Main.Modes History

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November 22, 2014, at 10:59 PM by 107.188.175.164 -
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  1. Sequential dynamic estimation (SQE) - new 22 Nov 2014
  2. Sequential dynamic optimization (SQO) - new 22 Nov 2014
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  1. Sequential dynamic estimation (SQE) - Newly Released on 22 Nov 2014
  2. Sequential dynamic optimization (SQO) - Newly Released on 22 Nov 2014
November 22, 2014, at 10:58 PM by 107.188.175.164 -
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  1. Sequential dynamic estimation (SQE) - under development
  2. Sequential dynamic optimization (SQO) - under development
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  1. Sequential dynamic estimation (SQE) - new 22 Nov 2014
  2. Sequential dynamic optimization (SQO) - new 22 Nov 2014
September 29, 2014, at 06:11 PM by 10.5.113.110 -
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  1. Nonlinear control (CTL)

Modes 1-3 are steady state modes with all derivatives set equal to zero. Modes 4-6 are dynamic modes where the differential equations define how the variables change with time. Each mode has a steady state and dynamic option.

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  1. Nonlinear control / dynamic optimization (CTL)
  2. Sequential dynamic simulation (SQS)
  3. Sequential dynamic estimation (SQE) - under development
  4. Sequential dynamic optimization (SQO) - under development

Modes 1-3 are steady state modes with all derivatives set equal to zero. Modes 4-6 are dynamic modes where the differential equations define how the variables change with time. Modes 7-9 are the same as 4-6 except the solution is performed with a sequential versus a simultaneous approach. Each mode for simulation, estimation, and optimization has a steady state and dynamic option.

October 02, 2008, at 01:32 PM by 158.35.225.228 -
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Modes 2 and 5 are estimation modes. Mode 2 is for steady-state estimation and mode 5 is for dynamic estimation. Mode 2 is also known as the data reconciliation step in a real-time optimization solution. Mode 5 is also known as moving horizon estimation. Mode 5 is equivalent to the Kalman filter when the model is linear, the disturbance noise is white, and the probability distribution function is assumed Gaussian.

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Modes 2 and 5 are estimation modes. Mode 2 is for steady-state estimation and mode 5 is for dynamic estimation. Mode 2 is also known as the data reconciliation step in a real-time optimization solution. Mode 5 is also known as moving horizon estimation. Mode 5 is equivalent to the Kalman filter when the model is linear, the disturbance noise is white, and the probability density function is assumed Gaussian.

October 01, 2008, at 11:09 AM by 158.35.225.229 -
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  1. Nonlinear control (NLC)
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  1. Nonlinear control (CTL)
October 01, 2008, at 10:56 AM by 158.35.225.229 -
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  1. Moving horizon estimation (MHE)
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  1. Moving horizon estimation (EST)
September 30, 2008, at 09:31 AM by 158.35.225.227 -
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Modes 3 and 6 are optimization and control modes. Mode 3 performs steady-state optimization. Combined with mode 2, this constitutes a real-time optimization (RTO) solution. Mode 6 has a similar objective as mode 3 but is solved with a time-varying model. For linear models, this is often referred to as control. For nonlinear models, this is often referred to as nonlinear control (NLC) or nonlinear model predictive control (NMPC).

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Modes 3 and 6 are optimization and control modes. Mode 3 performs steady-state optimization. Combined with mode 2, this constitutes a real-time optimization (RTO) solution. Mode 6 has a similar objective as mode 3 but is solved with a time-varying model. For linear models, this is often referred to as control. For nonlinear models, this is referred to as nonlinear control (NLC) or nonlinear model predictive control (NMPC).

September 29, 2008, at 12:38 PM by 158.35.225.229 -
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September 29, 2008, at 12:38 PM by 158.35.225.229 -
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September 29, 2008, at 12:37 PM by 158.35.225.229 -
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September 29, 2008, at 09:56 AM by 158.35.225.229 -
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  • Simulation
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Simulation

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  • Estimation
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Estimation

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  • Optimization and Control
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Optimization and Control

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September 29, 2008, at 09:55 AM by 158.35.225.229 -
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The core of all modes is the non-linear model. Each mode retrieves information from the non-linear model to give predictions or provides information to improve the model accuracy through parameter fitting.

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The core of all modes is the non-linear model. Each mode interacts with the nonlinear model to receive or provide information. There are 6 modes of operation for the APMonitor software.

  1. Steady-state simulation (SS)
  2. Model parameter update (MPU)
  3. Real-time optimization (RTO)
  4. Dynamic simulation (SIM)
  5. Moving horizon estimation (MHE)
  6. Nonlinear control (NLC)

Modes 1-3 are steady state modes with all derivatives set equal to zero. Modes 4-6 are dynamic modes where the differential equations define how the variables change with time. Each mode has a steady state and dynamic option.

  • Simulation

Modes 1 and 4 are simulation-only modes. These simulation modes are for steady-state and dynamic investigation of the model. There is no optimization with the simulation modes. The model serves as a virtual process or simulator.

  • Estimation

Modes 2 and 5 are estimation modes. Mode 2 is for steady-state estimation and mode 5 is for dynamic estimation. Mode 2 is also known as the data reconciliation step in a real-time optimization solution. Mode 5 is also known as moving horizon estimation. Mode 5 is equivalent to the Kalman filter when the model is linear, the disturbance noise is white, and the probability distribution function is assumed Gaussian.

  • Optimization and Control

Modes 3 and 6 are optimization and control modes. Mode 3 performs steady-state optimization. Combined with mode 2, this constitutes a real-time optimization (RTO) solution. Mode 6 has a similar objective as mode 3 but is solved with a time-varying model. For linear models, this is often referred to as control. For nonlinear models, this is often referred to as nonlinear control (NLC) or nonlinear model predictive control (NMPC).

September 29, 2008, at 09:36 AM by 158.35.225.229 -
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Non-linear Model Core

The core of all modes is the non-linear model. Each mode retrieves information from the non-linear model to give predictions or provides information to improve the model accuracy through parameter fitting.

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September 29, 2008, at 09:33 AM by 158.35.225.229 -
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September 29, 2008, at 09:31 AM by 158.35.225.229 -
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September 29, 2008, at 09:23 AM by 158.35.225.229 -
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September 29, 2008, at 09:21 AM by 158.35.225.229 -
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September 29, 2008, at 09:19 AM by 158.35.225.229 -
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Modes of Operation

APMonitor is designed to enable multiple modes of operation with one model. This model is defined in terms of differential and algebraic equations. The program handles all of the configuration and interfacing to the solvers.