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Development of Heuristic Algorithms for Real-Time Model Predictive Control of Nonlinear Parameter Varying Systems with Uncertainty

Nasrollahi Boroujeni, Saeed | 2019

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  1. Type of Document: Ph.D. Dissertation
  2. Language: Farsi
  3. Document No: 52474 (45)
  4. University: Sharif University of Technology
  5. Department: Aerospace Engineering
  6. Advisor(s): Nobahari, Hadi
  7. Abstract:
  8. In this study, novel algorithms are presented for nonlinear parameter varying systems with uncertainty in the model predictive control using heuristic algorithms. To this end, some algorithms are developed which provide the possibility of estimating simultaneously states and control signal of the stochastic nonlinear systems. Then, the model predictive control algorithm is presented for stochastic nonlinear systems with uncertainty to estimate uncertainty and compensate it using ant colony optimization. Next, the model predictive control algorithm is developed for nonlinear system with matched bounded uncertainty using particle swarm optimization. Performance of the developed controllers is tested for a continuous stirred tank reactor as a non-affine problem and for nonlinear cart and spring system as an affine problem. In addition, the developed algorithms are used to solve some nonlinear control and guidance problems. Attitude control of a quadrotor as a multi-input multi-output problem, autopilot of pursuer as a constraint problem, two-point guidance as an uncertain problem and differential game guidance as a parameter varying systems with uncertainty are the problems which are solved using the developed algorithms. In addition, two benchmark problems are tested to illustrate real-time implementation of two heuristic controllers
  9. Keywords:
  10. Nonlinear Predictive Control ; Heuristic Algorithm ; Navigation System Uncertainty ; Hardware in the Loop ; Nonlinear Estimation ; Parameter Varyin System

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