Nonlinear model predictive control using automatic differentiation
作者： Yi Cao , R. Al-Seyab
DOI: 10.23919/ECC.2003.7085261
关键词:
摘要: Although nonlinear model predictive control (NMPC) might be the best choice for a plant, it is still not widely used. This mainly due to computational burden associated with solving set of differential equations and dynamic optimization problem. In this work, new NMPC algorithm based on least square proposed. algorithm, residual Jacobian matrix efficiently calculated from sensitivity functions without extra integrations. Recently developed automatic differentiation techniques are applied get accurately efficiently. The has been an evaporation process satisfactory results cope large setpoint changes, measured unmeasured severe disturbances process-model mismatches.
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