Cooperative Control Design Research Articles

Adaptive Non-singular Fast Terminal Sliding Mode Control for Car-Like Vehicles with Faded Neighborhood Information and Actuator Faults

This study addresses the problem of cooperative control design for a group of car-like vehicles encountering fading channels, actuator faults, and external disturbances. It is presumed that certain followers lack direct access to the states of the leader via a directed graph. This arises challenges in maintaining synchronization and coordination within the network. The proposed control strategy utilizes non-singular fast terminal sliding mode control to accelerate consensus tracking and enhance the convergence of the overall system. This controller is designed to mitigate the impact of actuator faults in the presence of fading channels in the communication network. The effects of such issues on team performance are rigorously analyzed. Based on the Lyapunov stability principle, it has been demonstrated that the controller is capable of providing satisfactory performance for the entire system despite these challenges. Moreover, vehicle synchronization can be effectively maintained. Numerical simulations are conducted to verify the theoretical findings.

Nonlinear predictor‐feedback cooperative adaptive cruise control of vehicles with nonlinear dynamics and input delay

SummaryWe construct a nonlinear predictor‐feedback cooperative adaptive cruise control (CACC) design for homogeneous vehicular platoons subject to actuators delays, which achieves: (i) positivity of vehicles' speed and spacing states, (ii) string stability of the platoon, (iii) stability of each individual vehicular system, and (iv) regulation to the desired reference speed (dictated by the leading vehicle) and spacing. The design relies on a nominal, nonlinear adaptive cruise control (ACC) law that we construct, which guarantees (i)–(iv) in the absence of actuator delay, and nonlinear predictor feedback. We consider a classical (for ACC/CACC design) third‐order, nonlinear model subject to input delay, for the vehicles' dynamics. The proofs of the theoretical guarantees (i)–(iv) rely on derivation of explicit estimates on solutions (both during open‐loop and closed‐loop operation), capitalizing on the ability of predictor feedback to guarantee complete delay compensation after the dead‐time interval has elapsed, and derivation of explicit conditions on initial conditions and parameters of the nominal control law. We also present consistent simulation results, considering a platoon of ten vehicles, which validate the design developed.

Multi-objective cooperative controller design for rapid state-of-charge balancing and flexible bus voltage regulation in shipboard DC microgrids

In this paper, a multi-objective cooperative (MOC) controller based on average consensus algorithm is designed to achieve rapid State-of-Charge (SoC) balancing, proportional load current sharing, and flexible DC bus voltage regulation for parallel battery storage units (BSUs) in shipboard DC microgrids. Different from the conventional secondary controllers, the designed MOC controller can simultaneously achieve the above three control objectives with a fully distributed manner without requiring multiple controllers, thereby effectively improving the system stability and reducing the communication burden. Furthermore, an optimized convergence factor is designed to accelerate SoC balancing, and pinning control is introduced to obtain flexible and accurate DC bus voltage regulation. The process of SoC balancing and current sharing analysis, SoC convergence performance analysis, large-signal stability analysis, and global steady-state analysis verifies the rationality and stability of the MOC controller. Finally, the Matlab/Simulink simulation and StarSim HIL experimental results demonstrate the effectiveness and robustness of the designed MOC controller in a shipboard DC microgrid under various testing scenarios.

Fault-Tolerant Cooperative Control Design for Car-Like Vehicles Subject to Actuator Faults and Fading Channels

Fault-Tolerant Cooperative Control Design for Car-Like Vehicles Subject to Actuator Faults and Fading Channels

Distributed Neural-Network-Based Cooperation Control for Teleoperation of Multiple Mobile Manipulators Under Round-Robin Protocol.

This article addresses the distributed cooperative control design for a class of sampled-data teleoperation systems with multiple slave mobile manipulators grasping an object in the presence of communication bandwidth limitation and time delays. Discrete-time information transmission with time-varying delays is assumed, and the Round-Robin (RR) scheduling protocol is used to regulate the data transmission from the multiple slaves to the master. The control task is to guarantee the task-space position synchronization between the master and the grasped object with the mobile bases in a fixed formation. A fully distributed control strategy including neural-network-based task-space synchronization controllers and neural-network-based null-space formation controllers is proposed, where the radial basis function (RBF) neural networks with adaptive estimation of approximation errors are used to compensate the dynamical uncertainties. The stability and the synchronization/formation features of the single-master-multiple-slaves (SMMS) teleoperation system are analyzed, and the relationship among the control parameters, the upper bound of the time delays, and the maximum allowable sampling interval is established. Experiments are implemented to validate the effectiveness of the proposed control algorithm.

