• Data-driven model-free adaptive control for a class of MIMO nonlinear discrete-time systems

      Hou, Zhongsheng; Jin, Shangtai; Beijing Jiaotong University, Beijing, China (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2011)
      In this paper, a data-driven model-free adaptive control (MFAC) approach is proposed based on a new dynamic linearization technique (DLT) with a novel concept called pseudo-partial derivative for a class of general multiple-input and multiple-output nonlinear discrete-time systems. The DLT includes compact form dynamic linearization, partial form dynamic linearization, and full form dynamic linearization. The main feature of the approach is that the controller design depends only on the measured input/output data of the controlled plant. Analysis and extensive simulations have shown that MFAC guarantees the bounded-input bounded-output stability and the tracking error convergence.
    • Modified iterative-learning-control-based ramp metering strategies for freeway traffic control with iteration-dependent fctors

      Hou, Zhongsheng; Yan, Jingwen; Xu, Jian-Xin; Li, Zhenjiang; Beijing Jiaotong University, Beijing, China (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2012)
      For a freeway traffic system with strict repeatable pattern, iterative learning control (ILC) has been successfully applied to local ramp metering for a macroscopic freeway environment by formulating the original ramp metering problem as an output tracking, disturbance rejection, and error compensation problem. In this paper, we address the freeway traffic ramp-metering system under a nonstrict repeatable pattern. ILC-based ramp metering and ILC add-on to ALINEA strategies are modified to deal with the presence of iteration-dependent parameters, iteration-dependent desired trajectory, and input constraints. Theoretical analysis and extensive simulations are used to verify the effectiveness of the proposed approaches.
    • A novel data-driven control approach for a class of discrete-time nonlinear systems

      Hou, Zhongsheng; Jin, Shangtai; Beijing Jiaotong University, Beijing, China (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2011)
      In this work, a novel data-driven control approach, model-free adaptive control, is presented based on a new dynamic linearization technique for a class of discrete-time single-input and single-output nonlinear systems. The main feature of the approach is that the controller design depends merely on the input and the output measurement data of the controlled plant. The theoretical analysis shows that the approach guarantees the bounded input and bounded output stability and tracking error monotonic convergence. The comparison experiments verify the effectiveness of the proposed approach.