Abstract: An engine and one or more aftertreatment subsystems integrated into one system for optimization and control. At least one controller may be connected to the engine and the one or more aftertreatment subsystems. The controller may contain and execute a program for the optimization and control of the one system. Controller may receive information pertinent to the engine and the one or more aftertreatment subsystems for the program. The controller may prescribe setpoints and constraints for measured variables and positions of actuators according to the program to aid in effecting the optimization and control of the one system.

Abstract: An approach and system for engine and aftertreatment system optimization. Emissions of an engine may be reduced by an aftertreatment mechanism. Control of the engine and the aftertreatment mechanism may be coordinated for the best overall efficiency relative to both fuel consumption and the emissions reduction. Engine and aftertreatment control may also be optimized in terms of cost function minimization. Individual efficiencies of the engine and aftertreatment mechanism are not necessarily significant by themselves. Therefore, the engine and aftertreatment mechanism should be controlled in a manner to achieve the optimality of the engine and the aftertreatment mechanism together as one entity.

Abstract: A system for reducing environmentally harmful emissions from an internal combustion engine. The system may incorporate an exhaust after-treatment device. The exhaust after-treatment device may use selective catalytic reduction to remove certain emissions from the exhaust of the engine. Urea solution may be inserted into the exhaust emissions, which is decomposed to ammonia to become a reduction agent for reduction of NOx in the emissions. The engine may be managed by a controller and the exhaust after-treatment device may be managed by another controller. These controllers may be cascaded, or be managed by a third controller that provides hierarchical or coordinated control of engine performance and emissions reduction. The engine and the exhaust after-treatment device may be modeled to aid in designing and building a system for coordinated control of an actual engine and a selective catalytic reduction after-treatment device. The controllers may be predictive model controllers.

Abstract: Methods and systems for the design and implementation of optimal multivariable MPC controllers for fast-sampling constrained dynamic systems utilizing a primal-dual feasibility approach and/or a graph approach. The primal-dual feasibility approach can compute and store matrices defining constraints of quadratic programming problems in an off-line part in order to calculate vectors of Lagrange multipliers and an optimizer. Then primal-dual feasibility can be checked in an on-line part using the Lagrange multipliers and the optimizer can provide a unique optimal solution for the constrained dynamic system. The graph approach can compute and store the matrices and the vectors, and also prepare and store a structure of directed graph in off-line part. An optimizer for a given parameter vector can be determined in on-line part using the directed graph, the matrices and the vectors.

Abstract: One method includes assigning one of a number of predefined values to each of a number of shadow prices of the system, distributing the assigned predefined shadow price values to a number of sub-problems, wherein each sub-problem is associated with one of a number of subsystems of the system, performing an analysis, including: determining a parametric solution and a region of validity for each of the number of sub-problems, determining an intersection of the regions of validity of all the parametric solutions, determining whether the optimization problem is solved from the parametric solutions, determining one or more shadow price updates based on the parametric solutions, and distributing the updated shadow prices to sub-problems having a region of validity that does not include the updated shadow prices, and repeating the analysis using the updated shadow prices until the optimization problem is solved from the parametric solutions of the number of sub-problems.

Abstract: An engine control unit having a one-time integration of a model predictive control template via a potentially long software process. Changes to the control structure may subsequently be made via a calibration dataset connected to the engine control unit without incurring the potentially long and laborious software process of implementing the template of other approaches in the related art.

Abstract: The subject mater herein relates to coal mills and, more particularly, inferential pulverized fuel flow sensing and manipulation within a coal mill. Various embodiments provide systems, methods, and software to manipulate a primary air flow rate and a coal feed rate into a coal mill to produce a target pulverized fuel flow. Some embodiments include sensing a differential pressure between two or more locations within a coal mill to estimate a recirculated load of coal at one or more stages within the coal mill.

Abstract: A method and system for combining a feedback control and a feedforward control in a linear MPC to minimize effect of model uncertainty. An externally computed feedforward signal, which is more accurate and reliable, can be utilized in association with the MPC, A steady state relation between system parameters can be determined in order to compute the feedforward signal for a set of actuators associated with a non-linear system. A feedback MPC controller can then be designed. A state observer can be configured as an unknown input observer to estimate the effect of the feedforward signal. A strategy for manipulating the constraints of the MPC feedback signal can be implemented. A resulting control action for the actuators can be provided as a sum of corresponding feedback and feedforward signal while ensuring the constraints satisfaction.

Abstract: A system and method for solving a quadratic programming optimization problem with bound constraints using a semi-explicit QP solver with respect to an embedded platform is presented. A linear system of equations associated with a matrix (e.g., a Karush-Kuhn-Tucker matrix, KKT system) can be solved at each iteration of the solver based on a factorization approach. A set of partial factors with respect to the QP problem can be pre-computed off-line and stored into a memory. The factorization process of the KKT matrix can then be finished on-line in each iteration of the semi-explicit QP solver in order to effectively solve the QP optimization problems. The QP problem can be solved utilizing a standard active-set approach and/or a partial explicit approach based on a processor utilization and memory usage.

