The Experts below are selected from a list of 165 Experts worldwide ranked by ideXlab platform

Tongwen Chen - One of the best experts on this subject based on the ideXlab platform.

  • Setpoint dynamic compensation via output feedback control with network induced time delays
    2015 American Control Conference (ACC), 2015
    Co-Authors: Yi Jiang, Tianyou Chai, Tongwen Chen
    Abstract:

    In Operational control of most industrial systems, two Layers, the control Layer and the Operational Layer, exist, and are communicated via networks. Network induced time delays have negative impact on Operational control performance. For a class of industrial processes, this paper proposes a method of setpoint dynamic compensation based on output feedback control with network induced stochastic delays. Firstly, given a process, a multi-input multi-output PID controller with an adjustable response speed is designed to stabilize the plant without any steady-state error for setpoint tracking. Secondly, a network stochastic time-delay model is established by analyzing the characteristics of data transmission in the Ethernet, and is used in designing an Operational Layer controller based on output feedback. In particular, a condition to guarantee asymptotic stability of the whole closed-loop system is given. Finally, a simulation experiment in an industrial flotation process is employed to demonstrate the effectiveness of the proposed method.

  • ACC - Setpoint dynamic compensation via output feedback control with network induced time delays
    2015 American Control Conference (ACC), 2015
    Co-Authors: Yi Jiang, Tianyou Chai, Tongwen Chen
    Abstract:

    In Operational control of most industrial systems, two Layers, the control Layer and the Operational Layer, exist, and are communicated via networks. Network induced time delays have negative impact on Operational control performance. For a class of industrial processes, this paper proposes a method of setpoint dynamic compensation based on output feedback control with network induced stochastic delays. Firstly, given a process, a multi-input multi-output PID controller with an adjustable response speed is designed to stabilize the plant without any steady-state error for setpoint tracking. Secondly, a network stochastic time-delay model is established by analyzing the characteristics of data transmission in the Ethernet, and is used in designing an Operational Layer controller based on output feedback. In particular, a condition to guarantee asymptotic stability of the whole closed-loop system is given. Finally, a simulation experiment in an industrial flotation process is employed to demonstrate the effectiveness of the proposed method.

Yi Jiang - One of the best experts on this subject based on the ideXlab platform.

  • Operational Feedback Control of Industrial Process Under Wireless Packet Disordering
    2019 International Conference on Advanced Mechatronic Systems (ICAMechS), 2019
    Co-Authors: Jialu Fan, Wenkuan Feng, Yi Jiang
    Abstract:

    The goal of feedback control is to control the operation of the whole industrial process, which is to control the efficiency of industrial manufacture, the consumption of industrial materials and other indexes, which can reflect the Operational qualities, by sampling and compensating them and make them steadily operated in estimated range. Traditional Operational control method adopts manual setpoints of equipment Layer loop. However, this method can't automatically adjust setpoints as industrial process proceeds and will even causes breakdown. This paper proposes an Operational feedback control method of industrial process. This paper analyzes the unreliable communication features of wireless network and establishes the model of network communication under packet disordering. Based on this, this paper designs the Operational controllers of the system without communication problems and with packet disordering problem. To verify the effectiveness of control method, this paper utilizes flotation industrial process as the background and establishes its mathematical model. Based on that, this paper conducts the simulation experiment using the Operational feedback control in both equipment Layer and Operational Layer on MATLAB platform. The final result shows that the designed controller in this paper is effective under the network system with packet disordering.

  • Setpoint dynamic compensation via output feedback control with network induced time delays
    2015 American Control Conference (ACC), 2015
    Co-Authors: Yi Jiang, Tianyou Chai, Tongwen Chen
    Abstract:

    In Operational control of most industrial systems, two Layers, the control Layer and the Operational Layer, exist, and are communicated via networks. Network induced time delays have negative impact on Operational control performance. For a class of industrial processes, this paper proposes a method of setpoint dynamic compensation based on output feedback control with network induced stochastic delays. Firstly, given a process, a multi-input multi-output PID controller with an adjustable response speed is designed to stabilize the plant without any steady-state error for setpoint tracking. Secondly, a network stochastic time-delay model is established by analyzing the characteristics of data transmission in the Ethernet, and is used in designing an Operational Layer controller based on output feedback. In particular, a condition to guarantee asymptotic stability of the whole closed-loop system is given. Finally, a simulation experiment in an industrial flotation process is employed to demonstrate the effectiveness of the proposed method.

