scholarly journals Decentralized Optimization for a Novel Control Structure of HVAC System

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Shiqiang Wang ◽  
Jianchun Xing ◽  
Ziyan Jiang ◽  
Juelong Li
Keyword(s):  
Control System ◽  
Decentralized Control ◽  
Control Structure ◽  
Optimization Method ◽  
Labor Cost ◽  
Smart Device ◽  
Hvac System ◽  
Decentralized Optimization ◽  
System A ◽  
Novel Method

A decentralized control structure is introduced into the heating, ventilation, and air conditioning (HVAC) system to solve the high maintenance and labor cost problem in actual engineering. Based on this new control system, a decentralized optimization method is presented for sensor fault repair and optimal group control of HVAC equipment. Convergence property of the novel method is theoretically analyzed considering both convex and nonconvex systems with constraints. In this decentralized control system, traditional device is fitted with a control chip such that it becomes a smart device. The smart device can communicate and operate collaboratively with the other devices to accomplish some designated tasks. The effectiveness of the presented method is verified by simulations and hardware tests.

Fractional PIλDμ Control for Steer-by-Wire System

2011 ◽  
Vol 279 ◽  
pp. 423-428 ◽  
Author(s):  
Jie Tian ◽  
Jin Wu ◽  
Ning Chen
Keyword(s):  
Control System ◽  
Control Method ◽  
Optimization Method ◽  
Front Wheel ◽  
Design Parameters ◽  
Computational Simulations ◽  
System A ◽  
Steer By Wire ◽  
Simulation Results ◽  
Wire System

According to the design demands of the steer-by-wire system, a PIlDm controller based on fractional calculus was proposed. Aligning controller and steering controller were respectively designed to achieve the aligning and steering function of the front wheel steering module, which can ensure the robust of the steer-by-wire system during the special ranges of frequency. The five design parameters of fractional PIlDm controller were achieved by optimization method. Oustaloup method was used to approximate the fractional PIlDm controller and simulation model was achieved, which can be used in Matlab/Simulink. Computational simulations of the control system were carried out and simulation results showed the effectiveness of the control method to improve the robust of the steering-by-wire system.

scholarly journals A Novel Method of Optimization for Stochastic Control System

2020 ◽  
Vol 14 ◽  
Keyword(s):  
Control System ◽  
Stochastic Control ◽  
Dynamic Systems ◽  
External Environment ◽  
Optimization Method ◽  
Control Model ◽  
Stochastic Control System ◽  
Novel Method ◽  
The Stability ◽  
Stochastic Phenomena

Stochastic phenomena widely exist in the nature and real dynamic systems. The existence of random phenomena will make the system performance degrade greatly, and even cause instability. For the sake of improving the stability of stochastic control system, this paper proposed a novel method of optimization for stochastic control system by control model and max-plus algebraic algorithm. The simulation results indicate that the optimization method can effectively optimize the stochastic system. The input of the stochastic control system is stable to a certain extent, which weakens the random interference of the input signal in the external environment, thus improving the stability of the stochastic control system.

Sistem Kontrol Optimal Fuzzy-Particle Swarm Optimization

2018 ◽  
Vol 9 (1) ◽  
pp. 1-5
Author(s):  
Fachrudin Hunaini ◽  
Imam Robandi ◽  
Nyoman Sutantra
Keyword(s):  
Fuzzy Logic ◽  
Particle Swarm Optimization ◽  
Control System ◽  
Membership Function ◽  
Fuzzy Logic Control ◽  
Particle Swarm ◽  
Optimization Method ◽  
Swarm Optimization ◽  
Motion Error ◽  
Logic Control

Fuzzy Logic Control (FLC) is a reliable control system for controlling nonlinear systems, but to obtain optimal fuzzy logic control results, optimal Membership Function parameters are needed. Therefore in this paper Particle Swarm Optimization (PSO) is used as a fast and accurate optimization method to determine Membership Function parameters. The optimal control system simulation is carried out on the automatic steering system of the vehicle model and the results obtained are the vehicle's lateral motion error can be minimized so that the movement of the vehicle can always be maintained on the expected trajectory

Evidence on Food Control System in Charitable Food Assistance System: A Systematic Scoping Review

2018 ◽  
Author(s):  
Sizwe Makhunga ◽  
Tivani P. Mashamba-Thompson ◽  
Mbuzeleni Hlongwa ◽  
Khumbulani W. Hlongwana
Keyword(s):  
Control System ◽  
Scoping Review ◽  
Food Assistance ◽  
Assistance System ◽  
Food Control ◽  
System A

Multi-layer controller with state-constraint: Vehicle lateral stability control based on fuzzy logic

2021 ◽  
pp. 095440702110142
Author(s):  
Neng Wan ◽  
Guangping Zeng ◽  
Chunguang Zhang ◽  
Dingqi Pan ◽  
Songtao Cai
Keyword(s):  
Control System ◽  
Integrated Control ◽  
State Constraint ◽  
Stability Control ◽  
Lateral Stability ◽  
System A ◽  
Velocity Reduction ◽  
Vehicle Velocity ◽  
Allowable Range ◽  
Simulation Results

This paper deals with a new state-constrained control (SCC) system of vehicle, which includes a multi-layer controller, in order to ensure the vehicle’s lateral stability and steering performance under complex environment. In this system, a new constraint control strategy with input and state constraints is applied to calculate the steady-state yaw moment. It ensures the vehicle lateral stability by tracking the desired yaw rate value and limiting the allowable range of the side slip. Through the linkage of the three-layer controller, the tire load is optimized and achieve minimal vehicle velocity reduction. The seven-degree-of-freedom (7-DOF) simulation model was established and simulated in MATLAB to evaluate the effect of the proposed controller. Through the analysis of the simulation results, compared with the traditional ESC and integrated control, it not only solves the problem of obvious velocity reduction, but also solves the problem of high cost and high hardware requirements in integrated control. The simulation results show that designed control system has better performance of path tracking and driving state, which is closer to the desired value. Through hardware-in-the-loop (HIL) practical experiments in two typical driving conditions, the effectiveness of the above proposed control system is further verified, which can improve the lateral stability and maneuverability of the vehicle.

