐theoretic approach. It is shown that the proposed algorithms improve upon benchmark algorithm in terms of both performance and actuation effort. [ABSTRACT FROM AUTHOR]

In this work, we propose an effective and simple control approach for islanded DC microgrids that allows each distributed generator (DG) to achieve accurate voltage regulation and power-sharing. An improved dynamic consensus protocol, which is robust to measurement noise and states initialization, is employed to enable each agent to locally calculate the average bus voltage with a sparse cyber network. On this basis, we propose a cooperative controller that merges the voltage regulation and power-sharing objectives in a unified fashion. The proposed approach only uses neighbors’ voltage information to regulates the average bus voltage to its nominal value while maintaining proportional power-sharing or optimal power dispatch. This significantly simplifies its implementation and reduces the communication bandwidth requirement. A global model of the DC microgrid considering the cyber network is established in the form of a state-space-model, where the reference voltage vector corresponds to the input and the average bus voltage vector denotes the state. Then, the input-to-state stability analysis is carried out. To the end, comprehensive hardware-in-the-loop (HiL) tests are conducted to validate the effectiveness of the proposed control strategy. The proposed control strategy exhibits plug-and-play capability, and it is resilient to message update rate and communication failure. [ABSTRACT FROM AUTHOR]

Existing results for cooperative control of high-order agents mainly employ the Nussbaum-type function to cope with unknown control directions and mostly require an assumption that the control directions are identical and unknown. This paper proposes a class of algorithms with nonlinear PI functions to relax such an assumption and make them suitable for nonidentical unknown control directions. It is proven that if the distributed nonlinear PI functions are suitably selected, the proposed algorithms can achieve consensus for high-order agents under strongly connected topologies and switching topologies with a jointly strongly connected basis (JSCB). Furthermore, we extend the consensus results to the case of time-varying topologies described by $\delta $ -connected, continuous graphs. As a special case, the consensus of high-order agents under the directed graph having a spanning tree is also investigated. Finally, illustrative simulations are presented to indicate the efficiency of the proposed algorithms. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation 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.)

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & 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 paper proposes a guidance system with a new hybrid architecture for multiple fixed-wing unmanned aerial vehicles (UAVs) formation flight. The proposed architecture is hybrid in the sense of combining two control policies found in guidance systems: the Decentralized Partially Observable Markov Decision Process (Dec-POMDP) policy and the well-known PID controller. The Dec-POMDP policy part enables every UAV to avoid collision with any other UAV from the formation. The PID part is activated for regions far from the collision risk zone and is implemented in such a way that each UAV is completely controlled by only its own data, independent of its neighbors. The major novelty of the proposed system, compared to other hybrid approaches, is its decentralized nature which favors overcoming the usual problems that come with centralization such as the high dependence on a central decision node, a leader, or a ground station. Inherited from both parts, the overall system performance is robust in noisy and uncertain environments. Simulations were extensively performed to show the effectiveness of the proposed guidance system in distinct scenarios. [ABSTRACT FROM AUTHOR]

This paper addresses a multisource localization problem with multiple unmanned aerial vehicles equipped with appropriate sensors coordinating with each other, wherein the sources are simultaneously emitting identical acoustic signals. Distributed coordinated localization algorithms based on multiple range and direction measurements are presented and performances are evaluated in different practically significant mission scenarios. Non-deterministic polynomial (NP) hardness to determine optimal number of unmanned aerial vehicles for a given mission scenario is discussed. Group coordination, tactical path, and goal replan strategies to enable efficient localization of single and multiple acoustic sources have been designed. The localization algorithm along with coordination strategy is verified in the presence of realistic error conditions through simulation. [ABSTRACT FROM AUTHOR]

This paper considers the formation control problem for general linear networked agents constrained with event-triggered communications. We propose four kinds of edge-based event-triggered protocols, each of which can be used to achieve given formation structures and eliminate the unexpected Zeno behavior. Since the whole protocols are designed according to sampled information at event instants rather than real-time information, these protocols efficiently avoid continuous communications, reduce the bandwidth need of communication, and decrease the energy consuming. The distributed static state feedback edge-based event-triggered protocol or the adaptive one is applicable for the occasions with available states. Different from the state feedback protocols, users can choose the distributed static output feedback edge-based event-triggered protocol or the adaptive one no matter whether agents’ states are available or not. It is worth emphasizing that the adaptive state (or output) feedback event-triggered protocol requires no global information of the network topology and can be used in a fully distributed and scalable manner. Finally, numerical examples on formation control are offered to testify the feasibility of the proposed protocols. [ABSTRACT FROM AUTHOR]

