Heterogeneous Hardware Cyber-Physical System Optimization
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Solution Overview
Problem
Designing and deploying reliable and robust cyber-physical control systems is challenging due to complex interactions between distributed systems, non-linear dynamics, and the need for comprehensive validation and verification, particularly in applications like smart grids and microgrids, where traditional methods require re-testing and re-certification for any system changes.
Innovation Solution
A computer-implemented system and method using parallel floating point math functionality on a system with heterogeneous hardware components for global optimization and verification, which includes a control program, a model of a physical system, an objective function, and a requirements verification program, allowing for co-simulation and deployment on a heterogeneous hardware system to optimize and control cyber-physical systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional text-based programming languages and compilers are used to model and control physical systems, then programming flexibility and control are maintained, but user accessibility and ease of operation deteriorate because users must master complex programming techniques and the abstraction between conceptual modeling and implementation reduces efficiency
Solution Approach 1:
The patent introduces a graphical programming environment as an intermediary layer between the user and the underlying complex programming language. This graphical interface allows users to model physical systems using intuitive visual elements without needing to master text-based programming syntax and compilation processes, thereby improving ease of operation while maintaining access to powerful control capabilities through the underlying compiler infrastructure
Solution Approach 2:
The patent creates visual copies or representations of programming concepts through graphical icons and diagrams that mirror the functional structure of the underlying text-based code. These graphical representations serve as accessible proxies for complex programming constructs, allowing users to interact with system models visually while the compiler translates these visual models into executable code, thus reducing the barrier to entry without sacrificing programming power
2Ease of manufacture
If conventional text-based programming languages are used for controlling instrumentation and industrial automation systems, then precise control and implementation capability are maintained, but development and maintenance difficulty increases because traditional users lack programming training and the languages are not intuitive
Solution Approach 1:
The graphical programming environment serves as an intermediary that bridges intuitive visual modeling with precise text-based implementation. Users can develop software through visual drag-and-drop operations that automatically translate into precise control code via the compiler, making software development easier while maintaining control precision through the faithful translation of visual models to executable code
Solution Approach 2:
The patent replaces the mechanical process of manual text-based coding with an automated compilation process that transforms graphical models into executable code. This substitution eliminates the need for users to manually write and debug text code, significantly easing software development while maintaining reliability through the systematic translation process that preserves the intended control logic
3Reliability
If traditional testing and certification methods are used for cyber-physical control systems, then comprehensive validation is achieved, but productivity and development speed deteriorate because any system changes require re-testing and re-certification
Solution Approach 1:
The patent implements preliminary automated testing and verification processes that are integrated into the graphical programming environment itself. Rather than requiring separate re-testing cycles for every system change, the system performs automated validation checks during the development process, identifying issues early and reducing the need for extensive re-certification when modifications are made, thus maintaining reliability while improving productivity
Solution Approach 2:
The system incorporates continuous feedback mechanisms that automatically monitor and validate system behavior as changes are made to the graphical model. This real-time feedback provides immediate information about potential issues, allowing developers to correct problems during development rather than discovering them during formal certification, thereby maintaining system reliability while significantly reducing development cycles
Data Source
AI summary
Global optimization and verification of cyber-physical systems using graphical floating point math functionality on a heterogeneous hardware system (HHS). A program includes floating point implementations of a control program (CP), model of a physical system (MPS), objective function, requirements verification program (RVP), and/or global optimizer. A simulation simulates HHS implementation of the program using co-simulation with a trusted model, including simulating behavior and timing of distributed execution of the program on the HHS, and may verify the HHS implementation using the RVP. The HHS is configured to execute the CP and MPS concurrently in a distributed manner. After deploying the program to the HHS, the HHS is configured to globally optimize (improve) the CP and MPS executing concurrently on the HHS via the global optimizer. The optimized MPS may be usable to construct the physical system. The optimized CP may be executable on the HHS to control the physical system.