Combination of Data-Driven Active Disturbance Rejection and Takagi-Sugeno Fuzzy Control with Experimental Validation on Tower Crane Systems

In this paper a second-order data-driven Active Disturbance Rejection Control (ADRC) is merged with a proportional-derivative Takagi-Sugeno Fuzzy (PDTSF) logic controller, resulting in two new control structures referred to as second-order data-driven Active Disturbance Rejection Control combined wi...

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Bibliographic Details
Published inEnergies (Basel) Vol. 12; no. 8; p. 1548
Main Authors Raul-Cristian Roman, Radu-Emil Precup, Petriu, Emil M, Florin Dragan
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 24.04.2019
Subjects
Active Disturbance Rejection Control
Advantages
Algorithms
Amphibious aircraft
Brushless motors
Computer engineering
Computer simulation
Control systems
Control theory
Controllers
D C motors
data-driven control
Design
Diabetes mellitus
Electric motors
Electric vehicles
Energy consumption
Evolutionary algorithms
Feedback
Feedback control
fuzzy control
Fuzzy logic
Fuzzy systems
Gain scheduling
Informatics
Insulin
Laboratories
Laboratory equipment
Motor task performance
Neural networks
Nonlinear control
Nonlinear feedback
Objective function
Optimization
Oscillations
Permanent magnets
second-order data-driven Active Disturbance Rejection Control merged with proportional-derivative Takagi-Sugeno Fuzzy Control
Servomotors
Ships
Simulation
Spacecraft
State observers
Synchronous motors
tower crane systems
Tower cranes
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Summary:In this paper a second-order data-driven Active Disturbance Rejection Control (ADRC) is merged with a proportional-derivative Takagi-Sugeno Fuzzy (PDTSF) logic controller, resulting in two new control structures referred to as second-order data-driven Active Disturbance Rejection Control combined with Proportional-Derivative Takagi-Sugeno Fuzzy Control (ADRC–PDTSFC). The data-driven ADRC–PDTSFC structure was compared with a data-driven ADRC structure and the control system structures were validated by real-time experiments on a nonlinear Multi Input-Multi Output tower crane system (TCS) laboratory equipment, where the cart position and the arm angular position of TCS were controlled using two Single Input-Single Output control system structures running in parallel. The parameters of the data-driven algorithms were tuned in a model-based way using a metaheuristic algorithm in order to improve the efficiency of energy consumption.
ISSN:1996-1073
1996-1073
DOI:10.3390/en12081548