Design of a computationally efficient observer-based nonlinear model predictive control for a continuous stirred tank reactor
Nonlinear model predictive control (NMPC) proves to be a suitable technique for controlling nonlinear systems, However, the need for the online non-convex nonlinear optimization in the NMPC algorithm increases its computational burden and leads to unreliable or even unstable control. In this paper, a computationally efficient observer-based NMPC approach has been proposed for multiple-input multiple-output (MIMO) systems. After estimating the states, a multivariable NMPC algorithm with nonlinear prediction and linearization (NPL) was used. The efficacy of the proposed NMPC scheme has been demonstrated by conducting simulation studies on a jacketed CSTR used in the production process of propylene glycol.
NMPC EKF linearization quadratic programming inferential control CSTR state estimation
Hossein Khodadadi Hooshang Jazayeri-Rad
Instrumentation and Automation department Petroleum University of technology Ahuaz Iran
国际会议
厦门
英文
484-489
2010-10-29（万方平台首次上网日期，不代表论文的发表时间）