Coordinated Control Problem Research Articles

Resilient interval observer-based coordination control for multi-agent systems under stealthy attacks

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.

[formula omitted] tracking control for de-oiling hydrocyclone systems via event-triggered reinforcement learning

De-oiling hydrocyclone system is a crucial device in offshore oil and gas production. To reduce action frequency of actuators as well as energy costs, it is desired to apply event-triggered control (ETC) technique for coordination control of de-oiling hydrocyclone systems. However, the triggering errors and slugging disturbances will greatly affect oil-water separation efficiency and need to be well treated. Towards this end, this work studies the coordination control problem of de-oiling hydrocyclone systems subject to slugging disturbances and unknown system dynamics. Robust H∞ control approach is applied to reduce disturbances sensitivity and guaranteeing satisfactory oil-water separation performance. The coordination control problem is transformed into a 2-player zero-sum game problem. A model-based solution by solving the game algebraic Riccati equation (GARE) is obtained and an event-triggered (ET) off-policy reinforcement learning (RL) algorithm is developed to implement the model-based solution. The salient feature of the proposed algorithm is that the proposed model-free H∞ control method alleviates the affects of both triggering errors and slugging disturbances, which are handled together as a generalized disturbance in the algorithm. Stability and Zeno behavior avoidance of the proposed algorithm are analyzed. Simulation studies demonstrate the effectiveness of the proposed algorithm.

Coordinated discrete-time super-twisting sliding mode controller coupled with time-delay estimator for PWR-based nuclear steam supply system

The coordination control problem for the core thermal power of the nuclear reactor (NR) and the water level of the nuclear steam generator (SG) is a crucial challenge for real-time model-based control of a pressurized-water reactor (PWR)-based nuclear steam supply system (NSSS). In this paper, a new coordinated discrete-time super-twisting sliding mode controller (CDTSTSMC) coupled with time-delay estimators (TDEs) is proposed, tackling the coordination control problem for the core thermal power of the NR and the water level of the nuclear SG in the presence of unknown dynamics, such as unmeasured system states, model uncertainties, parameter perturbations, and disturbances. First of all, the continuous-time dynamical models of both the NR and the SG in the PWR-based NSSS are described with consideration of unknown dynamics and then are transformed into discrete-time forms using the Euler approximation method. Two TDEs capable of estimating the unknown dynamics existing in the NR and the SG, respectively, are developed, which rely merely on the measurements of the PWR-based NSSS without the upper bounds of the uncertain dynamics being known. After that, a CDTSTSMC strategy, based on the discrete-time dynamical models describing both the NR and the SG, is proposed, allowing the core thermal power to be driven to a desired value while at the same time maintaining the desired water level in the SG with the help of TDEs. It is proved from stability analysis using a Lyapunov approach that under the proposed CDTSTSMC strategy coupled with the TDEs, the stability of the controlled PWR-based NSSS can be ensured in a wide range of load, where the control errors of both the NR and the SG are driven to a neighbor of zero. Finally, the proposed CDTSTSMC strategy coupled with the TDEs is compared with the previous discrete-time optimized proportional–integral–derivative controller (DTOPIDC) and fuzzy weighting controller (FWC). The simulation results reveal that the proposed CDTSTSMC strategy coupled with the TDEs outperforms the DTOPIDC and the FWC, particularly in rejecting unknown dynamics while maintaining both the core thermal power in the NR and the water level in the SG in their desired ranges.

Semiglobal interval observer‐based robust coordination control of multi‐agent systems with input saturation

AbstractThis paper investigates the problem of robust coordination control based on interval observers for multi‐agent systems in the presence of input saturation and disturbances. Firstly, in the scenario where the system state is not directly measurable, two types of interval observers are, respectively, constructed by resorting to the upper and lower bounds on external perturbances as well as the output information. Secondly, a parametric Lyapunov equation‐based low‐gain feedback control method is proposed to guarantee semiglobal bounded consensus. In contrast to the conventional approach based on parametric algebraic Riccati equations, the proposed method offers the advantage of allowing the parameters to be determined in advance. Finally, a simulation example and a practical electrical circuit model are conducted to verify the theoretical results.

