학술논문

Novel Fractional-Order Model Predictive Control: State-Space Approach
Document Type
Periodical
Author
Source
IEEE Access Access, IEEE. 9:92769-92775 2021
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Regulators
Stability criteria
Programmable logic devices
Predictive models
Aerospace electronics
Cost function
Real-time systems
Model predictive control (MPC)
fractional calculus
fractional-order model
fractional derivative
fractional-order cost function
fractional integral
constrains
linear quadratic regulator (LQR)
Language
ISSN
2169-3536
Abstract
This paper deals with a novel approach to the fractional-order model predictive control in state space. Except well-known fractional-order models of processes (plants) with arbitrary (real) order of the derivatives in fractional differential equations a new fractional performance index (cost function) and fractional control action are considered. Such combined approach to the model predictive control provides more degrees of freedom and incorporates fractional-order dynamics into the control in the form of memory due to the property of the fractional-order operator. An illustrative example of this approach is presented.