Multirate Constrained Predictive Control: Algorithm and Experimental Results

2007 ◽  
Vol 2 (3) ◽  
Author(s):  
Qiuping Hu ◽  
Sohrab Rohani
Keyword(s):  
Control System ◽  
Predictive Control ◽  
Control Algorithm ◽  
Design Method ◽  
Pi Control ◽  
State Variables ◽  
Challenging Problem ◽  
State Estimator ◽  
Performance Specifications ◽  
Tank System

Control of multirate systems is a challenging problem due to several reasons such as increased complexity in the design with tighter performance specifications. In this work, an algorithm for multirate constrained predictive control (MCPC) is presented. The multirate predictive control system includes a multirate state estimator, which provides inter-sample estimates of state variables of the process from infrequent and slow measurements. Constraints are addressed rigorously in this framework. The proposed design method is verified via simulation as well as experimentation. The results of the multirate predictive control for temperature control of a stirred tank system are shown and compared with those of a proportional integral (PI) control system.

Design Method of Model Predictive Control for Development of Current Control System of PMSM

2020 ◽  
Vol 140 (11) ◽  
pp. 793-806
Author(s):  
Masahiro Shimaoka ◽  
Shinji Doki
Keyword(s):  
Control System ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Design Method ◽  
Current Control

scholarly journals Predictive Control Algorithm Based on Integral Action-Design and Implementation on a Conical Tank System

2018 ◽  
Vol 153 ◽  
pp. 06010 ◽  
Author(s):  
Vinayambika S Bhat ◽  
I. Thirunavukkarasu ◽  
S. Shanmuga Priya ◽  
C Shreesha
Keyword(s):  
Predictive Control ◽  
Control Algorithm ◽  
Level Control ◽  
Cross Sectional ◽  
Single Input Single Output ◽  
Predictive Algorithm ◽  
Single Output ◽  
Integral Action ◽  
Initial Stage ◽  
Tank System

This article presents a Model Predictive Control (MPC) algorithm based on integral action. Level control in process industry is challenging because of nonlinearity presents in the shape of the tank, actuators etc. The conical tank system is taken as benchmark process in the present study. It is Single Input Single Output (SISO) nonlinear system whose cross-sectional area varies along the tank height. The control algorithm is simulated using MATLAB m-file environment. The effectiveness of the predictive algorithm is also presented by experimentally validating it on a conical tank system at different heights. The interfacing of m-file with the experimental setup is the challenging task faced during the initial stage of experimental validation.

NEURAL ADAPTIVE CONTROL OF NONLINEAR MULTIVARIABLE SYSTEMS WITH APPLICATION TO A CLASS OF INVERTED PENDULUMS

2002 ◽  
Vol 12 (05) ◽  
pp. 411-424
Author(s):  
SHOULING HE
Keyword(s):  
Neural Networks ◽  
Control System ◽  
Control Algorithm ◽  
Learning Algorithm ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Base Point ◽  
Upper Body ◽  
Model Parameters ◽  
State Variables

In this paper multilayer neural networks (MNNs) are used to control the balancing of a class of inverted pendulums. Unlike normal inverted pendulums, the pendulum discussed here has two degrees of rotational freedom and the base-point moves randomly in three-dimensional space. The goal is to apply control torques to keep the pendulum in a prescribed position in spite of the random movement at the base-point. Since the inclusion of the base-point motion leads to a non-autonomous dynamic system with time-varying parametric excitation, the design of the control system is a challenging task. A feedback control algorithm is proposed that utilizes a set of neural networks to compensate for the effect of the system's nonlinearities. The weight parameters of neural networks updated on-line, according to a learning algorithm that guarantees the Lyapunov stability of the control system. Furthermore, since the base-point movement is considered unmeasurable, a neural inverse model is employed to estimate it from only measured state variables. The estimate is then utilized within the main control algorithm to produce compensating control signals. The examination of the proposed control system, through simulations, demonstrates the promise of the methodology and exhibits positive aspects, which cannot be achieved by the previously developed techniques on the same problem. These aspects include fast, yet well-maintained damped responses with reasonable control torques and no requirement for knowledge of the model or the model parameters. The work presented here can benefit practical problems such as the study of stable locomotion of human upper body and bipedal robots.

scholarly journals Automatic Control of the Middle Route Project for South-to-North Water Transfer Based on Linear Model Predictive Control Algorithm

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1873 ◽  
Author(s):  
Kong ◽  
Quan ◽  
Yang ◽  
Song ◽  
Zhu
Keyword(s):  
Control System ◽  
Model Predictive Control ◽  
Automatic Control ◽  
Predictive Control ◽  
Control Algorithm ◽  
Water Transfer ◽  
Water Delivery ◽  
Real Time Control ◽  
Time Control ◽  
North Water

The application of automatic control to irrigation canals is an important means of improving the efficiency of water delivery. The Middle Route Project (MRP) for South-to-North Water Transfer, the largest water transfer project in China, is currently under manual control. Given the complexity of the MRP, there is an urgent need to adopt some form of automatic control. This paper describes the application of model predictive control (MPC), a popular real time control algorithm particularly suited to the automatic control of multi-pool irrigation water delivery systems, to the MRP using a linear control model. This control system is tested in part of the MRP by means of numerical simulations. The results show that the control system can deal with both known and unknown disturbances, albeit with a degree of resonance in some short pools. However, it takes a long time for the MRP to reach a stable state under the MPC system and the calculation time for the whole MRP network would be too long to satisfy the requirements of real-time control. Suggestions are presented for the construction of an automatic control system for the MRP.