Lateral Stability Control for Intelligent Commercial Vehicle Based on Reconstructed Objective Function Method

In this paper, a novel electric-hydraulic power steering (EHPS) system and a vehicle stability coordination control algorithm are proposed which can not only ensure the accuracy of the trajectory tracking but also solve the coordination control problem between the stability of the lateral control and the stability of the roll in the extreme condition. Firstly, the EHPS system is designed to provide accurate control input of front wheel angle for vehicle lateral dynamics control. Secondly, on the basis of optimal preview theory, a new trajectory tracking fusion controller combined with sliding mode control is proposed to improve the accuracy and stability of the system in the process of vehicle lateral trajectory tracking control. Then, the stability domain boundary function of the phase plane is determined according to the phase plane of the sideslip angle-yaw rate, and the stability margin of the phase plane is calculated during the steering process. Finally, considering the tracking accuracy, lateral stability and roll stability performance in the process of trajectory tracking, the linear weighted algorithm is used to coordinate above three objectives, and the HIL bench test and real vehicle experiment verify that the proposed algorithm has good reliability and effectiveness.

Controller design of coordinated control problems over finite fields via fully actuated approach

This paper discusses coordinated control problems for systems over finite fields via fully actuated approach. Novel types of consensus and synchronization, which are irrelevant to initial states, are proposed. For different coordinated control problems, suitable controllers are designed, which are able to drive the system to the corresponding trajectory in finite steps. Besides, the conclusions are applied to stabilization, and the convergence time is analyzed. As an application, a camera network example is given to illustrate the results.

Coordinated Operation of Virtual Coupling High-Speed Trains Under a Novel Sequential Model Predictive Control Framework

This paper deals with the coordinated control problem of the multiple high-speeds operating under the virtual coupling mode with special consideration of the coupled safety inter-train distance constraints and other independent constraints affecting train dynamics. Considering the inertial lag phenomenon within longitudinal dynamics, this study employs a third-order nonlinear control model to characterize train motion. To cope with the intricate running constraints explicitly, a centralized constrained model predictive (MPC) control problem is formulated for the regulation of the trains. Within the framework of sequential solving approach, a novel distributed model predictive control (DMPC) algorithm is designed based on a distributed train running information exchange mechanism. The algorithm decomposes the centralized MPC problem into a sequence of local problems, allowing for sequential computation and meeting the real-time control requirements. Notably, the algorithm mitigates solution conservatism arising from the distributed optimization mechanism by accounting for potential hypothetical control policies among a train’s topological neighbors when designing its control policy. The feasibility and effectiveness of the proposed results are rigorously confirmed through theoretical analysis and illustrated by numerical experiment results.

Adaptive Neural Coordinated Control for Multiple Euler-Lagrange Systems With Periodic Event-Triggered Sampling.

This article addresses the event-triggered coordinated control problem for multiple Euler-Lagrange systems subject to parameter uncertainties and external disturbances. Based on the event-triggered technique, a distributed coordinated control scheme is first proposed, where the neural network-based estimation method is incorporated to compensate for parameter uncertainties. Then, an input-based continuous event-triggered (CET) mechanism is developed to schedule the triggering instants, which ensures that the control command is activated only when some specific events occur. After that, by analyzing the possible finite-time escape behavior of the triggering function, the real-time data sampling and event monitoring requirement in the CET strategy is tactfully ruled out, and the CET policy is further transformed into a periodic event-triggered (PET) one. In doing so, each agent only needs to monitor the triggering function at the preset periodic sampling instants, and accordingly, frequent control updating is further relieved. Besides, a parameter selection criterion is provided to specify the relationship between the control performance and the sampling period. Finally, a numerical example of attitude synchronization for multiple satellites is performed to show the effectiveness and superiority of the proposed coordinated control scheme.

