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  • 1. Bemporad, Alberto
    et al.
    Di Cairano, Stefano
    Henriksson, Erik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl H.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Hybrid Model Predictive Control Based on Wireless Sensor Feedback: an experimental study2007In: Proceedings of the 46th IEEE Conference on Decision and Control, New Orleans, Louisiana, USA., 2007, p. 5062-5067Conference paper (Refereed)
    Abstract [en]

    This paper presents the design and the experimental validation of model predictive control (MPC) of a hybrid dynamical process based on measurements collected by a wireless sensor network. The proposed setup is the prototype of an industrial application in which a remote station controls the process via wireless network links. The experimental platform is a laboratory process consisting of four infrared lamps, controlled in pairs by two on/off switches, and of a transport belt, where moving parts equipped with wireless sensors are heated by the lamps. By approximating the stationary heat spatial distribution as a piecewise affine function of the position along the belt, the resulting plant model is a hybrid dynamical system. The control architecture is based on the reference governor approach: the process is actuated by a local controller, while a hybrid MPC algorithm running on a remote base station sends optimal belt velocity set-points and lamp on/off commands over a network link exploiting the information received through the wireless network. A discrete-time hybrid model of the process is used for the hybrid MPC algorithm and for the state estimator.

  • 2. Bemporad, Alberto
    et al.
    Di Cairano, Stefano
    Henriksson, Erik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl H.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Hybrid model predictive control based on wireless sensor feedback: An experimental study2010In: International Journal of Robust and Nonlinear Control, ISSN 1049-8923, E-ISSN 1099-1239, Vol. 20, no 2, p. 209-225Article in journal (Refereed)
    Abstract [en]

    Design and experimental validation of model predictive control (MPC) of a hybrid dynamical laboratory process with wireless sensors is presented. The laboratory process consists of four infrared lamps, controlled in pairs by two on/off switches, and of a transport belt, where moving parts equipped with wireless sensors are heated by the lamps. The process, which is motivated by heating processes in the plastic and printing industry, presents interesting hybrid dynamics. By approximating the stationary heat spatial distribution as a piecewise affine function of the position along the belt, the resulting plant model is a hybrid dynamical system. The control architecture is based on the reference governor approach: the process is actuated by a local controller, while a hybrid MPC algorithm running on a remote base station sends optimal belt velocity setpoints and lamp on/off commands over a wireless link, exploiting the sensor information received through the wireless network. A discrete-time hybrid model of the process is used for the hybrid MPC algorithm and for the state estimator. The physical modelling of the process and the hybrid MPC algorithm are presented in detail, together with the hardware and software architectures. The experimental results show that the presented theoretical framework is well suited for control of the new laboratory process, and that the process can be used as a prototype system for evaluating hybrid and networked control strategies.

  • 3.
    Henriksson, Erik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Compensating for Unreliable Communication Links in Networked Control Systems2009Licentiate thesis, monograph (Other academic)
    Abstract [en]

    Control systems utilizing wireless sensor and actuator networks can be severely affectedby the properties of the communication links. Radio fading and interferencemay cause communication losses and outages in situations when the radio environmentis noisy and low transmission power is desirable. This thesis proposes amethod to compensate for such unpredictable losses of data in the feedback controlloop by introducing a predictive outage compensator (POC). The POC is a filter tobe implemented at the receiver sides of networked control systems where it generatesartificial samples when data are lost. If the receiver node does not receive thedata, the POC suggests a command based on the history of past data. It is shownhow to design, tune and implement a POC. Theoretical bounds and simulationresults show that a POC can improve the closed-loop control performance undercommunication losses considerably. We provide a deterministic and a stochasticmethod to synthesize POCs. Worst-case performance bounds are given that relatethe closed-loop performance with the complexity of the compensator. We also showthat it is possible to achieve good performance with a low-order implementationbased on Hankel norm approximation. Tradeoffs between achievable performance,communication loss length, and POC order are discussed. The results are illustratedon a simulated example of a multiple-tank process. The thesis is concludedby an experimental validation of wireless control of a physical lab process. Herethe controller and the physical system are separated geographically and interfacedthrough a wireless medium. For the remote control we use a hybrid model predictivecontroller. The results reflect the difficulties in wireless control as well as theyhighlight the flexibility and possibilities one obtains by using wireless instead of awired communication medium.

  • 4.
    Henriksson, Erik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Predictive Control for Wireless Networked Systems in Process Industry2014Doctoral thesis, monograph (Other academic)
    Abstract [en]

    Wireless networks in industrial process control enable new system architectures and designs. However, wireless control systems can be severely affected by the imperfections of the communication links. This thesis proposes new methods to handle such imperfections by adding additional components in the control loop, or by adapting sampling intervals and control actions.

    First, the predictive outage compensator is proposed. It is a filter which is implemented at the receiver side of networked control systems. There it generates predicted samples when data are lost, based on past data. The implementation complexity of the predictive outage compensator is analyzed. Simulation and experimental results show that it can considerably improve the closed-loop control performance under communication losses.

    The thesis continues with presenting an algorithm for controlling multiple processes on a shared communication network, using adaptive sampling intervals. The methodology is based on model predictive control, where the controller jointly decides the optimal control signal to be applied as well as the optimal time to wait before taking the next sample. The approach guarantees conflict-free network transmissions for all controlled processes. Simulation results show that the presented control law reduces the required amount of communication, while maintaining control performance.

