Related Experiment Video
Updated: May 7, 2026
08:35
Interactive and Visualized Online Experimentation System for Engineering Education and Research
Published on: November 24, 2021
Safety analysis of discrete event systems using a simplified Petri net controller
Meysam Zareiee1, Abbas Dideban1, Ali Asghar Orouji1
1Electrical Engineering Department, Semnan University, Semnan, Iran.
ISA Transactions
|October 1, 2013
Summary
This study presents a method to prevent forbidden states in discrete event systems using Petri nets. Generalized mutual exclusion constraints, derived from Integer Linear Programming, ensure system safety while maintaining maximal permissiveness.
Area of Science:
- Control Engineering
- Computer Science
- Operations Research
Background:
- Discrete event systems (DES) are crucial in modeling complex systems.
- Petri nets are widely used for DES modeling.
- Identifying and avoiding forbidden states is essential for system reliability.
Purpose of the Study:
- To develop a method for preventing forbidden states in Petri net models of DES.
- To ensure system safety and reliability through constraint-based control.
- To achieve maximally permissive control.
Main Methods:
- Utilizing Petri net models for discrete event systems.
- Formulating and solving Integer Linear Programming (ILP) problems.
- Constructing generalized mutual exclusion constraints.
- Implementing control places to enforce constraints.
Main Results:
- A novel method for preventing forbidden states in DES.
- Successfully applied ILP to derive necessary constraints.
- Demonstrated that constraints can be enforced using a minimal number of control places and arcs.
- Achieved maximally permissive control, balancing safety and efficiency.
Conclusions:
- The proposed method effectively prevents forbidden states in DES.
- The ILP-based approach offers a systematic way to design controllers.
- The resulting controller is both safe and maximally permissive, optimizing system performance.
Related Concept Videos
01:26PD Controller: Design
In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
01:19PID Controller
Proportional-Integral-Derivative (PID) controllers are widely used in various control systems to enhance stability and performance. In a thermostat, it adjusts heating or cooling based on the temperature difference between the actual and desired levels. They are often used in automotive speed systems, effectively managing sudden speed changes while maintaining a constant speed under varying conditions. On the other hand, PI controllers, commonly employed in voltage regulation, enhance stability...
01:24PI Controller: Design
Proportional Integral (PI) controllers are a fundamental component in modern control systems, widely used to enhance performance and mitigate steady-state errors. They are particularly effective in applications such as automatic brightness adjustment on smartphones, where they excel at mitigating steady-state errors for step-function inputs. Unlike PD controllers, which require time-varying errors to function optimally, PI controllers leverage their integral component to address residual...
01:07Time-Domain Interpretation of PD Control
Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...
Consider the example of control of motor torque. Initially, a positive...
01:26Feedback control systems
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
01:22Block Diagram Reduction
The process of deriving the transfer function of a control system often involves reducing its block diagram to a single block. This simplification can be achieved through a series of strategic operations, including relocating branch points and comparators. These operations preserve the overall function of the system while allowing for easier manipulation and combination of blocks.
The first step in this process is the identification and relocation of a branch point. A branch point, where a...
The first step in this process is the identification and relocation of a branch point. A branch point, where a...