INCA AptiTune

Download INCA AptiTune white paper (PDF) from our download section

Download INCA AptiTune brochure (PDF) from our download section

Dowload a detailed overview of the INCA Aptitune functionality from our documentation section

Have a look at the INCA AptiTune Demo (Movie)

Introduction

Tuning PID loops by trial and error takes up valuable time that engineers can ill afford. In addition, modern PID algorithms can have 5 tuning parameters to adjust. Interactive PID loops can cause the tuning on one PID loop to change the performance of other loops interacting with it. A 3 x 3 tuning challenge (such as the coil outlet temperature on an ethane furnace) can have up to 15 parameters to adjust, each parameter affecting the response of every loop. Doing this well requires a proven package, INCA AptiTune is field proven in every continent and on every DCS.

Six reasons to fine tune your PID loops with INCA AptiTune

• Process Realism: Tuning starts with a user supplied open loop response model. The input model is smoothed by fitting a high order state space model with explicit dead time to it. This model conversion helps make the process response model more realistic and allows reliable tuning constants to be calculated even when the supplied model was identified from a relatively short data set.

• Tuning that takes Plant Constraints into Account: It is straightforward to achieve closed loop behaviour that is tailored to the specific requirements of the process. INCA AptiTune does not use simplistic tuning rules, but rather uses a state space model of the open loop process, DCS specific PID equations and a non-linear optimiser to achieve the best possible trade-off between design objectives such as stability, setpoint tracking and disturbance rejection while dealing with dynamic interactions between the loops. The user has full control over how to balance these trade-offs.

• Detailed Control Design Objectives: The user can limit Process Variable (PV) overshoot to a setpoint response as well as limit the amount of output movement for a specified setpoint change. A loop can be made faster at the expense of another loop or the disturbance rejection can be improved at the expense of the setpoint tracking response. In addition the user can explicitly specify the maximum noise level in the output for a specific amount of noise in the PV. This can be especially useful for tuning fired heater draft pressure controls where PV noise is a significant factor in choosing the best tuning constants.

• One-Shot Tuning: What is most impressive about the software is that for many applications it delivers "one-shot tuning". The user tunes within the safe environment of his or her PC, where the optimiser can try out several thousand possibilities in a matter of seconds. With a reasonably accurate open loop response model, the calculated tuning on all of the control loops can be entered at the same time and will work as predicted. To confirm this, the user can make a setpoint change on the live system and compare the actual response to what was predicted on INCA AptiTune. This approach can save days or weeks of engineering effort, while significantly improving the overall process performance.

• Loop Stability despite Changes in the Process: By specifying the worst case changes in process gain and dead time, INCA AptiTune uses a robust approach to ensure all of the interacting loops will be stable if the process response changes. This feature provides protection against response model errors and ensures that a moderately accurate model will be adequate for tuning purposes. Nonetheless, all process control engineers will be aware that accurate open loop models will always result in the best performance of the tuned loop.

• PID Tuning Optimisation: The user can optimise not only Proportional, Integral and Derivative terms, but also Setpoint Filter and Derivative Filter as required. INCA AptiTune allows the user to pick the best PID equation available and take advantage of all the available tuning parameters in confidence.

Key Features

• Loop types:INCA AptiTune can tune SISO PID loops and simultaneous interactive PID loops, tuning up to 15 PID loops at the same time
  

• Input Data: The user can specify input models using several methods:

• Import a NxN discrete Model (MDL file)
• Copy and paste data from Excel/CSV files (SISO only)
• Specify directly a model using:
• First Order plus Dead Time
• Second Order Over-damped / Under-damped
• Z / Laplace Transfer Functions

• PID Loop Definition: The user needs to specify, as a minimum:

• Instrument Ranges (OP and PV)

  

• PID Equation
• Typical SP and Load Steps
• Optimisation weights (PV, OP, Disturbance)
• Gain and Dead Time Margins for Robustness
 The user can specify additional constraints:
• OP noise limit
• Maximum OP Change
• Maximum PV Overshoot
• Minimum Damping Ratio
• Desired Rise Time
• PV Deviation and Return Time (for distrbances)

• PID Tuning Visualisation:PID loop visualis ation of the loop performance includes:

• Setpoint change
• Load disturbance rejection
• Noise simulation
• Robustness

• Simulation capabilities: The user can simulate disturbances that are likely to impact the process and therefore the PID loops, such as:
  

• PV, SP and OP signal generators
• Step, impulse, ramp, zero and noise