This paper studies the distributed adaptive cooperative control of multiple urban rail trains with position output constraints and uncertain parameters. Based on an ordered set of trains running on the route, a dynamic multiple trains movement model is constructed to capture the dynamic evolution of the trains in actual operation. Aiming at the position constraints and uncertainties in the system, different distributed adaptive control algorithms are designed for all trains by using the local information about the position, speed and acceleration of the train operation, so that each train can dynamically adjust its speed through communicating with its neighboring trains. This control algorithm for each train is designed to track the desired position and speed curve, and the headway distance between any two neighboring trains is stable within a preset safety range, which guarantee the safety of tracking operation of multiple urban rail trains. Finally, the effectiveness of the designed scheme is verified by numerical examples.

This paper investigates the cooperative control problem for a group of autonomous nonholonomic mobile robots, in which the robots are required to collaboratively enclose and track a stationary or moving target in a circular formation. In order to solve the challenging problem that the robots with speed constraints move uniformly to the exact position on the circles centered on the target while avoiding obstacles encountered, a distributed coupling controller scheme consisting of target encircling, phase positioning and spacing assignment, and the avoidance of obstacles is proposed. First, a novel circular motion control law based on the feedback control idea of trajectory tracking is proposed, which guides all robots move to the target-centered circles and maintains the expected distances between the robots and the target. Second, a phase positioning and spacing assignment control law by introducing a nonlinear function is proposed, which can be coupled into the circular motion controller to implement the robots converge to the specified position on the circles. Finally, the obstacles avoidance control law based on artificial potential field only with repulsive force is adopted to ensure each robot effectively avoids obstacles. The rigorous theoretical analysis of the convergence of the proposed controller is given, and then the simulations and experiments are provided to validate the effectiveness and applicability of the proposed control scheme.

Summary: With the new edge of smart grids technology, the concept of efficient energy management among cooperative microgrids (MGs) distribution networks for the next generation of energy trading applications has become more and more challenging. This article presents smart energy dispatch for multi‐MGs (MMGs) systems based on the cooperative distributed economic model predictive control (DEMPC) within a hierarchical structure. The optimization framework consists of two levels. First, a DEMPC coordinator computes the optimal energy dispatch solution, taking into account the energy surplus with a power‐sharing policy, the retail electricity price based on the time of use (TOU), and the distributed generators units. For the second level, each local controller executes the energy scheduling reference from the first level. Thus, the MMGs system achieves a global supply‐demand balance. Moreover, the proposed approach improves the utilization of renewable power and demonstrates optimal energy dispatch while reducing operating costs. Finally, to validate the efficiency and resiliency of our proposed approach, two cases of study are presented based on three interconnected MGs system under a cooperative and non‐cooperative optimization. Simulation results show the advantage of the cooperative strategy with 28% for MG 1, and 20% for MG 2 in terms of daily operating costs savings. [ABSTRACT FROM AUTHOR]

This article investigates the issue of cooperative fault‐tolerant fuzzy tracking control for a class of nonlinear multiagent systems subject to actuator failures and external disturbances under a directed network topology. By introducing the hierarchical control scheme, a fully distributed tracking control method is proposed. Specifically, the hierarchical control framework includes the upper layer and the lower layer. The upper layer consists of a virtual system and a virtual cooperative controller. The lower layer consists of an actual system and a fault‐tolerant tracking controller. Compared with the most existing distributed fault‐tolerant control methods where the fault in one agent may cause chain reaction, the phenomenon of fault propagation can be eliminated. Finally, the proposed strategy is demonstrated by simulation results. [ABSTRACT FROM AUTHOR]

Cooperative target enclosing problem with multiple unmanned microaerial vehicles is addressed. A local controller based on a binary-tree (BT) communication topology is presented for the target enclosing formation. A sufficient condition is derived for the formation stability by a recursive Lyapunov method. In this article, a switching rule of the BT topology is developed to cope with the emergent failures of target sensing and the formation scalabilities. Besides, in order to accommodate the enclosure in complicated environments, a multitask framework is constructed which is compatible with the local control protocols. Comparative experiments on both simulations and platforms demonstrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]