Disturbance rejection and set-point tracking of sinusoidal signals using Generalized Predictive Control

2008 ◽  
Author(s):  
Liuping Wang ◽  
J.A. Rossiter
Keyword(s):  
Predictive Control ◽  
Disturbance Rejection ◽  
Generalized Predictive Control ◽  
Set Point ◽  
Point Tracking ◽  
Sinusoidal Signals

scholarly journals Modified two-degree-of-freedom Smith predictive control for processes with time-delay

2020 ◽  
Vol 53 (3-4) ◽  
pp. 691-697 ◽  
Author(s):  
Ziwei Li ◽  
Jianjun Bai ◽  
Hongbo Zou
Keyword(s):  
Time Delay ◽  
Predictive Control ◽  
Control Strategy ◽  
Disturbance Rejection ◽  
Control Method ◽  
Internal Model Control ◽  
Degree Of Freedom ◽  
Set Point ◽  
Point Tracking ◽  
Two Degree Of Freedom

This article proposes an improved two-degree-of-freedom Smith predictive control method for typical industrial control systems. Smith predictive control is a classic control strategy designed for systems with pure lag. As an extension of Smith predictive control, internal model control can solve the time-delay problem effectively and make the controller design simple. Based on the two control algorithms, an enhanced control method with modified control structure is developed in this paper. In the design scheme, the set-point tracking and the disturbance rejection characteristics are decoupled, such that the set-point tracking and disturbance rejection controllers can be designed independently to achieve better control performance. The obtained control strategy possesses simple and convenient parameter tuning procedures. The validity of the proposed scheme is verified through theoretical analysis and simulation comparison with other control methods, and the results indicate that the proposed strategy shows better performance on set-point tracking and disturbance rejection.

scholarly journals Optimization of control performance on CO2 removal in subang field using model predictive control

2018 ◽  
Vol 67 ◽  
pp. 01028
Author(s):  
Abdul Wahid ◽  
Yoga Wiranoto
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Disturbance Rejection ◽  
Performance Indicator ◽  
Co2 Removal ◽  
Control Performance ◽  
Improve Performance ◽  
Makeup Water ◽  
Set Point ◽  
Point Tracking

A model predictive control (MPC) is used to optimize the control performance on CO2 removal in Subang Field. MPC is implemented to control the feed gas pressure (PIC-1101), amine flow rate (FIC-1102), and makeup water flowrate (FIC-1103) to maintain CO2 concentration in sweet gas. MPC is built using the first-order plus dead time (FOPDT) models. The control performance tests are used set point (SP) tracking and disturbance rejection with the performance indicator is the integral of square error (ISE). The result show that the optimum setting of prediction horizon (P), horizon (M) and Time Sampling (T) in MPC are 9 1, 32 and 1 on PIC-1101; 34, 10 and 5 on FIC-1102 and 40, 10 and 5 on FIC-1103. Based on ISE values, the use of MPC can improve performance for set point tracking by 14.02% in PIC-1101, 76.74% in FIC-1102, and 16.31% in FIC-1103, the use of MPC can improve performance for disturbance rejection by 19.32% in FIC-1102, and 91.57% in FIC-1103, compared with the proportional-integral (PI) controller that used in the field.

scholarly journals A Modified 2-DOF Control Framework and GA Based Intelligent Tuning of PID Controllers

Processes ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 423
Author(s):  
Gun-Baek So
Keyword(s):  
Disturbance Rejection ◽  
Pid Controller ◽  
Weighting Function ◽  
Pid Controllers ◽  
Set Point ◽  
Tuning Method ◽  
Point Tracking ◽  
Load Disturbance ◽  
Control Framework ◽  
Feedforward Controller

Although a controller is well-tuned for set-point tracking, it shows poor control results for load disturbance rejection and vice versa. In this paper, a modified two-degree-of-freedom (2-DOF) control framework to solve this problem is proposed, and an optimal tuning method for the pa-rameters of each proportional integral derivative (PID) controller is discussed. The unique feature of the proposed scheme is that a feedforward controller is embedded in the parallel control structure to improve set-point tracking performance. This feedforward controller and the standard PID con-troller are combined to create a new set-point weighted PID controller with a set-point weighting function. Therefore, in this study, two controllers are used: a set-point weighted PID controller for set-point tracking and a conventional PID controller for load disturbance rejection. The parameters included in the two controllers are tuned separately to improve set-point tracking and load dis-turbance rejection performances, respectively. Each controller is optimally tuned by genetic algo-rithm (GA) in terms of minimizing the IAE performance index, and what is special at this time is that it also tunes the set-point weighting parameter simultaneously. The simulation results performed on four virtual processes verify that the proposed method shows better performance in set-point tracking and load disturbance rejection than those of the other methods.

Improving the Tracking of Generalized Predictive Control Controllers

1996 ◽  
Vol 210 (3) ◽  
pp. 169-182 ◽  
Author(s):  
J A Rossiter ◽  
B G Grinnell
Keyword(s):  
Frequency Domain ◽  
Predictive Control ◽  
Time Domain ◽  
Degree Of Freedom ◽  
Generalized Predictive Control ◽  
Control Law ◽  
Set Point ◽  
The Poor ◽  
Fixed Order ◽  
Two Degree Of Freedom

One of the advantages of predictive control is its ability to take optimal account of information about future set point changes in the specification of the control law. However, the optimum GPC (generalized predictive control) prefilter that uses this information can lead to a deterioration rather than an improvement in the accuracy of tracking. Some simple modifications to GPC to overcome this problem are discussed. It will then be shown how some simple algorithms can be used to design an optimal prefilter that does not have any of the poor effects arising from the standard choice and hence always improves the performance. The basis of the technique is analogous to the two-degree-of-freedom designs common in the literature on H∞. However, here the emphasis is on fixed-order prefilters designed from a time domain, not a frequency domain, objective.

Extended state observer based fractional order controller design for integer high order systems

2021 ◽  
pp. 095440622110621
Author(s):  
Rachid Mansouri ◽  
Maamar Bettayeb ◽  
Ubaid M Al-Saggaf ◽  
Abdulrahman U Alsaggaf ◽  
Muhammad Moinuddin
Keyword(s):  
Fractional Order ◽  
Disturbance Rejection ◽  
State Observer ◽  
Internal Model Control ◽  
Extended State Observer ◽  
Extended State ◽  
Set Point ◽  
Point Tracking ◽  
Model Control ◽  
Fractional Order Controller

In this paper, based on the extended state observer (ESO) and on a fractional order controller (FOC), composed of an integer order PID cascaded with a fractional order filter (FOF), a new control scheme for an n th order integer plant is proposed. The ESO is used to estimate and cancel the unknown internal dynamics and the external disturbance. Afterwards, an FOC is designed to resolve the set-point tracking problem. An analytical and systematic method is proposed to design the FOC. This method is based on the Internal Model Control (IMC) and the Bode’s Ideal Transfer Function (BITF). Therefore, the proposed control structure improves the robustness and performance of the traditional linear active disturbance rejection control (LADRC), especially for the open-loop gain variation. In addition, since the system be controlled is an n th order, a general form of the BITF is also proposed. Numerical simulations on a nonlinear model and experimental results on a cart-pendulum system design illustrate the effectiveness of the suggested ESO-PID-FOF scheme for the disturbance rejection, the set-point tracking and robustness. A comparison with the results obtained using the standard LADRC is also presented.

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