Neuromorphic-computing-based feedback control: A cognitive supervisory control framework

2016 ◽  
Author(s):  
Qing Hui ◽  
Wei Qiao ◽  
Chen Peng
Keyword(s):  
Feedback Control ◽  
Supervisory Control ◽  
Neuromorphic Computing ◽  
Control Framework

Feedback control framework for car-like robots using the unicycle controllers

Robotica ◽  
2011 ◽  
Vol 30 (4) ◽  
pp. 517-535 ◽  
Author(s):  
Maciej Michałek ◽  
Krzysztof Kozłowski
Keyword(s):  
Stability Analysis ◽  
Feedback Control ◽  
Closed Loop ◽  
Path Following ◽  
Rear Wheel ◽  
Front Wheel ◽  
Steering Angle ◽  
Formal Stability ◽  
Control Framework ◽  
Error Dynamics

SUMMARYThe paper introduces a novel general feedback control framework, which allows applying the motion controllers originally dedicated for the unicycle model to the motion task realization for the car-like kinematics. The concept is formulated for two practically meaningful motorizations: with a front-wheel driven and with a rear-wheel driven. All the three possible steering angle domains for car-like robots—limited and unlimited ones—are treated. Description of the method is complemented by the formal stability analysis of the closed-loop error dynamics. The effectiveness of the method and its limitations have been illustrated by numerous simulations conducted for the three main control tasks, namely, for trajectory tracking, path following, and set-point regulation.

Human Supervisory Control Framework for Interactive Medical Image Segmentation

2012 ◽  
pp. 77-88
Author(s):  
Ivan Kolesov ◽  
Peter Karasev ◽  
Grant Muller ◽  
Karol Chudy ◽  
John Xerogeanes ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Supervisory Control ◽  
Medical Image ◽  
Medical Image Segmentation ◽  
Control Framework ◽  
Human Supervisory Control

scholarly journals Two Phase Separation using Liquid Level Control System using PLC and SCADA

2019 ◽  
Vol 9 (2) ◽  
pp. 2389-2391
Keyword(s):  
Supervisory Control ◽  
Programmable Logic ◽  
Level Control ◽  
Fluid Level ◽  
Two Phase ◽  
Two Fluids ◽  
Control Framework ◽  
Set Up ◽  
The Individual ◽  
Fluid Levels

Activity of the plant requires a great deal of work and human asset and requires a ton of diligent work and persistence as the individual needs to take note of every single an incentive at various occasions by taking readings physically. With the advancement of Industrial Automation, fluid level control framework has been generally utilized in different fields. In this paper, in light of PLC a control framework is set up by PID calculation and this control framework can alter two diverse fluid levels consequently. On the off chance that there are two distinct kinds of fluids with various densities in an equivalent tank and so as to isolate those two fluids, Level control framework dependent on SCADA and PLC is actualized. This framework satisfies splendidly the need of various fluid level control framework in industry, and it brings advantageous and exact for controlling. The proposed framework gives the fluid Level control, with the assistance of Programmable Logic Controllesr (PLCs), and Supervisory Control and Data Acquisition (SCADA).

A feedback control framework for safe and economically-optimal operation of nonlinear processes

AIChE Journal ◽  
2016 ◽  
Vol 62 (7) ◽  
pp. 2391-2409 ◽  
Author(s):  
Fahad Albalawi ◽  
Anas Alanqar ◽  
Helen Durand ◽  
Panagiotis D. Christofides
Keyword(s):  
Feedback Control ◽  
Optimal Operation ◽  
Nonlinear Processes ◽  
Control Framework

scholarly journals Assessment and Feedback Control of Paving Quality of Earth-Rock Dam Based on OODA Loop

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7756
Author(s):  
Cheng Wang ◽  
Jiajun Wang ◽  
Wenlong Chen ◽  
Jia Yu ◽  
Zheng Jiao ◽  
...  
Keyword(s):  
Feedback Control ◽  
Control Method ◽  
Key Factors ◽  
Finite Point ◽  
Learning Automaton ◽  
Control Framework ◽  
Decision Module ◽  
Standard Value ◽  
Site Control

Paving thickness and evenness are two key factors that affect the paving operation quality of earth-rock dams. However, in the recent study, both of the key factors characterising the paving quality were measured using finite point random sampling, which resulted in subjectivity in the detection and a lag in the feedback control. At the same time, the on-site control of the paving operation quality based on experience results in a poor and unreliable paving quality. To address the above issues, in this study, a novel assessment and feedback control framework for the paving operation quality based on the observe–orient–decide–act (OODA) loop is presented. First, in the observation module, a cellular automaton is used to convert the location of the bulldozer obtained by monitoring devices into the paving thickness of the levelling layer. Second, in the orient module, the learning automaton is used to update the state of the corresponding and surrounding cells. Third, in the decision module, an overall path planning method is developed to realise feedback control of the paving thickness and evenness. Finally, in the act module, the paving thickness and evenness of the entire work unit are calculated and compared to their control thresholds to determine whether to proceed with the next OODA loop. The experiments show that the proposed method can maintain the paving thickness less than the designed standard value and effectively prevent the occurrence of ultra-thick or ultra-thin phenomena. Furthermore, the paving evenness is improved by 21.5% as compared to that obtained with the conventional paving quality control method. The framework of the paving quality assessment and feedback control proposed in this paper has extensive popularisation and application value for the same paving construction scene.

Supervisory Control and Distributed Optimization of Building Energy Systems

2020 ◽  
Vol 142 (10) ◽  
Author(s):  
Zhanhong Jiang ◽  
Venkatesh Chinde ◽  
Adam Kohl ◽  
Atul G. Kelkar ◽  
Soumik Sarkar
Keyword(s):  
Air Temperature ◽  
Supervisory Control ◽  
Large Scale ◽  
Distributed Optimization ◽  
Pacific Northwest National Laboratory ◽  
Energy Systems ◽  
Building Energy ◽  
Practical Implementation ◽  
Control Framework ◽  
Building Energy Systems

Abstract Energy consumption in commercial buildings is significantly affected by the performance of heating, ventilation, and air-conditioning (HVAC) systems, which are traditionally operated using centralized controllers. HVAC control requires adjusting multiple setpoints such as chilled water temperatures and supply air temperature (SAT). Supervisory control framework in a distributed setting enables optimal HVAC operation and provides scalable solutions for optimizing energy across several scales from homes to regional areas. This paper proposes a distributed optimization framework for achieving energy efficiency in large-scale building energy systems. It is highly desirable to have building management systems that are scalable, robust, flexible, and are low cost. For addressing the scalability and flexibility, a modular problem formulation is established that decouples the distributed optimization level from local thermal zone modeling level. We leverage a recently developed generalized gossip algorithm for robust distributed optimization. The supervisory controller aims at minimizing the energy input considering occupant comfort. For validating the proposed scheme, a numerical case study based on a physical testbed in the Iowa Energy Center is presented. We show that the distributed optimization methodology outperforms the typical baseline strategy, which is a rule-based controller to set a constant supply air temperature. This paper also incorporates a software architecture based on the volttron platform, developed by the Pacific Northwest National Laboratory (PNNL), for practical implementation of the proposed framework via the BACnet system. The experimental results show that the supervisory control framework proposed in this paper can save energy by approximately 11%.

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