Wiener model based GMVC design considering sensor noise and delay

Abstract

Even though there is a plethora of literature available for assessing linear control loop performance, they cannot be applied to the nonlinear control loops. In this paper, a nonlinear generalized minimum variance (NGMV) controller based on a single input-single output (SISO) Wiener model is proposed. The NGMV controller's performance is used as a benchmark for a class of nonlinear control loops. The advantage of the proposed method is ability of online parameter estimation of the nonlinear model using common recursive least squares (RLS) method. In real-world applications, sensor and measurement tools force noises and extra delay to the control loop which poses limitations on achievable control performance. Hence, the classic control performance assessment techniques, is not attainable anymore. To handle the limitation caused by sensor delay, the k-step ahead prediction method is utilized. Further, the exponential digital filter is used in order to attenuate impact of the measurement noise on the controller. To show the effectiveness of the proposed method, a simulation test on a pH neutralization process is carried out.

Keywords: Nonlinear generalized minimum variance control (NGMV); Sensor and measurement delay; Wiener model; pH neutralization process.