Enhancing the quadratic problem solver in the pilot scale distillation control systems using different optimization methods

The analysis of possible energy saving in in the technological process of production of elements of scraper conveyors containing flexible automated production is given. It consists of complex subordinate aggregate installations consisting of conveyor lines, robot manipulators and tripods. The studied technological processes and control systems for electric drives of actuators are multi-connected, distributed in space, stochastic and multidimensional in the number of control and monitoring coordinates. It is proposed a methodology of reducing energy consumption of actuators by means of physical-virtual modeling and parameterization based on estimates of energy costs, by means of planning factor experiments, steep ascending in the anti-gradient direction of integral quadratic estimates of the control system, which are proportional to the costs of electricity in transient modes of actuators. The methodology, in comparison with the well-known optimization methods, is invariant to the type of products developed in flexible automated production, to the laws of distribution of the semi-finished products flows entering the production line, and is focused on predicting the boundaries of the saved energy and the life of the electromechanical equipment and improving reliability of electric drive control systems operation as a part of industrial complexes. The uniqueness of the method consists in applicability of the developed algorithm of evaluating energy savings and optimizing technological processes according to the criterion of energy consumption in real time in the condi- tions of the probabilistic situation of input parameters, regardless of the selected method of setting the optimal parameters of production line facilities.

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The problem of choosing the optimal performance in the multiprocessor computer system design

Journal of Physics Conference Series ◽

10.1088/1742-6596/2094/3/032058 ◽

2021 ◽

Vol 2094 (3) ◽

pp. 032058

Author(s):

S N Efimov ◽

V A Terskov ◽

I Yu Sakash ◽

V V Molokov ◽

D L Nikiforov

Keyword(s):

Control Systems ◽

Real Time ◽

Optimization Methods ◽

Computing System ◽

Control Problems ◽

Real Time Systems ◽

Computing Systems ◽

Multiprocessor Computer ◽

The Cost ◽

Time Systems

Abstract The article presents the formulation of the problem of optimizing the structure of multiprocessor computing systems designed to solve control problems in real time. The features of this problem, which influence the choice of optimization methods, have been studied. It is concluded that this problem can be effectively solved using evolutionary methods of optimization. The considered models for finding performance can be used to optimize the architecture of multiprocessor computing systems. Besides, it should be taken into account that the resources allocated for the development and operation of computing systems are always limited. Therefore, it is advisable to consider the problem of optimizing the structure of a computing system as multi-criterial one: one criterion is the performance, and the other one is the cost of development and operation of the system. Acquired results can be used in development of multiprocessor computing systems for real-time systems, which is going to reduce the cost of development and operation of these control systems.

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Real-time control of nitrogen removal using three ORP bending-points: signification, control strategy and results

Water Science & Technology ◽

10.2166/wst.1996.0027 ◽

1996 ◽

Vol 33 (1) ◽

pp. 275-280 ◽

Cited By ~ 16

Author(s):

S. Plisson-Saune ◽

B. Capdeville ◽

M. Mauret ◽

A. Deguin ◽

P. Baptiste

Keyword(s):

Control Systems ◽

Real Time ◽

Control Strategy ◽

Pilot Scale ◽

Real Time Control ◽

Nitrogen And Phosphorus ◽

Nitrogen And Phosphorus Removal ◽

Load Variations ◽

New Methods ◽

Time Control

The necessity to achieve nitrogen and phosphorus removal in wastewater, according to the European Directive (EEC 1991), leads to the conception of new methods to control the aeration of low-loaded activated sludge plants. The behaviour of N.NOx concentrations and of ORP during a complete nitrification-denitrification cycle is described by a typical profile with 3 bending-points: α, β and χ. The goal of this study is to get more insights into the biological and chemical signification of the bending-points. This leads to the conception of new real-time control systems able to be adaptive to the influent load variations and free from ORP drift problems. The results obtained on pilot-scale plant using a three bending-points based control strategy show a real advantage through a decrease of the global aeration duration.