Minimally Disruptive Cooperative Lane-Change Maneuvers

A lane-change maneuver on a congested highway could be severely disruptive or even infeasible without the cooperation of neighboring cars. However, cooperation with other vehicles does not guarantee that the performed maneuver will not have a negative impact on traffic flow unless it is explicitly considered in the cooperative controller design. In this letter, we present a socially compliant framework for cooperative lane-change maneuvers for an arbitrary number of CAVs on highways that aims to interrupt traffic flow as minimally as possible. Moreover, we explicitly impose feasibility constraints in the optimization formulation by using reachability set theory, leading to a unified design that removes the need for an iterative procedure used in prior work. We quantitatively evaluate the effectiveness of our framework and compare it against previously offered approaches in terms of maneuver time and incurred throughput disruption.

Cooperative Adaptive Cruise Control in a Mixed-Autonomy Traffic System: A Hybrid Stochastic Predictive Approach Incorporating Lane Change

This paper presents a stochastic and predictive control design approach for connected and automated vehicles (CAVs) in a mixed-autonomy traffic environment, where CAVs are able to react properly to uncertain maneuvers of human-driven vehicles (HVs). The proposed fully-automated cooperative adaptive cruise control (CACC) design leverages a discrete hybrid stochastic model predictive controller that automatically determines the vehicle's operating mode based on onboard sensors data and information received through vehicle-to-vehicle (V2V) communication. Operating modes include free following, warning, danger, emergency braking, and lane change. Although the controller mainly focuses on maintaining the desired velocity and distance among CAVs, it also allows HVs to perform lane-change maneuvers and merge into the platoon's lane when needed. In response to an HV's position in the lane and its probabilistic behavior, the controller may switch the CAV's operating mode to react accordingly. Considering free-following and emergency-braking modes leads to efficient and safe autonomous driving. Switching between warning, danger, and lane-change modes along with adjusting the steering angle to perform a lane-change maneuver, when needed, robustifies the platoon's performance against unexpected human-driven vehicle maneuvers. Simulation studies are conducted to validate the efficacy of the proposed control design approach. The performance of the proposed control design approach is also compared to a switching control using simulation studies.

Stability analysis and design of cooperative control for linear delta operator system

<abstract><p>This paper investigates the cooperative state feedback control problem for delta operator-based large-scale systems with independent subsystems. First, the state feedback controller is introduced to interconnect the adjacent subsystems into a closed-loop system. Second, the Lyapunov function in delta domain is constructed, and the linear matrix inequality method is used to design the cooperative state feedback stability controller for the whole large-scale interconnected system. Third, a performance index is introduced for the design of the optimal cooperative state feedback controller. Finally, stability of the closed-loop system is proved on the basis of stability theory, and simulation examples are given for showing the effectiveness of the design method.</p></abstract>

Human Decision-Making Modeling and Cooperative Controller Design for Human–Agent Interaction Systems

In this article, the problem of human intervention and autonomous controller design for human–agent interaction systems is addressed. In particular, a human drift diffusion model is developed for second-order linear multiagent systems subject to unknown external disturbances. The proposed human drift diffusion model can model human decision-making behavior using multiple sources of human decision-making information. Accurate human intervention timing is obtained by setting varying thresholds for different decision-making information. In addition, a fixed-time sliding mode adaptive behavioural controller is developed to execute human decisions in the framework of the null-space based behavioral control method. The controller guarantees that agents can follow human commands given an arbitrary initial task error and can finish tasks in fixed time. A simulation under various scenarios shows that the proposed human drift diffusion model is able to provide appropriate human intervention and the proposed controller can guarantee human command fulfillment within fixed time.

Structural basis of glucocorticoid receptor signaling bias.

Dissociation between the healthy and toxic effects of cortisol, a major stress-responding hormone has been a widely used strategy to develop anti-inflammatory glucocorticoids with fewer side effects. Such strategy falls short when treating brain disorders as timing and activity state within large-scale neuronal networks determine the physiological and behavioral specificity of cortisol response. Advances in structural molecular dynamics posit the bases for engineering glucocorticoids with precision bias for select downstream signaling pathways. Design of allosteric and/or cooperative control for the glucocorticoid receptor could help promote the beneficial and reduce the deleterious effects of cortisol on brain and behavior in disease conditions.