Distributed Coordination of Networked Manipulators: A Two-Layer Control Scheme

This article studies the coordination control problem of networked manipulators, where manipulators are actuated to cooperatively transport an unknown object along a prescribed trajectory. It is assumed that the accurate position and velocity information of the trajectory is known only to a subset of manipulators. A two-layer control scheme consisting of an estimation layer and a control layer is developed. At the estimation layer, prescribed-time distributed estimators are designed to estimate the position and velocity of the trajectory. The estimation errors are shown to converge to zero in pre-specified time. At the control layer, an event-driven distributed controller with a dynamic triggering mechanism is proposed, where nonuniform time-varying communication delays are considered. A distinctive feature of the proposed controller is that both control updates and communication occur at certain event instants, and thus control update burden and communication costs are reduced. Moreover, two adaptive time-varying control gains are designed so that the controller can be implemented without requiring any inequality condition or global information. Finally, a simulation platform based on MATLAB Robotics Toolbox is designed and implemented to verify the effectiveness and superiority of the proposed two-layer control scheme.

Event-triggered fault-tolerant optimal coordination for multiple Euler–Lagrange systems with semi-Markov jumping networks

ABSTRACT This article explores a distributed optimal coordination control problem for multiple Euler–Lagrange systems with actuator faults. To address this problem, an event-triggered fault-tolerant optimisation algorithm is first proposed to eliminate unexpected faults and reduce the consumption of control resources. In order to further enhance the system's reliability, another algorithm based on the Nussbaum function is proposed to handle faulted systems with uncertain control directions. Note that an auxiliary system with adaptive gains is introduced to eliminate the need for agents to interact with their actual state information, and thus has the effect of protecting privacy. Moreover, the stochastic semi-Markov jumping networks are considered in the algorithms to describe the switching process of uncertain communication graphs. Additionally, the algorithms are fully distributed since it does not require global information of topologies. Finally, numerical simulations are conducted in the article to verify the effectiveness of the proposed algorithms.

Optimal Coordinated Control for Speed Tracking and Torque Synchronization of Rigidly Connected Dual-Motor Systems

Dual-motor systems have been broadly used to drive large inertia loads. In this article, the optimal coordinated control problem of rigidly connected permanent magnet synchronous motor (PMSM) systems is investigated to enhance the speed tracking and torque synchronization performance. First, the mathematical model of rigidly connected dual-PMSM systems is established in terms of the model of the PMSM and the characteristics of gear transmission drive. Second, to minimize the speed tracking and torque synchronization errors, a novel optimal coordinated control scheme is proposed for rigidly connected dual-PMSM systems by combining the conventional master–slave control structure and the linear–quadratic regulator control strategy. Then, taking into account the inherent two-time-scale characteristics, a composite suboptimal coordinated controller is devised through optimal problems of slow and fast subsystems. Furthermore, the closed-loop stability is proved by singular perturbation theory. Finally, simulation and experimental studies are provided to corroborate our theoretical results. It is shown that the proposed method can effectively improve the speed tracking and torque synchronization performance of the rigidly connected dual-PMSM system simultaneously.

Distributed Coordination Control of Networked Lagrangian Systems With Velocity and Input Constraints Over Event-Triggered Communication

In this paper, the coordination control problem of networked Euler-Lagrange (E-L) systems with velocity and input constraints over event-triggered communication is considered. A novel distributed controller is proposed to achieve the control objective under reasonable initial conditions. Unlike existing methods, neither the proposed controller nor the event-triggered scheme relies on any global information of the communication graph. Also, Zeno behavior is proved to be non-existent. In addition, the constraints on the system velocity and input will not be violated. Finally, case studies and experiment results are provided to show the effectiveness of the proposed method.