    The third contribution of the thesis is an event-triggered model predictive controller for use over a wireless link. The controller uses open-loop optimal control, re-computed and communicated only when the system behavior deviates enough from a prediction. Simulations underline the methods ability to significantly reduce computation and communication effort, while guaranteeing a desired level of system performance.

    The thesis is concluded by an experimental validation of wireless control for a physical lab process. A hybrid model predictive controller is used, connected to the physical system through a wireless medium. The results reflect the advantages and challenges in wireless control.

  • 5.
    Henriksson, Erik
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Quevedo, Daniel
    University of Newcastle, Australia.
    Sandberg, Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl H.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Self-Triggered Model Predictive Control for Network Scheduling and Control2012In: Advanced Control of Chemical Processes, Vol. 8. Part 1 2012, 2012, p. 432-438Conference paper (Refereed)
    Abstract [en]

    Herein we present an algorithm for controlling LTI processes using an adaptive sampling interval where the controller at every sampling instant not only computes the new control command but also decides the time interval to the next sample. The approach relies on MPC where the cost function depends on the control performance as well as the cost for sampling. The paper presents a method for synthesizing such a predictive controller and gives explicit conditions for when it is stabilizing. Further it is shown that the optimization problem may be solved off-line and that the controller may be implemented as a lookup table of state feedback gains. The paper is concluded with a numerical example.

  • 6. Henriksson, Erik
    et al.
    Quevedo, D.E
    Peters, E.G.W.
    Sandberg, Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Multiple loop self-triggered model predictive control for network scheduling and control2015In: IEEE Transactions on Control Systems Technology, ISSN 1063-6536, E-ISSN 1558-0865, Vol. 23, no 6, p. 2167-2181Article in journal (Refereed)
    Abstract [en]

    We present an algorithm for controlling and scheduling multiple linear time-invariant processes on a shared bandwidth-limited communication network using adaptive sampling intervals. The controller is centralized and not only computes at every sampling instant the new control command for a process but also decides the time interval to wait until taking the next sample.The approach relies on model predictive control ideas, where the cost function penalizes the state and control effort as well as the time interval until the next sample is taken. The latter is introduced to generate an adaptive sampling scheme for the overall system such that the sampling time increases as the norm of the system state goes to zero. This paper presents a method for synthesizing such a predictive controller and gives explicit sufficient conditions for when it is stabilizing. Further explicit conditions are given that guarantee conflict free transmissions on the network. It is shown that the optimization problem may be solved offline and that the controller can be implemented as a lookup table of state feedback gains. The simulation studies which compare the proposed algorithm to periodic sampling illustrate potential performance gains.

  • 7.
    Henriksson, Erik
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Sandberg, Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Predictive Compensation for Communication Outages in Networked Control Systems2008In: Proceedings of the 47th IEEE Conference on Decision and Control, Cancun, Mexico, 2008, p. 2063-2068Conference paper (Refereed)
    Abstract [en]

    A predictive outage compensator co-located with the actuator node in a networked control system can be used to counteract unpredictable losses of data in the feedback control loop. When a new control command is not received at the actuator node at an appropriate time instance, the predictive outage compensator suggests a replacement command based on the history of past control commands. It is shown that a simple tuning phase together with the monitoring of the control history can lead to a compensator that can improve the closed-loop control performance under communication outages considerably compared to traditional schemes. Worst case performance bounds are given that relate the quality of the tuning phase and the complexity of the compensator with the length of the communication outage period. Zero-order-hold (holding the past control command if the current is lost) and applying an a priori decided constant signal (using a redefined value on the control command if the current is lost) are special cases of the more general compensation scheme presented. The predictive outage compensator is illustrated through computer simulation with communication outages.

  • 8.
    Henriksson, Erik
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Sandberg, Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Reduced-Order Predictive Outage Compensators for Networked Systems2009In: Proceedings of the combined 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference, Shanghai, P.R. China, 2009, p. 3775-3780Conference paper (Refereed)
    Abstract [en]

    Control systems utilizing wireless sensor and actuator networks can be severely affected by the properties of the wireless links. Radio fading and interference may cause communication outage of several samples in situations when the radio environment is noisy and low transmission power is desirable. We propose a method to compensate for outages by introducing a predictive outage compensator (POC), which is a filter to be implemented at the receiver sides of networked control systems and that generates artificial samples during the outage. The main contribution of the paper is to show that a POC can be derived based on a Kalman filter formulation and that it is possible to achieve good performance with a low-order implementation based on Hankel norm approximation. Tradeoffs between achievable closed-loop performance, outage length, and POC order are discussed. The results are illustrated on a simulated example of a multiple-tank process.

  • 9.
    Lehmann, Daniel
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Henriksson, Erik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Event-Triggered Model Predictive Control of Discrete-Time Linear Systems Subject to Disturbances2013In: 2013 European Control Conference (ECC), IEEE , 2013, p. 1156-1161Conference paper (Refereed)
    Abstract [en]

    This paper presents an approach to event-triggered model predictive control for discrete-time linear systems subject to input and state constraints as well as exogenous disturbances. Stability properties are derived by evaluating the difference between the event-triggered implementation and the conventional time-triggered scheme. It is shown that the event-triggered implementation, in stationarity, is able to keep the state in an explicitly computable set given by the disturbance bound and the event threshold. Simulation results underline the effectiveness of the proposed scheme in terms of reducing the communication and computational effort while guaranteeing a desired performance.

1 - 9 of 9
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