Robust Platoon Control in Mixed Traffic Flow Based on Tube Model Predictive Control

The design of cooperative adaptive cruise control is critical in mixed traffic flow, where connected and automated vehicles (CAVs) and human-driven vehicles (HDVs) coexist. Compared with pure CAVs, the major challenge is how to handle the prediction uncertainty of HDVs, which can cause significant state deviation of CAVs from planned trajectories. In most existing studies, model predictive control (MPC) is utilized to replan CAVs' trajectories to mitigate the deviation at each time step. However, as the replan process is usually conducted by solving an optimization problem with information through inter-vehicular communication, MPC methods suffer from heavy computational and communicational burdens. To address this limitation, a robust platoon control framework is proposed based on tube MPC in this paper. The prediction uncertainty is dynamically mitigated by the feedback control and restricted inside a set with a high probability. When the uncertainty exceeds the set or additional external disturbance emerges, the feedforward control is triggered to plan a ``tube'' (a sequence of the set), which can bound CAVs' actual trajectories. As the replan process is usually not required, the proposed method is much more efficient regarding computation and communication, compared with the MPC method. Comprehensive simulations are provided to validate the effectiveness of the proposed framework.

Motion information based avoidance control for 3-D multi-agent systems

This paper presents a closed-form cooperative avoidance control design for 3-dimensional rigid-body agents. New avoidance functions are designed to integrate the collision risk with the addition of motion and posture information. Time-varying sensing regions enable the conflict resolution actions only when there is a potential risk of collision, thus further reducing some unnecessary interference with other objectives. These characteristics lead to the less-conservative avoidance response, smoother maneuvers, and milder motion trajectories. The stability of the proposed method is analyzed and the corresponding proofs and guaranties for collision-free maneuvering, are provided. Performance comparisons are presented for two simulation scenarios, which illustrate the effectiveness and reliability of the new method.

Compact Cooperative Adaptive Cruise Control for Energy Saving: Air Drag Modelling and Simulation

This paper studies the value of communicated motion predictions in the longitudinal control of connected automated vehicles (CAVs). We focus on a safe cooperative adaptive cruise control (CACC) design and analyze the value of vehicle-to-vehicle (V2V) communication in the presence of uncertain front vehicle acceleration. The interest in CACC is motivated by the potential improvement in energy consumption and road throughput. In order to quantify this potential, we characterize experimentally the relationship between inter-vehicular gap, vehicle speed, and (reduction of) energy consumption for a compact plug-in hybrid electric vehicle. The resulting model is leveraged to show efficacy of our control design, which pursues small inter-vehicle gaps between consecutive CAVs and, therefore, improved energy efficiency. Our proposed control design is based on a robust model predictive control framework to systematically account for the system uncertainties. We present a set of thorough simulations aimed at quantifying energy efficiency improvement when vehicle states and predictions exchanged via V2V communication are used in the control law.

Design and field evaluation of cooperative adaptive cruise control with unconnected vehicle in the loop

To fully harvest the benefits of vehicular automation and connectivity in the mixed traffic, a cooperative longitudinal control strategy named Cooperative Adaptive Cruise Control with Unconnected vehicle in the loop (CACCu) has been proposed. When encountering an unconnected preceding vehicle, CACCu enables a Connected and Automated Vehicle (CAV) to benefit from communicating with a connected vehicle further ahead, rather than completely falling back to Adaptive Cruise Control (ACC). To validate the feasibility of CACCu, this study developed and tested a CACCu system with real vehicles in the field. A speed-command-based CACCu controller is designed and parameterized for optimizing the anticipated string stability. The experiment was conducted with two automated vehicles equipped with Mobileye sensors and Wi-Fi modules. The car-following performance of CACCu, in comparison with ACC and human driving (as the ego vehicle), was evaluated in the real-traffic scenarios constructed using NGSIM vehicle trajectory data. Over the 6 test runs for each control method, it was found that CACCu reduced 10.8% acceleration Root Mean Square (RMS), 60.8% spacing error RMS and 6.2% fuel consumption from ACC’s, indicating advantages of CACCu in control accuracy, ride comfort and energy efficiency. Compared with human driving, CACCu also reduced 17.6% acceleration and 13.4% fuel consumption. More importantly, the CACCu was able to efficiently avoid the traffic disturbance amplifications that frequently happened to ACC and human driving, which means the string stability has been significantly improved by the CACCu.

Adaptive MLP neural network controller for consensus tracking of Multi-Agent systems with application to synchronous generators

In this study a novel cooperative controller design is developed to tackle the consensus tracking problem of Multi-Agent systems (MAS) based on multilayer perceptron neural network (MLPNN), applied on a distributed synchronous generator (SG) Multi-Agent system in presence of model uncertainties and external disturbances. Application of MLPNN in controller design can lead to smoother system response and can neutralize the impacts of model uncertainties. Furthermore, the proposed method benefits from a novel algorithm formerly known as error backpropagation (BP) algorithm to update and to regulate the weights of MLPNN adaptively based on the principles of consensus error. The proposed strategy can be very effective in control of the distributed SG Multi-Agent system due to its ability for system identification, parameter estimation, and disturbance approximation. Moreover, the utilization of neural networks can meet the criterion to make the consensus error uniformly ultimately bounded. Ultimately, simulation results illustrate the applicability and effectiveness of the novel MLPNN controller to model the system uncertainties and to deal with external disturbances of the distributed SG Multi-Agent system.

