The widespread adoption of advanced control in industrial applications is undeniable, yet opinions differ on the root causes of its popularity. While algorithms and models are often considered the core strengths of advanced control, the reality is more nuanced. In single-variable control, advanced control offers little advantage over PID, as PID controllers are highly effective and cost-efficient, even for systems with large dead times, significant time lags, or higher-order dynamics. Historically, efforts to replace PID in single-variable control have yielded limited success and failed to achieve widespread adoption. The notion that advanced control algorithms are inherently superior to PID does not fully explain PID’s century-long dominance in industrial settings.
Both advanced control and PID rely on models, but PID tuning implicitly incorporates models (e.g., through response-based methods like Lambda tuning) and leverages robustness to tolerate uncertainties, reducing the need for precise models. Advanced control, contrary to common belief, also does not strictly depend on highly accurate models. The Lambda tuning method, for instance, prioritizes response curve analysis over detailed system identification, emphasizing simplicity and robustness.
The true engineering reasons for advanced control’s popularity lie in its ability to address complex, multivariable control problems that PID struggles to handle effectively. Below are the key factors driving its industrial adoption:
- Multivariable Coordination and Optimization:
- PID excels in single-variable control but is less suited for coordinating multiple variables under constraints. Advanced control was developed to tackle multivariable optimization problems, which are critical in complex industrial processes. As plants incorporate more control mechanisms and grow in complexity, the need for coordinated optimization increases, making advanced control indispensable.
- Degrees of Freedom:
- In engineered systems, measurement points often outnumber manipulated variables, but operational systems typically have more manipulated variables than controlled variables. PID’s single-variable nature requires reformulating complex problems into paired single-loop configurations, forcing a square system (equal numbers of controlled and manipulated variables). Advanced control, however, can directly handle non-square systems (unequal numbers of controlled and manipulated variables). For example, branch temperature balancing or level equalization can be implemented straightforwardly with advanced control without constructing intermediate variables, such as controlling two temperatures with three manipulated variables.
- Flexibility:
- Advanced control allows real-time adjustments to models and parameters when boundary conditions or operational strategies change, without requiring significant reconfiguration. If performance is suboptimal, modifications are straightforward. For instance, a reflux system designed to control a reflux tank’s level can seamlessly switch to using steam for level control if the reflux valve saturates. Such adaptability is challenging with complex PID-based schemes, which often require intricate reconfiguration.
- Safety:
- Configuring complex control schemes in a Distributed Control System (DCS) involves multiple steps and poses safety risks due to potential errors in configuration, logic, or parameters. Offline implementation may be restricted in some plants due to these risks, and recovering from errors is time-consuming. Advanced control reduces these risks, as it typically requires minimal or no DCS downloads, and implementation is more controlled and less error-prone.
- Economic Benefits:
- Advanced control software lowers the skill threshold and implementation costs for solving complex control problems. The more complex the problem, the greater the cost advantage of advanced control. This is why advanced control first gained traction in large petrochemical plants, where complexity is high. Unlike complex PID-based schemes (e.g., split-range, fan-out, cascade, override, or valve position control), which require explicit single-loop configurations, advanced control achieves similar functionality through models and parameters without introducing new variables or complex logic.
In summary, advanced control’s industrial popularity stems from its ability to provide simple, flexible, safe, and cost-effective solutions for multivariable, constrained optimization problems that PID cannot efficiently address. It complements rather than replaces PID, thriving in scenarios where complexity and coordination are paramount. As you aptly noted, “Simple, flexible, convenient, safe, and cost-effective industrial solutions—who wouldn’t love them?”