Honeywell International Inc.

Sujit Gaikwad

Sachi Dash

Konstantinos Tsakalis

Ranganathan Srinivasan

Sanjay Kantilal Dave

Sriram Hallihole

Gunter Stein

Madhukar Madhavamurthy Gundappa

Dale Mukavetz

Sachindra K Dash

Mohamad Hanify Vhora

Ward MacArthur

Ravi Bhaskar

Herman Dharmarajah

Bill Sheridan

Kosta S Tsakalis

Sachindra Kumar Dash

Ward Macarthur

A model predictive controller (MPC) for controlling physical processes includes a non-linear control section that includes a memory that stores a non-linear (NL) model that is coupled to a linearizer that provides at least one linearized model, and a linear control section that includes a memory that stores a linear model. A controller engine is coupled to receive both the linearized model and linear model. The MPC includes a switch that in one position causes the controller engine to operate in a linear mode utilizing the linear model to implement linear process control and in another position causes the controller engine to operate in a NL mode utilizing the linearized model to implement NL process control. The switch can be an automatic switch configured for automatically switching between linear process control and NL process control.

Integrated linear/non-linear hybrid process controller

A system and method include providing waste water to a treatment tank, diffusing air into the waste water in the treatment tank to treat the waste water, and measuring Opercentage in off gas from the waste water having diffused air. Dissolved oxygen in the waste water is measured in further embodiments, and the amount of air diffused into the waste water may be controlled as a function of the measurements.

Aeration basin with off gas monitoring

A method to automatically tune control systems, the method comprising selecting a target loop transfer function for at least one plant subsystem in response to an input excitation, selecting at least one fit-error criterion for a plant subsystem transfer function, and automatically inputting the input excitation and tuning the plant subsystem transfer function to the target loop transfer function. The tuning includes automatically selecting a bandwidth of the plant subsystem transfer function from a plurality of bandwidths determined in accordance with limits of the plant subsystem, inputting the input excitation to the plant subsystem, determining the fit-error of the plant subsystem transfer function to the target loop transfer function in response to the input excitation, and continuing the selecting of a bandwidth in accordance with the fit-error criterion.

On-demand auto-tuner for a plant control system

An apparatus, method, and computer program are provided for controller performance monitoring in a process control system. A level of disturbance associated with the process system is determined, and at least one value identifying a stability measure of a controller in the process system is determined using the determined level of disturbance and operating data associated with operation of the process system. The at least one value is compared to at least one threshold value, and a problem with the controller is identified based on the comparison. As an example, the process system could represent a product production system. Also, the operating data could include at least one of: measurement data from one or more sensors and control data for one or more actuators. The controller may be operable to receive the measurement data and generate the control data.

Apparatus and method for controller performance monitoring in a process control system

A method of monitoring turbine engines used in aircraft from sensor signals from an engine for a predetermined set of engine characteristics. The signals are transmitted to a nonlinear engine model that predicts the output values for the given set of engine characteristics. The model generates residuals by calculating the difference between the actual values and the predicted values for each member of the set. The generated residuals are evaluated to estimate bounds of uncertainties as indicative of sensor noise. Incoming residuals from ongoing actual engine values are continuously tested against the bounds. A fault is signaled for each of the set of characteristics when a detected bound is exceeded. A computer is used to calculate the fault residual for each of the set of characteristics and the closest fault residual is selected as a diagnosed fault.

Model-based detection, diagnosis of turbine engine faults

A method and apparatus for automatically adjusting the gains of a feedback controller while the process continues to run and the controller continues to operate and control the process is disclosed. A desired closed-loop control bandwidth and a target loop transfer function are specified by the operator, and the tuning is accomplished automatically with minimal operator intervention and without the need for developing a model of the process. The automatic tuner subjects the process to one or more disturbance and the operation of both the process and the controller are monitored.

Auto-tuning controller using loop-shaping

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Glendale, AZ, United States of America

Sujit Gaikwad