A Control Method for Active Power Filters with Three-Level NPC Inverter

2011 ◽  
Vol 268-270 ◽  
pp. 428-433
Author(s):  
Chen Guo ◽  
Cun Bing Gui ◽  
Zhong Ren Chen
Keyword(s):  
Control Algorithm ◽  
Control Method ◽  
Sampling Period ◽  
Active Power ◽  
Pi Control ◽  
State Variables ◽  
Active Power Filters ◽  
Power Filters ◽  
Repetitive Nature ◽  
Periodic Error

This paper researches control problem for active power filters with three-level NPC inverter and proposes a novel PI control algorithm for tracking harmonic command current. This novel PI control algorithm can suppress the periodic error in the whole system to achieve zero steady error tracking. In this scheme, the state variables are estimated with a state observer to cancel the delay of one sampling period in this digital control system. Harmonic current is predicted with a repetitive algorithm simultaneity, which makes use of the repetitive nature of load current. The controller is analyzed and designed in the paper, and the experiment results illustrate that this APF can be controlled in a satisfactory way.

Reduction of Quantization Error in Multirate Output Feedback Control

2016 ◽  
Vol 28 (5) ◽  
pp. 640-645
Author(s):  
Takao Sato ◽  
◽  
Hironobu Sakaguchi ◽  
Nozomu Araki ◽  
Yasuo Konishi
Keyword(s):  
Control System ◽  
Feedback Control ◽  
Output Feedback ◽  
Design Method ◽  
Output Feedback Control ◽  
Quantization Error ◽  
Design Parameters ◽  
Control Input ◽  
State Variables ◽  
Feedback Control System

[abstFig src='/00280005/04.jpg' width='250' text='Multirate output feedback control' ] In the new design method we propose for a multirate output feedback control system, the hold interval of control input is longer than the sampling interval of plant output. In this system, unknown state variables are calculated using control input and plant output without observers. The multirate output feedback control system has been extended by introducing new design parameters that are designed independent of the calculation of the state variable. To our knowledge, however, no systematic design scheme has ever been proposed for design parameters in this case. In this study, quantization error is dealt with statistically and design parameters are decided to minimize quantization error.

Research of Speed Regulating System Based on New Fuzzy PI Control

2014 ◽  
Vol 518 ◽  
pp. 310-315 ◽  
Author(s):  
Hui Wang ◽  
Li Rui Wan ◽  
Cai Dong Wang
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Control Algorithm ◽  
Dynamic Performance ◽  
Mathematic Model ◽  
Pi Controller ◽  
Pi Control ◽  
Dynamic Performances ◽  
Saturation Method ◽  
Fuzzy Control Algorithm

In order to further improve on the static and dynamic performance of the permanent magnet linear synchronous motor (PMLSM) speed regulating system, the traditional PI control is combined with the fuzzy control to achieve PI parameters self-regulating. In this paper, on the basis of studying the mathematic model of PMLSM, the resisting integral saturation method are adopted to eliminate the integral saturation which the traditional PI causes. the fuzzy control is introduced into the PI control to realize to the self-optimization of the PI parameters. The simulation results show the resisting integral saturation PI control system based on the fuzzy control algorithm has better static and dynamic performances and stability, and possesses stronger anti-strike performance. Therefore, the new control system resolves the problems which the traditional PI controller cant achieve the most optimization because of the difficulty of the parameter regulating.

Performance-Adaptive Generalized Predictive Control-Based Proportional-Integral-Derivative Control System and Its Application

2014 ◽  
Vol 136 (6) ◽  
Author(s):  
Takao Sato ◽  
Toru Yamamoto ◽  
Nozomu Araki ◽  
Yasuo Konishi
Keyword(s):  
Control System ◽  
Predictive Control ◽  
Pid Control ◽  
Design Method ◽  
Design Parameters ◽  
Generalized Predictive Control ◽  
Control Performance ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Proportional Integral Derivative Control

In the present paper, we discuss a new design method for a proportional-integral-derivative (PID) control system using a model predictive approach. The PID compensator is designed based on generalized predictive control (GPC). The PID parameters are adaptively updated such that the control performance is improved because the design parameters of GPC are selected automatically in order to attain a user-specified control performance. In the proposed scheme, the estimated plant parameters are updated only when the prediction error increases. Therefore, the control system is not updated frequently. The control system is updated only when the control performance is sufficiently improved. The effectiveness of the proposed method is demonstrated numerically. Finally, the proposed method is applied to a weigh feeder, and experimental results are presented.

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