Managing multi-mode tasks with time cost and quality levels using optimal discrete control synthesis

Even for suciently simple single-input control-ane systems without state constraints the subject of analytical and qualitative investigation of global optimal control synthesis is developed rather poorly in the literature on optimal control theory and its applications. The aim of this work is to present numerical-analytical and qualitative methods to construct global optimal control synthesis with reference to a nonlinear mathematical model describing interactions between the production of a company, its technology stock and R&D investments on a xed time in

Infinite-time optimal controllers have been designed for a dispersion-type tubular reactor model within the framework of adaptive-critic-based neuro-controller design. For the reactor control problem, which is governed by two coupled nonlinear partial differential equations, an optimal controller synthesis scheme is presented using two sets of neural networks. One set of neural networks captures the relationship between the states and the control, whereas the other set of networks captures the relationship between the states and the co-states. This innovative approach solves the optimal controller in a feedback form. This methodology can be viewed as a practical computational tool in designing optimal controllers for distributed parameter systems in general.

This paper presents an optimal nonlinear control scheme for a renewable-energy-based micro-grid. The optimal controller synthesis is based on the state-dependent Riccati equation approach, where it is considered the minimization of a performance index (cost functional), which results in an efficient control strategy. The micro-grid is used to integrate the energy from renewable resources, with the facility to storage energy, to provide of energy to loads and to provide/consume energy to/from the utility grid. Simulation results are presented to assess the performance of the proposed controller for a case study micro-grid, which is composed of a wind energy system, a load, a storage element and the connection with the utility grid.

The problem of optimal control synthesis of complex nonlinear and multidimensional systems oriented on the building of integrated control systems with the adaptation and self-organization properties is of much current interest. The development of optimization methods employed in control problems demonstrated their effectiveness and has led to the construction of algorithms of approximate solution of optimization problems that significantly extends the class of control problems that can be set. In this work we consider a synthesis of optimal control for affine nonlinear system, in which a special emphasis is placed on the degenerate problems of optimal control. Our approach is based on the extension of the method of minimization of generalized work function by properly transforming the initial nondegenerate problem of optimal control into degenerate problem of optimal control synthesis. The search for the solution is based on the suboptimal strategy that includes the construction of minimizing sequences that converge interval-wise to the optimal solution of the initial problem. We obtain some optimality conditions as well as the necessary and sufficient conditions of existence of optimal solution.

Solution to the variation problem for information path functional of a controlled random process

The synthesis of optimal control in a fourth-order linear speed of response problem

An optimal control problem modeling the economic behavior of a representative household is studied. The existence of its solution is proved, necessary optimality conditions in the form of the Pontryagin–Clarke maximum principle are obtained, and an optimal control synthesis is constructed. The model is identified against Russian statistical data. The model is used to analyze consumer crediting in Russia and its influence on the household economy under COVID-19 pandemic conditions.

The tax big data supervision system and method, including the distributed real-time management and control system deployed in the superior unit and each subordinate unit, the superior distributed real-time management and control system is used to receive the management and control rules, and issue the management and control rules to the subordinate distributed real-time management and control System: The distributed real-time management and control system writes the massive data in the data source at the same level into the distributed message queue Kafka in real time, and uses the distributed stream computing engine Flink to compare and calculate based on the management and control rules, and write the data that conforms to the management and control rules. Enter the alarm information into Kafka; the lower-level distributed real-time management and control system pushes the alarm information in the Kafka subscription at this level to Kafka in the upper-level distributed real-time management and control system; the upper-level distributed real-time management and control system pushes the alarm information in the Kafka subscription to users , at the same time push the alarm information to the distributed search engine ElasticSearch to save, and provide the historical alarm information query function.

1 A Survey on Computational Optimal Control.- Issues in the Direct Transcription of Optimal Control Problems to Sparse Nonlinear Programs.- Optimization in Control of Robots.- Large-scale SQP Methods and their Application in Trajectory Optimization.- Solving Optimal Control and Pursuit-Evasion Game Problems of High Complexity.- 2 Theoretical Aspects of Optimal Control and Nonlinear Programming.- Continuation Methods In Boundary Value Problems.- Second Order Optimality Conditions for Singular Extremals.- Synthesis of Adaptive Optimal Controls for Linear Dynamic Systems.- Control Applications of Reduced SQP Methods.- Time Optimal Control of Mechanical Systems.- 3 Algorithms for Optimal Control Calculations.- Second Order Algorithm for Time Optimal Control of a Linear System.- An SQP-type Solution Method for Constrained Discrete-Time Optimal Control Problems.- Numerical Methods for Solving Differential Games, Prospective Applications to Technical Problems.- Construction of the Optimal Feedback Controller for Constrained Optimal Control Problems with Unknown Disturbances.- Repetitive Optimization for Predictive Control of Dynamic Systems under Uncertainty.- Optimal Control of Multistage Systems Described by High-Index Differential-Algebraic Equations.- A New Class of a High Order Interior Point Method for the Solution of Convex Semiinfinite Optimization Problems.- A Structured Interior Point SQP Method for Nonlinear Optimal Control Problems.- 4 Software for Optimal Control Calculations.- Automated Approach for Optimizing Dynamic Systems.- ANDECS: A Computation Environment for Control Applications of Optimization.- Application of Automatic Differentiation to Optimal Control Problems.- OCCAL: A mixed symbolic-numeric Optimal Control CALculator.- 5 Applications of Optimal Control.- A Robotic Satellite with Simplified Design.- Nonlinear Control under Constraints of a Biological System.- An Object-Oriented Approach to Optimally Describe and Specify a SCADA System Applied to a Power Network.- Near-Optimal Flight Trajectories Generated by Neural Networks.- Performance of a Feedback Method with Respect to Changes in the Air-Density during the Ascent of a Two-Stage-To-Orbit Vehicle.- Linear Optimal Control for Reentry Flight.- Steady-State Modelling of Turbine Engine with Controllers.- Shortest Paths for Satellite Mounted Robot Manipulators.- Optimal Control of the Industrial Robot Manutec r3.

