Development

Development Principles

In control system design, development is about creating, testing, and refining systems to meet precise performance goals. This involves building models, designing controls, and validating them through simulation and real-world testing. Our approach ensures reliability, stability, and continuous improvement.

The process unfolds in key stages:

• Analysis: Studying system behavior to identify improvement areas.
• Design: Developing models and controls to enhance performance.
• Simulation: Testing and refining designs in a virtual environment.
• Real-World Testing: Validating performance under actual conditions.

Success requires deep expertise in system dynamics and software development, ensuring your control systems excel in any scenario.

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Development Methods

We employ a range of proven methods to deliver robust control systems, tailored to your needs:

• Model-Based Design: Using mathematical models to simulate and design systems before implementation.
• Iterative Design: Refining systems through multiple cycles based on test feedback.
• Co-Simulation: Simulating the control and physical systems together for accuracy.
• Rapid Prototyping: Quickly building and testing prototypes to catch issues early.
• Hardware-in-the-Loop Testing: Evaluating systems on physical prototypes in real conditions.
• Simulation-Based Optimization: Fine-tuning parameters through iterative simulations.

By combining these methods, we create control systems that are reliable, optimized, and ready for real-world challenges.

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Case Study: LLM Project Development

At JCBTech, we’ve developed an advanced Large Language Model (LLM) system to enhance automation workflows. Designed to run locally and deployed easily from an SD card, this solution ensures proprietary data remains secure while delivering cutting-edge AI capabilities to control systems.

• Analysis: We defined requirements for natural language processing, PLC integration, and real-time responsiveness, prioritizing local execution for security.
• Model-Based Design: Simulations modeled the LLM’s interaction with industrial protocols, ensuring seamless, secure data handling.
• Rapid Prototyping: Early SD card-based prototypes tested language comprehension and system compatibility, refining deployment ease.
• Co-Simulation: The LLM was validated alongside simulated factory setups, confirming performance without external data exposure.
• Optimization: Iterative simulations fine-tuned efficiency, reducing latency while maintaining robust local operation.

The result is a portable, secure LLM that streamlines automation processes, showcasing our ability to transform innovative ideas into practical, high-performance applications.

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