scholarly journals A New Model-Free Predictive Control Method Using Input and Output Data

2014 ◽  
Vol 1042 ◽  
pp. 182-187 ◽  
Author(s):  
Shigeru Yamamoto
Keyword(s):  
Mathematical Model ◽  
Predictive Control ◽  
Control Method ◽  
Just In Time ◽  
Control Input ◽  
Input Output ◽  
Output Data ◽  
Online Data ◽  
Model Free ◽  
The Mathematical Model

The purpose of this paper is to present a new predictive control utilizing online data and stored data of input/output of the controlled system. The conventional predictive control methods utilize the mathematical model of the control system to predict an optimal future input to control the system. The model is usually obtained by a standard system identification method from the measured input/output data. The proposed method does not require the mathematical model to predict the optimal future control input to achieve the desired output. This control strategy, called just-in-time, was originally proposed by Inoue and Yamamoto in 2004. In this paper, we proposed a simplified version of the original just-in-time predictive control method.

Chaotic motion control of a vibro-impact system based on data-driven control method

2021 ◽  
pp. 107754632110433
Author(s):  
Xiao-juan Wei ◽  
Ning-zhou Li ◽  
Wang-cai Ding
Keyword(s):  
Motion Control ◽  
Data Model ◽  
Chaotic Motion ◽  
Control Method ◽  
Data Driven ◽  
Damping Coefficient ◽  
Input Output ◽  
Output Data ◽  
Controlled System ◽  
Impact System

For the chaotic motion control of a vibro-impact system with clearance, the parameter feedback chaos control strategy based on the data-driven control method is presented in this article. The pseudo-partial-derivative is estimated on-line by using the input/output data of the controlled system so that the compact form dynamic linearization (CFDL) data model of the controlled system can be established. And then, the chaos controller is designed based on the CFDL data model of the controlled system. And the distance between two adjacent points on the Poincaré section is used as the judgment basis to guide the controller to output a small perturbation to adjust the damping coefficient of the controlled system, so the chaotic motion can be controlled to a periodic motion by dynamically and slightly adjusting the damping coefficient of the controlled system. In this method, the design of the controller is independent of the order of the controlled system and the structure of the mathematical model. Only the input/output data of the controlled system can be used to complete the design of the controller. In the simulation experiment, the effectiveness and feasibility of the proposed control method in this article are verified by simulation results.

scholarly journals Active Fault-Tolerant Control Based on Multiple Input Multiple Output-Model Free Adaptive Control for Four Wheel Independently Driven Electric Vehicle Drive System

2019 ◽  
Vol 9 (2) ◽  
pp. 276 ◽  
Author(s):  
Yugong Luo ◽  
Yun Hu ◽  
Fachao Jiang ◽  
Rui Chen ◽  
Yongsheng Wang
Keyword(s):  
Control System ◽  
Active Fault ◽  
Control Method ◽  
Fault Tolerant ◽  
Fault Tolerant Control ◽  
Drive System ◽  
Input Output ◽  
Vehicle Model ◽  
Model Free ◽  
Active Fault Tolerant Control

To solve the problems with the existing active fault-tolerant control system, which does not consider the cooperative control of the drive system and steering system or accurately relies on the vehicle model when one or more motors fail, a multi-input and multi-output model-free adaptive active fault-tolerant control method for four-wheel independently driven electric vehicles is proposed. The method, which only uses the input/output data of the vehicle in the control system design, is based on a new dynamic linearization technique with a pseudo-partial derivative, aimed at solving the complex and nonlinear issues of the vehicle model. The desired control objectives can be achieved by the coordinated adaptive fault-tolerant control of the drive and steering systems under different failure conditions of the drive system. The error convergence and input-output boundedness of the control system are proven by means of stability analysis. Finally, simulations and further experiments are carried out to validate the effectiveness and real-time response of the fault-tolerant system in different driving scenarios. The results demonstrate that our proposed approach can maintain the longitudinal speed error (within 3%) and lateral stability, thereby improving the safety of the vehicles.

scholarly journals Convergence Guaranteed Nonlinear Constraint Model Predictive Control via I/O Linearization

2013 ◽  
Vol 2013 ◽  
pp. 1-9
Author(s):  
Xiaobing Kong ◽  
Xiangjie Liu ◽  
Xiuming Yao
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Output Feedback ◽  
Feedback Linearization ◽  
Optimal Solution ◽  
Quadratic Program ◽  
Control Input ◽  
Input Output ◽  
Nonlinear Constraint ◽  
Constraint Model

Constituting reliable optimal solution is a key issue for the nonlinear constrained model predictive control. Input-output feedback linearization is a popular method in nonlinear control. By using an input-output feedback linearizing controller, the original linear input constraints will change to nonlinear constraints and sometimes the constraints are state dependent. This paper presents an iterative quadratic program (IQP) routine on the continuous-time system. To guarantee its convergence, another iterative approach is incorporated. The proposed algorithm can reach a feasible solution over the entire prediction horizon. Simulation results on both a numerical example and the continuous stirred tank reactors (CSTR) demonstrate the effectiveness of the proposed method.

