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Aspen Apollo™
Non-linear model-predictive controller
Aspen Apollo is a non-linear, multi-variable model-predictive controller capable of full automation and dynamic optimization of product-grade transitions. It uses a combination of simple, first-principle models (general equations) in conjunction with non-linear approximation technology that can be safely used directly within a controller. Aspen Apollo is a core element of AspenTech’s aspenONE™ Advanced Process Control applications.
Features
- Full non-linear model-predictive control: Supports dynamic and steady state, as well as interacting nonlinearities.
- Reduced modeling complexity: Captures all relationships in a single model per controlled variable.
- All components of the solution reference the same model. Models are gain, time-constant, and delay-type models.
- State-space model formulation features Extended Kalman Filter for unmeasured disturbance handling.
- Requires little or no step testing.
- Highly accurate models, reliable process gain profiles: Eliminates reliance on lab feedback during transitions.
- Constraint ranking: Allows different variables to be ranked for targets and limits so that under certain conditions, the optimizer will focus on higher ranked constraints first.
- Dead time and dynamics: Supports independent dead-time alignment for each pair of relationships, as well as general state space models and parametric dynamics.
- Guaranteed gain and extrapolation: Ensures that bounded derivative network gains will be within specified bounds; models extrapolate sensibly outside data in existing operating regions.
- Variable dynamics support: Supports variable dynamics and dead times; model dynamics can be adjusted online in real-time.
- Gain constrained dynamics: Provides accurate modeling of non-linear gains across the entire operating space.
- Ease of use: Implements interfaces designed by operators for operators.
- Interactive graphical simulation environment: Simulates open loop and closed loop performance, helping you validate controller tuning including move plan, optimization, and unmeasured disturbance rejection.
Benefits
- Full automation and optimization of complex-grade transition strategies
- Easily model multiple catalysts and donors in a single model
- Faster grade transitions
- Reduced maintenance compared to multiple model per CV designs
- Robust solution (a single model per CV eliminates model conflict problems associated with controllers where the inferential model is different to the control model)
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Product Name Changes
With the release of aspenONE V7, we have renamed many of our engineering products to be more descriptive for new users. Click here to learn more
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