Information Technology
SISO Model Predictive Controller
WARF: P04113US
Inventors: James Rawlings, Gabriele Pannocchia, Nabil Laachi
The Wisconsin Alumni Research Foundation (WARF) is seeking commercial partners interested in developing a fast, easily tuned controller specifically tailored to SISO processes.
Overview
Currently, most single-input, single-output (SISO) systems use a proportional, integral, derivative (PID) controller. The PID controller is simple, fast, and easily implemented on simple computing hardware; however, it is also difficult to tune; falls short in setpoint tracking accuracy and disturbance rejection; lacks robustness when the system and system model are mismatched; and has difficulty handling system constraints.
Most large-scale processes with multiple-inputs, multiple-outputs (MIMO) systems use model-based control methods such as linear quadratic (LQ) control or model predictive control (MPC). Model-based control methods explicitly optimize the process, can handle complex multivariable processes and account for constraints; however, they are slow, difficult to implement on simple computing hardware and hard to tune.
Most large-scale processes with multiple-inputs, multiple-outputs (MIMO) systems use model-based control methods such as linear quadratic (LQ) control or model predictive control (MPC). Model-based control methods explicitly optimize the process, can handle complex multivariable processes and account for constraints; however, they are slow, difficult to implement on simple computing hardware and hard to tune.
The Invention
UW-Madison researchers have developed a fast, easily tuned controller specifically tailored to SISO processes. The controller combines the best features of model-based control methods and PID controllers and performs better than PID controllers on all SISO processes.
This offset-free, constrained, linear quadratic (CLQ) controller has three modules: a state and disturbance estimator, a target calculation and a constrained dynamic optimization. Each of the modules is implemented efficiently so that the overall CLQ algorithm has little computational cost and can be applied using simple hardware and software.
This offset-free, constrained, linear quadratic (CLQ) controller has three modules: a state and disturbance estimator, a target calculation and a constrained dynamic optimization. Each of the modules is implemented efficiently so that the overall CLQ algorithm has little computational cost and can be applied using simple hardware and software.
Applications
- Controling SISO processes
Key Benefits
- Fast execution – makes control decisions quickly
- Easily tuned
- Can be implemented on simple computing hardware
- Optimizes control behavior
- Superior to PID controllers on all SISO processes
- Especially exceeds performance of PID controllers for systems with large time delays; setpoints that are or become unreachable due to constraints on the manipulated variable; complex, high-order dynamics; or significant measurement and process noise
Tech Fields
For current licensing status, please contact Emily Bauer at [javascript protected email address] or 608-960-9842