scholarly journals Formally proving whether the software implementation of models applied in instrumentation and control systems conform to the specified requirements

2021 ◽  
Vol 1 (7) ◽  
pp. 99-108
Author(s):  
Eduard S. Lapin ◽  
◽  
Marat I. Abdrakhmanov ◽  
Keyword(s):  
Control Systems ◽  
A Priori ◽  
Mining Industry ◽  
Software Implementation ◽  
Finite State Automaton ◽  
Software Model ◽  
Finite State ◽  
Initial Description ◽  
Priori Information ◽  
And Control

Research objective is to study the possibility to formally validate whether the model’s software implementation meets all the specified requirements of the systems, the model of which can be represented in the form of finite-state automata. Research relevance. At one of the first stages, the development of software for instrumentation and control systems provides for the creation of the system model. The model is based on the terms of reference, specification, and various a priori information. Most of the models for engineering systems in the modern mining industry (conveyor systems, ventilation systems, etc.) can be described in terms of the finite state automaton model. Such a model can be applied to solve diverse tasks. The next step is to implement the model in whole or in part. In this context, the task arises to determine the model’s software implementation conformity to its initial description. Results. One way to solve the task is to formally prove that the software model possesses the properties which are provided in the specification (description) of the initial model. By the example of the mine conveyor system, the paper illustrates the application of the method which consists in the software implementation of the corresponding finite-state automaton model, forecasting whether the model possesses the properties through theorems and their subsequent proof by applying special software. Conclusions. Formal methods of specification, development, and verification of system models’ software implementation together with other methods make it possible to improve the quality and reliability of solutions under development.

scholarly journals ОСОБЛИВОСТІ АВТОМАТИЗАЦІЇ КОНТРОЛЮ ТЕХНІЧНОГО СТАНУ МОРСЬКОГО ТРАНСПОРТУ

World Science ◽  
2019 ◽  
Vol 1 (3(43)) ◽  
pp. 19-25
Author(s):  
Коломієць Оксана Михайлівна
Keyword(s):  
Water Transport ◽  
A Priori ◽  
Technical Condition ◽  
Software Implementation ◽  
Effective Strategy ◽  
Kutta Method ◽  
A Priori Information ◽  
Automated Control ◽  
Runge Kutta Method ◽  
Priori Information

The article analyzes the principles of automation of the control of the technical condition of water transport vehicles, which has been determined: the principle of coherence; the principle of integration; Principle of independence of execution.It is determined that the most effective strategy is to improve the methods of automated control of the technical condition of water transport vehicles, which, unlike existing ones, is based on Markov processes, the Runge-Kutta method of numerical solution of the system of Kolmogorov differential equations and a priori information about the intensity of transitions from state to state.Using the software implementation of the model significantly improves performance due to the ergonomics of the interface and reduced number of operations.

scholarly journals A METHOD FOR INFERRING HIERARCHICAL DYNAMICS IN STOCHASTIC PROCESSES

2008 ◽  
Vol 11 (01) ◽  
pp. 1-16 ◽  
Author(s):  
OLOF GÖRNERUP ◽  
MARTIN NILSSON JACOBI
Keyword(s):  
Time Series ◽  
Stochastic Processes ◽  
A Priori ◽  
Main Idea ◽  
A Priori Knowledge ◽  
Finite State Automaton ◽  
State Spaces ◽  
Markovian Dynamics ◽  
Finite State ◽  
Operational Algorithm

Complex systems may often be characterized by their hierarchical dynamics. In this paper we present a method and an operational algorithm that automatically infer this property in a broad range of systems — discrete stochastic processes. The main idea is to systematically explore the set of projections from the state space of a process to smaller state spaces, and to determine which of the projections impose Markovian dynamics on the coarser level. These projections, which we call Markov projections, then constitute the hierarchical dynamics of the system. The algorithm operates on time series or other statistics, so a priori knowledge of the intrinsic workings of a system is not required in order to determine its hierarchical dynamics. We illustrate the method by applying it to two simple processes — a finite state automaton and an iterated map.

CONTROL OF COMPLEX PEAK-TO-PEAK DYNAMICS

2002 ◽  
Vol 12 (12) ◽  
pp. 2927-2936 ◽  
Author(s):  
CARLO PICCARDI ◽  
SERGIO RINALDI
Keyword(s):  
Hybrid Model ◽  
Chaotic Systems ◽  
Reduced Model ◽  
Finite State Automaton ◽  
Output Variable ◽  
One Dimensional ◽  
Chua's Circuit ◽  
Scalar Output ◽  
Finite State ◽  
And Control

The paper illustrates a method for the design of suitable controllers of chaotic systems characterized by complex peak-to-peak dynamics, namely by a recursive relationship between consecutive peaks (relative maxima) of a scalar output variable. For such systems, a reduced model can be defined which, in general, is a hybrid model composed of a one-dimensional map and a finite-state automaton. The issues related to the identification and control of such a reduced model are discussed with the help of three applications: the Chua's circuit, a market with advertizing, and a CO2laser.

scholarly journals Asimovian Adaptive Agents

2000 ◽  
Vol 13 ◽  
pp. 95-153 ◽  
Author(s):  
D. F. Gordon
Keyword(s):  
Side Effects ◽  
Response Time ◽  
Formal Verification ◽  
A Priori ◽  
Finite State Automaton ◽  
Evolutionary Learning ◽  
Adaptive Agents ◽  
Finite State ◽  
Behavioral Constraints ◽  
Positive Results

