Chemical Process Closed-Loop Control Using Dynamic Process Simulation
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Solution Overview
Problem
Industrial-scale chemical installations face challenges in optimizing operation, maintaining safety, and preventing failures, particularly in complex systems with multiple subsystems, which often result in significant costs and inefficiencies.
Innovation Solution
A closed-loop control system is implemented using sensors to acquire process data, which is transferred via a fieldbus to a control system and a computer system containing a simulation program and closed-loop control program. This system calculates and adjusts manipulated variables to achieve setpoint values, utilizing a client-server architecture and potentially incorporating a machine-learning module for improved control and dynamic behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If an extended process control system is implemented in complex chemical installations with multiple subsystems, then control and transparency are improved, but device complexity increases
Solution Approach 1:
The control system is divided into multiple independent control modules, each responsible for specific subsystems or functions. This segmentation allows the complex control task to be distributed across manageable units, improving overall control reliability while keeping individual module complexity low. Each module can operate semi-independently, facilitating easier maintenance and fault isolation.
Solution Approach 2:
A standardized interface layer is introduced between the various subsystems and the control modules. This intermediary layer provides uniform communication protocols and data exchange formats, enabling complex multi-subsystem control without requiring complex point-to-point connections. The interface layer acts as a mediator that simplifies the overall system architecture while maintaining comprehensive control capabilities.
2Manufacturing precision
If real-time dynamic process simulation is implemented, then control precision and failure prevention are improved, but use of energy and computational resources increases
Solution Approach 1:
The dynamic process simulation is executed in periodic cycles rather than continuously. Control modules perform simulation calculations at predetermined time intervals, updating process models and predicting future states at these discrete moments. This periodic execution maintains control precision by regularly refreshing the simulation data while significantly reducing computational resource consumption compared to continuous real-time simulation.
Solution Approach 2:
The simulation is performed with appropriate levels of detail based on operational conditions. During normal stable operation, simplified simulation models are used that require fewer computational resources. When approaching critical thresholds or during transient conditions, more detailed and computationally intensive simulations are activated to provide higher precision control where it is most needed, rather than maintaining maximum simulation fidelity at all times.
3Productivity
If advanced control systems are retrofitted to existing installations, then production optimization is improved, but loss of time and implementation costs increase
Solution Approach 1:
Control modules are designed and configured offline before being deployed to the chemical installation. Simulation models, control algorithms, and parameter settings are developed and validated in advance using historical process data. This preliminary preparation allows for thorough testing and optimization without disrupting actual production, significantly reducing on-site implementation time while ensuring the control system is ready to immediately optimize production upon deployment.
Solution Approach 2:
The control system uses digital replicas and virtual models of the chemical installation processes. Instead of physically modifying existing equipment, virtual copies of process models are created and used for simulation and control. This digital copying approach allows advanced control functionality to be implemented through software rather than hardware modifications, reducing installation time and costs while maintaining production optimization capabilities.
Data Source
AI summary
A method for closed-loop control of a chemical process may involve acquiring process data with sensors, transferring the process data to a control system via a fieldbus, transferring a subset of the process data to a computer system that includes a simulation program for stationary and dynamic process simulation of the chemical process, a closed-loop control program for implementing a closed-loop controller, and a memory for storing simulated state variables, cyclically repeatedly calculating and storing the simulated state variables of the chemical process by the simulation program from the subset of the process data, transferring a setpoint value of a control variable of the chemical process to the closed-loop control program, reading a subset of the simulated state variables for input into the closed-loop control program, ascertaining a manipulated variable to achieve the setpoint value by the closed-loop control program, and transferring the calculated manipulated variable to the control system.