  • ACC - Setpoint dynamic compensation via output feedback control with network induced time delays
    2015 American Control Conference (ACC), 2015
    Co-Authors: Yi Jiang, Tianyou Chai, Tongwen Chen
    Abstract:

    In Operational control of most industrial systems, two Layers, the control Layer and the Operational Layer, exist, and are communicated via networks. Network induced time delays have negative impact on Operational control performance. For a class of industrial processes, this paper proposes a method of setpoint dynamic compensation based on output feedback control with network induced stochastic delays. Firstly, given a process, a multi-input multi-output PID controller with an adjustable response speed is designed to stabilize the plant without any steady-state error for setpoint tracking. Secondly, a network stochastic time-delay model is established by analyzing the characteristics of data transmission in the Ethernet, and is used in designing an Operational Layer controller based on output feedback. In particular, a condition to guarantee asymptotic stability of the whole closed-loop system is given. Finally, a simulation experiment in an industrial flotation process is employed to demonstrate the effectiveness of the proposed method.

Tianyou Chai - One of the best experts on this subject based on the ideXlab platform.

  • Setpoint dynamic compensation via output feedback control with network induced time delays
    2015 American Control Conference (ACC), 2015
    Co-Authors: Yi Jiang, Tianyou Chai, Tongwen Chen
    Abstract:

    In Operational control of most industrial systems, two Layers, the control Layer and the Operational Layer, exist, and are communicated via networks. Network induced time delays have negative impact on Operational control performance. For a class of industrial processes, this paper proposes a method of setpoint dynamic compensation based on output feedback control with network induced stochastic delays. Firstly, given a process, a multi-input multi-output PID controller with an adjustable response speed is designed to stabilize the plant without any steady-state error for setpoint tracking. Secondly, a network stochastic time-delay model is established by analyzing the characteristics of data transmission in the Ethernet, and is used in designing an Operational Layer controller based on output feedback. In particular, a condition to guarantee asymptotic stability of the whole closed-loop system is given. Finally, a simulation experiment in an industrial flotation process is employed to demonstrate the effectiveness of the proposed method.

  • ACC - Setpoint dynamic compensation via output feedback control with network induced time delays
    2015 American Control Conference (ACC), 2015
    Co-Authors: Yi Jiang, Tianyou Chai, Tongwen Chen
    Abstract:

    In Operational control of most industrial systems, two Layers, the control Layer and the Operational Layer, exist, and are communicated via networks. Network induced time delays have negative impact on Operational control performance. For a class of industrial processes, this paper proposes a method of setpoint dynamic compensation based on output feedback control with network induced stochastic delays. Firstly, given a process, a multi-input multi-output PID controller with an adjustable response speed is designed to stabilize the plant without any steady-state error for setpoint tracking. Secondly, a network stochastic time-delay model is established by analyzing the characteristics of data transmission in the Ethernet, and is used in designing an Operational Layer controller based on output feedback. In particular, a condition to guarantee asymptotic stability of the whole closed-loop system is given. Finally, a simulation experiment in an industrial flotation process is employed to demonstrate the effectiveness of the proposed method.

  • Wireless network based Operational optimization and control for a class of industrial processes
    2015 10th Asian Control Conference (ASCC), 2015
    Co-Authors: Lei Wang, Tianyou Chai
    Abstract:

    Recently, wireless networks are gradually applied into on-line monitoring and open-loop Operational control in most industrial processes. However, it tends to design double-closed-loop controllers for dual-Layer structure, including the control Layer and the Operational Layer. This paper creatively studies wireless network based Operational optimization and feedback control for a class of industrial processes, in order to overcome the negative effect on Operational performance by unreliable wireless communications. Firstly, a wireless communication model integrating packet dropout and noise is proposed. Secondly, a LQR controller and model predictive controller are designed for the control Layer and the Operational Layer, respectively. Specifically, a condition to guarantee asymptotic stability of the double-closed-loop system is given. Finally, a simulation in a flotation process is conducted to demonstrate the effectiveness of the proposed method.