The goal of this research is to develop agents that are adaptive and predictable and timely. At first blush, these three requirements seem contradictory. For example, adaptation risks introducing undesirable side effects, thereby making agents' behavior less predictable. Furthermore, although formal verification can assist in ensuring behavioral predictability, it is known to be time-consuming. Our solution to the challenge of satisfying all three requirements is the following. Agents have finite-state automaton plans, which are adapted online via evolutionary learning (perturbation) operators. To ensure that critical behavioral constraints are always satisfied, agents' plans are first formally verified. They are then reverified after every adaptation. If reverification concludes that constraints are violated, the plans are repaired. The main objective of this paper is to improve the efficiency of reverification after learning, so that agents have a sufficiently rapid response time. We present two solutions: positive results that certain learning operators are a priori guaranteed to preserve useful classes of behavioral assurance constraints (which implies that no reverification is needed for these operators), and efficient incremental reverification algorithms for those learning operators that have negative a priori results.

scholarly journals Information indicators of radar portraits of air objects and generalized indicators of the ability of recognition systems to extract information

2018 ◽  
Vol 21 (5) ◽  
pp. 94-104
Author(s):  
R. N. Akinshin ◽  
A. V. Peteshov
Keyword(s):  
A Priori ◽  
Quality Criterion ◽  
Recognition System ◽  
Mean Values ◽  
Amount Of Information ◽  
Information Group ◽  
Priori Information ◽  
Stationary Random Processes ◽  
And Control ◽  
Decisive Rule

To improve the quality of recognition of air objects, it is proposed to use a priori information contained in reference portraits, which are formed adaptively to the conditions of observation. A decisive rule is formulated on the assignment of the observed target to the k-th group under the assumption that the signal and background are normal stationary random processes with zero mean values and the covariance matrices of portraits are known. The quality criterion of recognition is proposed, the result of which implementation is a decision with a probability not below the required Ptr. The price for the implementation of this criterion is the decision content change. For the implementation of the radar recognition system (HRD) with structural-parametric adaptation of the radar it is proposed to introduce into the system a device of the quality and control forecast, which conducts the assessment (forecast) of the amount of information and change the decisive rule of the HRD system in accordance with the received assessment. An indicator of the amount of information extracted by the recognition system from the radar portrait (RLP) is introduced, which is thought as a measure of reducing uncertainty in the decision-making process on the target group with the help of the RLR system. It is shown that the amount of extracted information depends not only on the parameters of the RLP, but also on the algorithm of its processing. The potential amount of information about the goal of the k-th information group contained in the RLP is determined, the concept of a sufficiently informative portrait with the recognition of the goals of all groups is introduced. The concepts of differential and integral contrast are formalized in the case of arbitrarily correlated RLP. The introduced concepts of differential and integral contrasts for the special case of uncorrelated RLP are extended to the General case of arbitrarily correlated RLP.

scholarly journals Autonomous Trajectory Planning and Control of Anti-Radiation Loitering Munitions under Uncertain Conditions

Electronics ◽  
2021 ◽  
Vol 10 (19) ◽  
pp. 2399
Author(s):  
Linyuan Bai ◽  
Hongchuan Luo ◽  
Haifeng Ling
Keyword(s):  
Trajectory Planning ◽  
Particle Filtering ◽  
A Priori ◽  
Planning And Control ◽  
Autonomous Planning ◽  
Sensing Model ◽  
Priori Information ◽  
Radar Information ◽  
And Control ◽  
Trajectory Planning And Control

As an autonomous system, an anti-radiation loitering munition (LM) experiences uncertainty in both a priori and sensed information during loitering because it is difficult to accurately know target radar information in advance, and the sensing performance of the seeker is affected by disturbance and errors. If, as it does in the state of the art, uncertainties are ignored and the LM travels its planned route, its battle effectiveness will be severely restricted. To tackle this problem, this paper studies the method of autonomous planning and control of loitering routes using limited a priori information of target radar and real-time sensing results. We establish a motion and sensing model based on the characteristics of anti-radiation LMs and use particle filtering to iteratively infer the target radar information. Based on model predictive control, we select a loitering path to minimize the uncertainty of the target information, so as to achieve trajectory planning control that is conducive to the acquisition of target radar information. Simulation results show that the proposed method can effectively complete the autonomous trajectory planning and control of anti-radiation LMs under uncertain conditions.

scholarly journals Functional approach to deterministic finite-state automata systems dynamic modeling

2021 ◽  
Vol 1 ◽  
pp. 113-122
Author(s):  
Eduard S. Lapin ◽  
◽  
Marat I. Abdrakhmanov ◽  
Keyword(s):  
Dynamic Modeling ◽  
Mining Industry ◽  
Good Alternative ◽  
Functional Approach ◽  
Algorithm Analysis ◽  
Substantial Part ◽  
Finite State Automaton ◽  
Finite State Automata ◽  
Advantages And Disadvantages ◽  
Finite State

Research aim is to study the functional approach to modeling the deterministic finite-state automata system which is not confined to the elements communication topology and the heterogeneity of the algorithm types. Relevance. The substantial part of engineering systems applied in the mining industry may be described through the finite-state automaton model. They include the mine conveyor systems, shaft signal systems, processing facilities control systems, etc. Such model makes it possible to shorten the time spent on control software development and carry out algorithm analysis, debug, and testing effectively. There are a lot of effective approaches and tools to solve the problem of finite-state automata dynamic modeling, each of which has its own advantages and disadvantages. Methodology. In this article, the methodology of finite-state automata systems modeling is considered as applied to mine conveyor systems. Results. Final-state automata (FSA) models have been developed together with the conditions for FSA systems dynamic modeling as applied to mine conveyor systems. Conclusions. The considered approach to modeling, which involves functors and applicative functors 122 "Izvestiya vysshikh uchebnykh zavedenii. Gornyi zhurnal". No. 2. 2021 ISSN 0536-1028 for structure composition and its operational dynamics study, as well as the possibility to mathematically prove the model’s properties, makes the approach a good alternative when choosing tools for systems models development.

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