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船舶運動及 控制

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船舶運動及 控制. 指導教授 : 曾 慶 耀 學 號 :10267036 學 生 : 潘 維 剛. Path following of a model ship using model predictive control with experimental verification. Outline. Abstract Introduction Ship dynamic model Path following of the ship using MPC INPA-SQP ALGORITHM

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slide1

船舶運動及控制

指導教授:曾 慶 耀學 號:10267036學 生:潘 維 剛

outline
Outline
  • Abstract
  • Introduction
  • Ship dynamic model
  • Path following of the ship using MPC
  • INPA-SQP ALGORITHM
  • Experimental platform and experimental results
  • Conclusion
abstract
Abstract
  • This paper presents an experimental implementation of a Model Predictive Control (MPC) strategy for path following on a model ship.
  • The implementation is performed experimentally via Integrated Perturbation Analysis and Sequential Quadratic Programming (InPA-SQP) algorithm.
introduction
Introduction
  • MPC is an attractive candidate to achieve zero cross tracking error and heading angle error via minimizing a suitable cost function while taking into account physical constraints.
  • Quadratic Programming (InPA-SQP), the algorithm was developed to address the computational complexity of MPC.
slide7

The following model characterizes the

dynamics of the model ship.

slide9

Assumption can be satisfied by properly controlling the propeller speed to maintain constant vessel surge speed.

  • The nominal value u = 0.4 m/s. The state of the system is and δ is the rudder angle which acts as the only input to the system.
slide11

Consider the initial state of the system as

. To compare the linear and nonlinear model,we solve the optimization problem P(x0) with N = 200 and sampling time 0.1, for both linear and nonlinear systems.

  • Figure 2 shows the resulting open loop optimal control command for linear and nonlinear systems.
conclusion
Conclusion
  • In this paper, a Model Predictive Controller is designed for path following of a model ship subject to input constraints.To implement MPC with a nonlinear model, the InPA-SQP method is introduced to solve the constrained optimal control problem. The InPA-SQP solver can meet the computational efficiency demand even for the nonlinear model considered in this paper. The effectiveness of the proposed MPC has been verified with experimental results.