Cooperative Networked Control Based on a Time-Varying Lyapunov Function

This paper treats switched cooperative control design of a networked system composed of a set of linear time-invariant (LTI) plants. Our main objective is to synthesize a cooperative resource-sharing dynamic strategy assuring stability and a $$\mathscr {H}_2$$ guaranteed performance for the overall system. This strategy relies upon a coordinator that manages the control signal transmission among the LTI plants. Mathematically, the coordinator is described as a switching rule that chooses at each sampling time one of the plants to receive the updated control signal, while the others must hold constant their previously received ones. The design conditions are based on a time-varying convex Lyapunov function and expressed in terms of linear matrix inequalities, being easier to solve than other methodologies available in the literature. The proposed control strategy has been experimentally validated by simultaneously controlling two different mechanical systems, an inverted pendulum and an active suspension. Experimental results and simulations show the efficiency of the proposed control technique.

Active Fault‐Tolerant/Active Passive Intrusion‐Tolerant H∞ Cooperative Control of Discrete NCS under the Background of Big Data

For the linear discrete networked control system (NCS) which may suffer DoS attack on both sides of the controller, when the actuator has time‐varying failure, the intelligent sensor unit uses wireless sensors to collect data. According to the large amount of data collected, the active fault tolerance/active passive capacity of linear discrete NCS under the discrete event‐triggered communication mechanism (DETCS) is studied. The problem of cooperative controller design is discussed. Firstly, a linear discrete NCS model integrating DETCS, actuator fault, and network attack is established. Then, based on the idea of integral sliding mode control, an active fault‐tolerant/attack active passive intrusion‐tolerant cooperative controller is designed, and the actuator attack side network attack and sensor side network attack are extended to the state to obtain a new state vector. Then, an adaptive Kalman filter estimator (AKF) estimates the fault and attack information and then adjusts the initial fault‐tolerant/intrusion‐tolerant cooperative controller in real time according to the estimated information obtained by the adaptive Kalman filter estimator; finally, the MATLAB simulation example is used to verify the improvement of system performance by the designed control law and the saving of network resources by the introduction of DETCS.

Correction to: Novel Cooperative Controller Design of Heterogeneous Energy Storages for Economic Applications in Electric Railway Systems

Correction to: Novel Cooperative Controller Design of Heterogeneous Energy Storages for Economic Applications in Electric Railway Systems

Optimal Tracking Cooperative Control for Cyber-Physical Systems: Dynamic Fault-Tolerant Control and Resilient Management

This article proposes a novel dynamic fault-tolerant control model to address the optimal tracking cooperative control problem for cyber-physical systems, by considering that all systems can be endowed as a multiagent system and the admissible levels of the actuator fault can be resiliently management. Different from previous works, the feedback gain for the cooperative controller design is no longer fixed, and actuator outage behaviors can be solved by a resilient control way. By introducing a sampling manner, a robust optimal framework is first developed to determine the appropriate feedback gain under a cost constraint for the dynamic fault model. The dynamic fault-tolerant control protocol is, then, designed to achieve the cooperative behaviors. Moreover, a fault management mechanism is proposed, in which the fault parameter is reset as an initial value when the fault growth is greater than the admissible level. By this design, the tracking cooperative behaviors can be achieved in a resilient management process. Two examples are presented to illustrate the effectiveness of the proposed theories.

Novel Cooperative Controller Design of Heterogeneous Energy Storages for Economic Applications in Electric Railway Systems

Owing to the consistently increased request about efficiency improvement through utilization of regenerative energy from braking railway vehicle in the DC electric railway systems, there are a lot of researches about energy storage applications. However, the feasibility of ESS technology application is usually limited by economic factors rather than technical factors of it. Therefore, this paper proposes the application of heterogeneous energy storage system based on ramp-rate-considered cooperative controller in order to improve economics. The heterogeneous combination of energy storage devices with different technical advantages can gives a more economical solution to respond to individual specifications required by the system. A ramp-rate-considered cooperative controller for the heterogeneous ESS application is presented numerically, and effectiveness of the proposed method has been verified through electromagnetic transient simulation.