Meng Wang - One of the best experts on this subject based on the ideXlab platform.

  • A hierarchical approach for splitting truck platoons near network discontinuities
    Transportation Research Part B-methodological, 2019
    Co-Authors: Aurélien Duret, Meng Wang, Andres Ladino
    Abstract:

    Abstract Truck platooning has attracted substantial attention due to its pronounced benefits in saving energy and promising business model in freight transportation. However, one prominent challenge for the successful implementation of truck platooning is the safe and efficient interaction with surrounding traffic, especially at network discontinuities where mandatory lane changes may lead to the decoupling of truck platoons. This contribution puts forward an efficient method for splitting a platoon of vehicles near network merges. A model-based bi-level control strategy is proposed. A supervisory tactical strategy based on a first-order car-following model with bounded acceleration is designed to maximize the flow at merge discontinuities. The decisions taken at this level include optimal vehicle order after the merge, new equilibrium gaps of automated trucks at the merging point, and anticipation horizon that the platoon members start to track the new equilibrium gaps. The lower-level Operational Layer uses a third-order longitudinal dynamics model to compute the optimal truck accelerations so that new equilibrium gaps are created when merging vehicles start to change lane and the transient maneuvers are efficient, safe and comfortable. The tactical decisions are derived from an analytic car-following model and the Operational accelerations are controlled via model predictive control with guaranteed stability. Simulation experiments are provided in order to test the feasibility and demonstrate the performance and robustness of the proposed strategy.

  • A Hierarchical Model-Based Optimization Control Approach for Cooperative Merging by Connected Automated Vehicles
    IEEE Transactions on Intelligent Transportation Systems, 1
    Co-Authors: Na Chen, Bart Van Arem, Tom Alkim, Meng Wang
    Abstract:

    Gap selection and dynamic speed profiles of interacting vehicles at on-ramps affect the safety and efficiency of highway merging sections. This paper puts forward a hierarchical control approach for Connected Automated Vehicles (CAVs) to achieve efficient and safe merging operations. A tactical Layer controller employs a second-order car-following model with a cooperative merging mode to represent a cooperative merging process and generates an optimal vehicle merging sequence and time instants when on-ramp CAVs start to adapt their speeds and positions to prepare merging into the target gaps respectively. An Operational Layer controller is designed based on Model Predictive Control (MPC). It uses a third-order vehicle dynamics model and optimizes desired accelerations for CAVs and the time instants when the on-ramp CAVs initiate the lane-changing executions respectively. Both the tactical Layer controller and Operational Layer controller derive their control commands by minimizing an objective function for different time horizons. The objective function penalizes deviations of CAVs' inter-vehicle gaps to their desired values, relative speeds to their direct predecessors, and actual or desired accelerations, subject to constraints on velocities, actual or desired accelerations, and inter-vehicle gaps. The performance of the proposed hierarchical control framework and a benchmark on-ramp merging method using a first-in-first-out rule to determine the merging sequence is demonstrated under 135 scenarios with different initial conditions, desired time gap settings, and numbers of on-ramp vehicles. The experimental results show the superiority of the hierarchical control approach.

  • A Hybrid Submicroscopic-Microscopic Traffic Flow Simulation Framework
    IEEE Transactions on Intelligent Transportation Systems, 1
    Co-Authors: Freddy Antony Mullakkal-babu, Bart Van Arem, Meng Wang, Barys Shyrokau, Riender Happee
    Abstract:

    Current lane-based microscopic traffic simulators combine car-following and lane changing logic to describe the (often discrete) lateral vehicle motion on multi-lane road segments. However, the simulated lateral trajectories are physically unplausible and inside-lane behavior such as lane-keeping and curve negotiation cannot be modelled. In this work, we integrate lateral vehicle dynamics and yaw motion into a traffic simulation framework, aiming to describe lateral motion and vehicle interactions with more precision. The resulting framework consists of two coupled Layers, an upper tactical level that plans maneuvers such as lane-changing; and a lower Operational Layer with a control module (steering and acceleration control) that operates in a closed loop with the bicycle model of vehicle dynamics. The feedback mechanism between the Layers allows for dynamic trajectory re-planning. Unlike the microscopic traffic models, the proposed framework accounts for lateral vehicle dynamics and yaw motion; provides additional variables such as vehicle heading and front wheel steering angle; and is hence termed as submicroscopic. Case study results demonstrate the power of the framework to include lateral maneuvers such as curve negotiation, corrective steering, lane change abortion and fragmented lane changing. The framework was Operationalized to model multi-lane traffic flow consisting of human-driven vehicles. At the macroscopic level, the traffic flow simulation can reproduce phenomena such as capacity drop. Thus the framework preserves the properties of the component models and at the same time describe the continuous 2-D planar movement of vehicles.

Bart Van Arem - One of the best experts on this subject based on the ideXlab platform.

  • A Hierarchical Model-Based Optimization Control Approach for Cooperative Merging by Connected Automated Vehicles
    IEEE Transactions on Intelligent Transportation Systems, 1
    Co-Authors: Na Chen, Bart Van Arem, Tom Alkim, Meng Wang
    Abstract:

    Gap selection and dynamic speed profiles of interacting vehicles at on-ramps affect the safety and efficiency of highway merging sections. This paper puts forward a hierarchical control approach for Connected Automated Vehicles (CAVs) to achieve efficient and safe merging operations. A tactical Layer controller employs a second-order car-following model with a cooperative merging mode to represent a cooperative merging process and generates an optimal vehicle merging sequence and time instants when on-ramp CAVs start to adapt their speeds and positions to prepare merging into the target gaps respectively. An Operational Layer controller is designed based on Model Predictive Control (MPC). It uses a third-order vehicle dynamics model and optimizes desired accelerations for CAVs and the time instants when the on-ramp CAVs initiate the lane-changing executions respectively. Both the tactical Layer controller and Operational Layer controller derive their control commands by minimizing an objective function for different time horizons. The objective function penalizes deviations of CAVs' inter-vehicle gaps to their desired values, relative speeds to their direct predecessors, and actual or desired accelerations, subject to constraints on velocities, actual or desired accelerations, and inter-vehicle gaps. The performance of the proposed hierarchical control framework and a benchmark on-ramp merging method using a first-in-first-out rule to determine the merging sequence is demonstrated under 135 scenarios with different initial conditions, desired time gap settings, and numbers of on-ramp vehicles. The experimental results show the superiority of the hierarchical control approach.

  • A Hybrid Submicroscopic-Microscopic Traffic Flow Simulation Framework
    IEEE Transactions on Intelligent Transportation Systems, 1
    Co-Authors: Freddy Antony Mullakkal-babu, Bart Van Arem, Meng Wang, Barys Shyrokau, Riender Happee
    Abstract:

    Current lane-based microscopic traffic simulators combine car-following and lane changing logic to describe the (often discrete) lateral vehicle motion on multi-lane road segments. However, the simulated lateral trajectories are physically unplausible and inside-lane behavior such as lane-keeping and curve negotiation cannot be modelled. In this work, we integrate lateral vehicle dynamics and yaw motion into a traffic simulation framework, aiming to describe lateral motion and vehicle interactions with more precision. The resulting framework consists of two coupled Layers, an upper tactical level that plans maneuvers such as lane-changing; and a lower Operational Layer with a control module (steering and acceleration control) that operates in a closed loop with the bicycle model of vehicle dynamics. The feedback mechanism between the Layers allows for dynamic trajectory re-planning. Unlike the microscopic traffic models, the proposed framework accounts for lateral vehicle dynamics and yaw motion; provides additional variables such as vehicle heading and front wheel steering angle; and is hence termed as submicroscopic. Case study results demonstrate the power of the framework to include lateral maneuvers such as curve negotiation, corrective steering, lane change abortion and fragmented lane changing. The framework was Operationalized to model multi-lane traffic flow consisting of human-driven vehicles. At the macroscopic level, the traffic flow simulation can reproduce phenomena such as capacity drop. Thus the framework preserves the properties of the component models and at the same time describe the continuous 2-D planar movement of vehicles.