Control Design for Nonlinear Stochastic Processes in the Presence of Input Constraint

Mozaffari Bezi, Ali | 2022

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 55673 (06)
  4. University: Sharif University of Technology
  5. Department: Chemical and Petroleum Engineering
  6. Advisor(s): Shahrokhi, Mohammad
  7. Abstract:
  8. Due to the presence of a random variable in the process dynamics or due to the presence of measurement noise, many processes have stochastic in nature. Behaviors of these processes are different from the deterministic processes and therefore their controllers are also different. The aim of this research is to design adaptive controller for stochastic processes with a non-strict feedback structure and in the presence of input constraints. Also, the considered system has other limitations such as the unmeasured states, actuator failure, unknown dynamics and fixed time stability is desired. The input limitation can be caused by the limitation of the final control element, because the input power is limited. The saturation limit is of this type. Another limitation is the presence of dead zone, backlash or hysteresis in the final control element. Another issue that must be considered in the controller design is the nonlinear dynamics of the process, because most systems have nonlinear behaviors. Ignoring to consider these limitations in the controller design can cause instability of the closed loop system. In this work, a non-linear stochastic system is considered in a non-strict feedback structure and then a controller is designed using the backstepping method in the presence of the mentioned constraints. Using stability theorems, the stability of the closed loop is proved. Finally, the performance of the controller is checked by simulation. The results indicate that the designed controller has a satisfactory performance
  9. Keywords:
  10. Stochastic Process ; Adaptive Control ; Input Constraint ; Linear Observer ; Unknown Dynamics ; Actuator Failure ; Fixed-Time Stability

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