Adaptive event-triggered coordination control of unknown autonomous underwater vehicles under communication link faults

Coordination control of autonomous underwater vehicles finds broad applications in various marine activities. This paper focuses on the adaptive event-triggered coordination control problem of autonomous underwater vehicles under the effects of nonlinear and coupled dynamics, unknown system parameters, and communication link faults. The limited communication capacity is considered and an event-triggered distributed observer is designed under the effects of communication link faults. Reinforcement learning method is implemented to learn optimal coordination controller to achieve the position formation and the attitude synchronization for autonomous underwater vehicles with unknown dynamics. Simulation results verify the effectiveness of the proposed approach.

Optimal-Consensus-Based Event-Triggered Control Strategy for Island AC Microgrids

This article proposed an optimal-consensus-based even t-triggered control strategy to coordinate multiple distributed generators (DGs) in an alternative current (ac) microgrid. The proposed control strategy integrated the average bus voltage recovery and the proportional reactive power sharing by turning the coordinated control problem into a convex optimization problem, which realized the bus voltage control and proportional reactive power sharing of the DGs in one controller so that the controller structure is significantly simplified. Accordingly, the controller provided an asynchronous event-triggered mechanism considering the finite availability of communication resources, which reduces communication burdens and avoids Zeno behaviors. The sufficient conditions are demonstrated using the Lyapunov function for maintaining the stability of the proposed control strategy. Several simulations are exhibited using the MATLAB/Simulink platform and the results are reviewed to validate the effectiveness of the proposed control strategy for enhancing the ac microgrid robustness and reducing communication burdens.

Event-driven fully distributed optimal coordinated control for Euler–Lagrange multi-agent systems with connectivity preservation

This paper studies the distributed optimal coordinated control problem for Euler–Lagrange multi-agent systems with connectivity preservation. The aim is to force agents to achieve the optimal solution minimizing the sum of the local objective functions while guaranteeing the connectivity of the communication graph. For practical purposes, the gradient vector of the local objective function is allowed to use only at the real-time generalized position instead of at the auxiliary system state. To make the control parameters independent of the global information and guarantee the fully distributed manner of controller, the adaptive control is introduced to update the coupling weights of the relative states among neighbors. Moreover, to reduce the resource for control updates, the event-driven communication is employed for the updates of both the relative states and the gradient of the connectivity-preserving potential function. Based on the Lyapunov analysis framework, it is proved that agents can converge to the optimal solution with connectivity preservation and Zeno behavior is excluded for the two event-triggering conditions. Finally, the effectiveness of the proposed method is verified by a numerical simulation example.

Formation Trajectory Tracking of Discrete-Time Distributed Multi-AUVs with Nonconvex Control Inputs and Weak Communication

This paper considers the formation trajectory tracking problem of discrete-time distributed multi-AUVs (multiple autonomous underwater vehicles) with control input in a nonconvex set and weak communication. Firstly, a linear model of a single AUV is obtained by the feedback linearization of a single AUV model using the Lie derivative theory. Then, a linear equation of multi-AUV formation is obtained, and the formation coordinated control system of multi-AUVs based on the feedback linearization model is given. Secondly, the formation trajectory tracking problem of multi-AUVs is transformed into the coordination control problem of leader–followers formation. The coordination controller of the leader–followers formation under a weak communication environment is designed, and the controller satisfies the nonconvex constraints. Next, the coordination control problem of leader–followers formation is transformed into the stability of the error of leader and followers at zero by coordinate transformation. By establishing an appropriate Lyapunov–Krasovskii function, the corresponding linear matrix inequalities are obtained, and the condition of zero stability is obtained by solving the linear matrix inequalities of the leader–followers formation. Under this condition, stable trajectory tracking can be achieved in the multi-AUV formation. Finally, the stability of the designed coordination controller is verified by simulation experiments.