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DQN-BASED TRAFFIC SIGNAL CONTROL SYSTEMS

Chronos Journal ◽

10.52013/2658-7556-57-7-6 ◽

2021 ◽

Vol 6 (7(57)) ◽

pp. 16-18

Author(s):

Ivan Vladimirovich Kondratov

Keyword(s):

Reinforcement Learning ◽

Control Systems ◽

Real Time ◽

Traffic Control ◽

Optimization Methods ◽

Traffic Signal ◽

Modern World ◽

Signal Control ◽

Traffic Signal Control ◽

Traffic Signal Control Systems

Real-time adaptive traffic control is an important problem in modern world. Historically, various optimization methods have been used to build adaptive traffic signal control systems. Recently, reinforcement learning has been advanced, and various papers showed efficiency of Deep-Q-Learning (DQN) in solving traffic control problems and providing real-time adaptive control for traffic, decreasing traffic pressure and lowering average travel time for drivers. In this paper we consider the problem of traffic signal control, present the basics of reinforcement learning and review the latest results in this area.

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Problems of Choosing Optimization Method for Next-Generation Aviation Radio Control Systems

SPIIRAS Proceedings ◽

10.15622/sp.2019.18.3.534-556 ◽

2019 ◽

Vol 18 (3) ◽

pp. 535-557 ◽

Cited By ~ 1

Author(s):

Vladimir Verba ◽

Vladimir Merkulov

Keyword(s):

Control Systems ◽

Dynamic Properties ◽

Optimization Methods ◽

Optimization Method ◽

Information Support ◽

Computationally Efficient ◽

Maneuvering Targets ◽

Control Signals ◽

High Dynamics ◽

And Control

Analysis of the trends of military-technical confrontation in the aerospace sector allows us to identify a number of areas that directly affect the information and control side of the operation of aviation radio control systems, including: group use of means of attack and defence; the qualitative complexity of the laws of the mutual spatial placement of the aircraft; high dynamics, nonstationarity of environment; use of control modes and information support on the verge of buckling, which is characteristic of super-maneuverable aircraft and intensively maneuvering targets tracking systems; the discrepancy of the dynamic properties of airborne targets and interceptors; growing complexity of information support algorithms. Mathematical apparatus used for synthesis of aircraft control systems must provide: effective guidance on targets maneuvering under complex laws, including the change of signs of derivatives; guaranteed withdrawal from the boundaries of stable (dangerous) work, including collision prevention in groups; accounting for the discrepancy between the dynamic properties; redistribution of control priorities in the guidance process; universality of the formation of guidance methods and feasibility of information support algorithms. Analysis of the possibilities of classical optimization methods based on minimization of quadratic quality functionals showed that they are not able to meet the totality of these requirements and thus new approaches are required. As such, it is proposed to use the synthesis of control signals that are optimal for a minimum of quadratic-biquadrate quality functional. The application of this approach in the framework of computationally efficient local optimization is considered. An example of the synthesis of a method of guidance, illustrating the possibility of the formation of control signals, providing guidance of inertial aircraft to intensively maneuvering targets accounting for both linear and nonlinear dependences on the operation errors and the mismatch of the dynamic characteristics of the target and interceptor.

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Efficient Hyperparameter Optimization for Physics-based Character Animation

Proceedings of the ACM on Computer Graphics and Interactive Techniques ◽

10.1145/3451254 ◽

2021 ◽

Vol 4 (1) ◽

pp. 1-19

Author(s):

Zeshi Yang ◽

Zhiqi Yin

Keyword(s):

Control Systems ◽

Task Difficulty ◽

State Of The Art ◽

Optimization Methods ◽

Search Space ◽

Character Animation ◽

Bayesian Optimization ◽

Efficiency Gain ◽

Hyperparameter Optimization ◽

Optimization Framework

Physics-based character animation has seen significant advances in recent years with the adoption of Deep Reinforcement Learning (DRL). However, DRL-based learning methods are usually computationally expensive and their performance crucially depends on the choice of hyperparameters. Tuning hyperparameters for these methods often requires repetitive training of control policies, which is even more computationally prohibitive. In this work, we propose a novel Curriculum-based Multi-Fidelity Bayesian Optimization framework (CMFBO) for efficient hyperparameter optimization of DRL-based character control systems. Using curriculum-based task difficulty as fidelity criterion, our method improves searching efficiency by gradually pruning search space through evaluation on easier motor skill tasks. We evaluate our method on two physics-based character control tasks: character morphology optimization and hyperparameter tuning of DeepMimic. Our algorithm significantly outperforms state-of-the-art hyperparameter optimization methods applicable for physics-based character animation. In particular, we show that hyperparameters optimized through our algorithm result in at least 5x efficiency gain comparing to author-released settings in DeepMimic.

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