Gear factories are most typical discrete manufacturing factories. Many gear factories are striving to explore how to achieve intelligent manufacturing in order to improve efficiency and reduce costs. Digital twin technology is currently one of the most reliable ways to achieve intelligent manufacturing. This article aims to establish a real-time control system in order to promote intelligent manufacturing for discrete manufacturing factories. Firstly, a model for a digital twin gear factory is put forward based on the characteristics of gear factories, and the composition of a real-time control system for gear factories is clarified. Then, a human–computer interaction architecture for the real-time control system is proposed. The real-time control system consists of three parts as follows: a monitoring module, a virtualizing module, and a controlling module. At work, it appears as a kind of human–machine interaction form with the three following interfaces: a monitoring window, a virtualizing window, and a controlling window. Finally, a gear factory, which is specialized in manufacturing the intermediate shaft dual gear of a new energy vehicle gearbox, develops a set of software for the real-time control system. The prototype software is obtained through some development activities such as 3D MAX and WebGL virtualization modeling and OPC UA and REST communication design.

For regular vehicles, the vibration generated when a vehicle passes through a groove or step is dampened but still remains and causes whole-body vibration (WBV) to occupants through vehicle seat. Several epidemiological studies have clearly demonstrated that prolonged exposure to vibration from vehicles is detrimental to human health and may cause motion sickness. To reduce this whole-body vibration. We designed a simple and effective feed-forward control system with compact actuator compatible to the limited under-seat dimension and power outlet of compact general passenger cars and successfully authenticated the possibility of vertical vibration reduction by controlling the vehicle seat surface vertical displacement. In this research, we designed a real-time feed-forward control system with transfer function model estimation. This real-time control system contains a commercial DSP device providing coherence input and output with a controllable delay. With the application of transfer function model and state space model, this system successfully estimated the upcoming vibration acceleration according to the input of the vibrational acceleration time-domain data acquired from lower arm when the test vehicle passing a step. Furthermore, it is possible to process the input data and control the linear actuator precisely to reduce the vertical impact observed as setting force reduction.

Finite-time partial stability and stabilization, and optimal feedback control

This paper is concerned with the problem of validation in the context of numerical computations in control. We explore the possibility of using computer algebra tools and interval methods to compute solutions which have guarantees on accuracy, e.g. which are not subject to unknown errors due to rounding or approximation. We demonstrate that this is possible for two common norms of a linear system (L <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> and L <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> ) and H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> -optimal controller synthesis. We further discuss some of the issues involved in achieving a validation property for other problems of controller synthesis.

Voting is an important operation in multichannel computation paradigm and realization of ultrareliable and real-time control systems that arbitrates among the results of N redundant variants. These systems include N-modular redundant (NMR) hardware systems and diversely designed software systems based on N-version programming (NVP). Depending on the characteristics of the application and the type of selected voter, the voting algorithms can be implemented for either hardware or software systems. In this paper, a novel voting algorithm is introduced for real-time fault-tolerant control systems, appropriate for applications in which N is large. Then, its behavior has been software implemented in different scenarios of error-injection on the system inputs. The results of analyzed evaluations through plots and statistical computations have demonstrated that this novel algorithm does not have the limitations of some popular voting algorithms such as median and weighted; moreover, it is able to significantly increase the reliability and availability of the system in the best case to 2489.7% and 626.74%, respectively, and in the worst case to 3.84% and 1.55%, respectively.

We have designed an active stressed lap and its control mode is that an computer sends control orders to the control system of the active stress lap, under windows operating system. The control mode has a shortage, which is a limit exists when we use the lap to complete an aspheric surface deformation task with a fast focal ratio, because windows system is not real-time. Therefore, we have designed a real-time deformation control system for the active stressed lap. The paper makes an introduction to the structure of the deformation control system of the active stressed lap. Secondly, gives a detailed presentation on the design of the test system from software and hardware two aspects .Finally, the paper makes a dynamic response test on the deformation control system of stressed lap, a stability test on the control system and an overall performance test.