A multi-objective operation strategy optimization for ice storage systems based on decentralized control structure

2020 ◽  
Vol 42 (1) ◽  
pp. 62-81
Author(s):  
Yanhuan Ren ◽  
Junqi Yu ◽  
Anjun Zhao ◽  
Wenqiang Jing ◽  
Tong Ran ◽  
...  
Keyword(s):  
Energy Saving ◽  
Decentralized Control ◽  
Optimization Algorithm ◽  
Control Strategy ◽  
Load Distribution ◽  
Air Conditioning ◽  
Control Structure ◽  
Ice Storage ◽  
Swarm Optimization ◽  
Multi Objective

Improving the operational efficiency of chillers and science-based planning the cooling load distribution between the chillers and ice tank are core issues to achieve low-cost and energy-saving operations of ice storage air-conditioning systems. In view of the problems existing in centralized control architecture applied in heating, ventilation, and air conditioning, a distributed multi-objective particle swarm optimization improved by differential evolution algorithm based on a decentralized control structure was proposed. The energy consumption, operating cost, and energy loss were taken as the objectives to solve the chiller’s hourly partial load ratio and the cooling ratio of ice tank. A large-scale shopping mall in Xi’an was used as a case study. The results show that the proposed algorithm was efficient and provided significantly higher energy-savings than the traditional control strategy and particle swarm optimization algorithm, which has the advantages of good convergence, high stability, strong robustness, and high accuracy. Practical application: The end equipment of the electromechanical system is the basic component through the building operation. Based on this characteristic, taken electromechanical equipment as the computing unit, this paper proposes a distributed multi-objective optimization control strategy. In order to fully explore the economic and energy-saving effect of ice storage system, the optimization algorithm solves the chillers operation status and the load distribution. The improved optimization algorithm ensures the diversity of particles, gains fast optimization speed and higher accuracy, and also provides a better economic and energy-saving operation strategy for ice storage air-conditioning projects.

scholarly journals Method for Dynamic Service Orchestration in Fog Computing

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1796
Author(s):  
Nerijus Morkevicius ◽  
Algimantas Venčkauskas ◽  
Nerijus Šatkauskas ◽  
Jevgenijus Toldinas
Keyword(s):  
Fog Computing ◽  
Optimization Method ◽  
Service Orchestration ◽  
Multi Objective ◽  
System A ◽  
Service Distribution ◽  
Judgment Matrix ◽  
Hierarchy Process ◽  
Application Specific ◽  
Constrained Devices

Fog computing is meant to deal with the problems which cloud computing cannot solve alone. As the fog is closer to a user, it can improve some very important QoS characteristics, such as a latency and availability. One of the challenges in the fog architecture is heterogeneous constrained devices and the dynamic nature of the end devices, which requires a dynamic service orchestration to provide an efficient service placement inside the fog nodes. An optimization method is needed to ensure the required level of QoS while requiring minimal resources from fog and end devices, thus ensuring the longest lifecycle of the whole IoT system. A two-stage multi-objective optimization method to find the best placement of services among available fog nodes is presented in this paper. A Pareto set of non-dominated possible service distributions is found using the integer multi-objective particle swarm optimization method. Then, the analytical hierarchy process is used to choose the best service distribution according to the application-specific judgment matrix. An illustrative scenario with experimental results is presented to demonstrate characteristics of the proposed method.

Control System for the Mountainous Orchard Electric-Drive Monorail Transporter

2015 ◽  
Vol 738-739 ◽  
pp. 935-940 ◽  
Author(s):  
Zhen Li ◽  
Pei Xu ◽  
Yu Ping Ouyang ◽  
Shi Lei Lv ◽  
Qiu Fang Dai
Keyword(s):  
Control System ◽  
Electric Drive ◽  
Gear Ratio ◽  
System A ◽  
Speed Measurement ◽  
Driving Speed ◽  
Current Consumption ◽  
Operation Risk ◽  
Load Weight ◽  
Steep Hill

In order to reduce operation risk and working intensity in mountainous orchard transportation and to realize optimized control for the mountainous orchard electric-drive monorail transportation system, a mountainous orchard electric-drive monorail transporter control system was designed and developed in this study. The system mainly consists of modules as: manual and remote control, positioning, obstacle avoidance, speed measurement, motor control, electric-magnetic break, and the position limit. The driving speed, current consumption, break control, and battery pack running ability experiments were conducted to test the control system. Results indicated that, the transporter’s driving speed is 0.60~0.58 m/s when it is running on the ground with the load weight from 0 to 100kg. This speed is little affected by the load weight. The transporter’s driving speed is 0.45~0.28 m/s when it is climbing a steep hill with an angle of 39°. That speed is critically affected by the load weight. In further improvements, a shift mechanism will be introduced so that adjustable gear ratio could be achieved thus solve the current overload problem in a full load situation.

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