Mathematical modelling and model predictive controller design of a quad tiltrotor UAV

2020 ◽  
pp. 095440622097133
Author(s):  
Jingxian Liao ◽  
Xiaodong Song
Keyword(s):  
Mathematical Model ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Trajectory Tracking ◽  
Controller Design ◽  
Control Input ◽  
Random Disturbance ◽  
Effect Analysis ◽  
Input Variables ◽  
Induced Velocity

A novel convertible unmanned aerial vehicle (UAV) with four tiltable rotors and a tandem-wing system has been developed. Considering the aerodynamic effect caused by the rotor-induced velocity, a mathematical model that contains the traditional free airstream analysis and rotor-induced effect analysis is proposed, from which the precise equilibrium point of the control inputs and states can be derived. Moreover, a control allocation algorithm is designed to provide the mapping relationship between traditional input variables and specific input variables of the UAV, so that the complicated mathematical model can be linearized for the design of model predictive control (MPC) system. In order to handle the control input constraints of the UAV system, an MPC system is applied for the trajectory tracking during the cruising phase. The simulation results demonstrate that the proposed model predictive control system has stability, accuracy without a random disturbance and quick response capabilities with a random disturbance during cruising trajectory tracking, which are in high demand for the quick UAV flight system.

A linear input/output data-based predictive control with integral action property

2001 ◽  
Vol 34 (25) ◽  
pp. 631-636
Author(s):  
In-Hyoup Song ◽  
Kee-Yoon Yoo ◽  
Hyun-Ku Rhee
Keyword(s):  
Predictive Control ◽  
Input Output ◽  
Output Data ◽  
Integral Action

scholarly journals Self-Triggered Model Predictive Control for Linear Systems Based on Transmission of Control Input Sequences

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Koichi Kobayashi
Keyword(s):  
Control System ◽  
Model Predictive Control ◽  
Linear Systems ◽  
Communication Networks ◽  
Predictive Control ◽  
Control Method ◽  
Input Sequence ◽  
Networked Control System ◽  
Control Input ◽  
Sampled Data

A networked control system (NCS) is a control system where components such as plants and controllers are connected through communication networks. Self-triggered control is well known as one of the control methods in NCSs and is a control method that for sampled-data control systems both the control input and the aperiodic sampling interval (i.e., the transmission interval) are computed simultaneously. In this paper, a self-triggered model predictive control (MPC) method for discrete-time linear systems with disturbances is proposed. In the conventional MPC method, the first one of the control input sequence obtained by solving the finite-time optimal control problem is sent and applied to the plant. In the proposed method, the first some elements of the control input sequence obtained are sent to the plant, and each element is sequentially applied to the plant. The number of elements is decided according to the effect of disturbances. In other words, transmission intervals can be controlled. Finally, the effectiveness of the proposed method is shown by numerical simulations.

Analysis of Polar Positioning System in Laser Device for Glass Engraving

2009 ◽  
Vol 147-149 ◽  
pp. 107-112 ◽  
Author(s):  
Roman Trochimczuk ◽  
Marek Gawrysiak
Keyword(s):  
Mathematical Model ◽  
Rotation Angle ◽  
Positioning System ◽  
Laser Device ◽  
Output Data ◽  
Cartesian Coordinates ◽  
Object Structure ◽  
Mechanical Parts ◽  
The Mathematical Model ◽  
Discretization Process

In the work the new concept of polar positioning system, alternative for Cartesian one, is presented. The mathematical model which allows calculation of the rotation angle of polar positioning system is considered. The Cartesian coordinates of formed points of object structure, received after discretization process of object are the inputs data to calculation. Output data however are rotation angles i.e. both working arm and rotation table angles. The influence of the stiffness of mechanical parts on the precision of instrument positioning and productivity of the presented polar device is defined.

Analysis and Design of a Linear Input/Output Data-Based Predictive Control

2001 ◽  
Vol 40 (20) ◽  
pp. 4292-4301 ◽  
Author(s):  
In-Hyoup Song ◽  
Kee-Youn Yoo ◽  
Hyun-Ku Rhee
Keyword(s):  
Predictive Control ◽  
Input Output ◽  
Output Data ◽  
Analysis And Design
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