Research on Computer Carbon Reduction Control System of Energy Saving and Emission Reduction Comprehensive Enterprise

Construct an energy-saving and emission-reduction plan that minimizes the overall cost of the energy network. Applying the Hybrid optimal method solves the problem. Research on the optimal design of multi-energy cooperative integrated energy systems. Establish a central system control strategy, an energy system network structure, and an integrated energy management and control system. Finally, the coordination control problem of the proposed multi-energy cooperative integrated energy supply system is verified. The scenario comparison method is used to study the energy distribution effect under different scenarios. The results of this project show that adding flexible loads to the carbon market can significantly improve the overall economic and environmental benefits of the electricity market.

Fixed‐time velocity‐free coordination control for human‐robot systems without any approximation function

AbstractIn this paper, the fixed‐time coordination control problem is addressed for a class of uncertain human‐robot systems without velocity information. Specifically, due to the absence of approximation function, the developed control scheme is more practical. Firstly, a new fixed‐time velocity observer is introduced to estimate unmeasured velocities with the homogeneity theory. Then, the performance of the velocity observer in the presence of parametric uncertainties and non‐parametric uncertainties is analyzed seriously. Furthermore, a novel distributed continuous fixed‐time control (DCFTC) scheme is proposed. Compared with the existing velocity‐free controllers, fixed‐time convergence is achieved both for velocity estimation and trajectory tracking. More than that, distributed control is realized by using graph theoretic notions. Finally, numerical simulation results and experiment results demonstrate the efficacy and superior performance of the proposed velocity estimation method and control algorithms.

Formula omitted]-Synthesis robust coordinated control of variable speed wind power generators and electric vehicles to regulate frequency

Variable speed wind power generators (VSWPGs) can inevitably introduce power fluctuations and reduce the system inertia in modern power systems. On the other hand, VSWPGs also have certain frequency support ability due to the fast control characteristics of the power electronics in the converters. Therefore, it is urgently required for VSWPGs to regulate the frequency of the power system. Taking into consideration the internal and external uncertainty in the power systems and that frequent regulation actions of VSWPGs might lead to mechanical failures and aggravate the aging process of the wind power generators, a coordinated control method of VSWPGs and electric vehicles (EVs) for frequency regulation on the basis of μ-synthesis control is proposed in this paper. The EVs are modeled as energy aggregators, the VSWPGs are modeled under the derating control using the small-signal analysis method, and the dynamic frequency response model for the system with uncertainty is then built. Considering the power system parametric uncertainty, a μ-synthesis controller is implemented to tackle the coordinated control problem of VSWPGs and EVs regulating system frequency by means of the D-K iterative method. Then the comparisons through time-domain simulations are conducted to verify the presented coordinated strategy is able to overcome influence of uncertainty on system frequency and also has better dynamic frequency performance.

Attitude-Orbit Coupled Control of Gravitational Wave Detection Spacecraft with Communication Delays

In order to meet the position and attitude requirements of spacecrafts and test masses for gravitational-wave detection missions, the attitude-orbit coordination control of multiple spacecrafts and test masses is studied. A distributed coordination control law for spacecraft formation based on dual quaternion is proposed. By describing the relationship between spacecrafts and test masses in the desired states, the coordination control problem is converted into a consistent-tracking control problem in which each spacecraft or test mass tracks its desired states. An accurate attitude-orbit relative dynamics model of the spacecraft and the test masses is proposed based on dual quaternions. A cooperative feedback control law based on a consistency algorithm is designed to achieve the consistent attitude tracking of multiple rigid bodies (spacecraft and test mass) and maintain the specific formation configuration. Moreover, the communication delays of the system are taken into account. The distributed coordination control law ensures almost global asymptotic convergence of the relative position and attitude error in the presence of communication delays. The simulation results demonstrate the effectiveness of the proposed control method, which meets the formation-configuration requirements for gravitational-wave detection missions.