Abstract: A method includes associating a plurality of valve balancing units with a plurality of valves in a hydronic network. The method also includes adjusting a setting of at least one of the valves using at least one of the valve balancing units to balance the hydronic network. Adjusting the setting could include identifying a differential pressure across a valve and a flow rate of material through that valve. Adjusting the setting could also include comparing the identified differential pressure to a target differential pressure and/or the identified flow rate to a target flow rate. Adjusting the setting could further include instructing an actuator to adjust the setting until the identified differential pressure is within a first threshold of the target differential pressure and/or the identified flow rate is within a second threshold of the target flow rate.

Abstract: An engine control unit having a one-time integration of a model predictive control template via a potentially long software process. Changes to the control structure may subsequently be made via a calibration dataset connected to the engine control unit without incurring the potentially long and laborious software process of implementing the template of other approaches in the related art.

Abstract: Methods and systems for the design and implementation of optimal multivariable MPC controllers for fast-sampling constrained dynamic systems utilizing a primal-dual feasibility approach and/or a graph approach. The primal-dual feasibility approach can compute and store matrices defining constraints of quadratic programming problems in an off-line part in order to calculate vectors of Lagrange multipliers and an optimizer. Then primal-dual feasibility can be checked in an on-line part using the Lagrange multipliers and the optimizer can provide a unique optimal solution for the constrained dynamic system. The graph approach can compute and store the matrices and the vectors, and also prepare and store a structure of directed graph in off-line part. An optimizer for a given parameter vector can be determined in on-line part using the directed graph, the matrices and the vectors.

Abstract: A method and system of predictive model control of a controlled system with one or more physical components using a model predictive control (MPC) model, determining an iterative, finite horizon optimization of a system model of the controlled system, in order to generate a manipulated value trajectory as part of a control process. At time t sampling a current state of the controlled system a cost function minimizing manipulated variables trajectories is computed with the MPC model for a relatively short time horizon in the future, wherein the MPC uses a quadratic programming (QP) algorithm to find the optimal solution, and wherein the QP algorithm is solved using an Active Sets solver (AS) class algorithm with simple constraints based on gradient projection and using Newton step projection. A move of the manipulated value trajectory is implemented and the control process is moved forward by continuing to shift the prediction horizon forward.

Abstract: An engine control unit having a one-time integration of a model predictive control template via a potentially long software process. Changes to the control structure may subsequently be made via a calibration dataset connected to the engine control unit without incurring the potentially long and laborious software process of implementing the template of other approaches in the related art.

Abstract: A method and system for optimal model-based multivariable balancing for distributed hydronic networks based on global differential pressure/flow rate information. A simplified mathematical model of a hydronic system can be determined utilizing an analogy between hydronic systems and electrical circuits. Thereafter, unknown parameters can be identified utilizing the simplified mathematical model and a set of available measurements. Next, balancing valve settings can be calculated by reformulating the simplified mathematical model based on the parameterized model. The sum of pressure drops across selected balancing valves can be then minimized to achieve optimal economic performances of the system. The data can be collected and transferred to a central unit either by wireless communication or manually by reading the local measurement devices. Such a multivariable balancing approach provides a fast and accurate balancing of distributed hydronic heating systems based on a centralized and non-iterative approach.

Abstract: An engine control unit having a one-time integration of a model predictive control template via a potentially long software process. Changes to the control structure may subsequently be made via a calibration dataset connected to the engine control unit without incurring the potentially long and laborious software process of implementing the template of other approaches in the related art.

Abstract: An engine control unit having a one-time integration of a model predictive control template via a potentially long software process. Changes to the control structure may subsequently be made via a calibration dataset connected to the engine control unit without incurring the potentially long and laborious software process of implementing the template of other approaches in the related art.

Abstract: The subject mater herein relates to coal mills and, more particularly, inferential pulverized fuel flow sensing and manipulation within a coal mill. Various embodiments provide systems, methods, and software to manipulate a primary air flow rate and a coal feed rate into a coal mill to produce a target pulverized fuel flow. Some embodiments include sensing a differential pressure between two or more locations within a coal mill to estimate a recirculated load of coal at one or more stages within the coal mill.

Abstract: The subject matter herein relates to coal mills and, more particularly, inferential pulverized fuel flow sensing and manipulation within a coal mill. Various embodiments provide systems, methods, and software to manipulate a primary air flow rate and a coal feed rate into a coal mill to produce a target pulverized fuel flow. Some embodiments include sensing a differential pressure between two or more locations within a coal mill to estimate a recirculated load of coal at one or more stages within the coal mill.

Abstract: A method and system for combining a feedback control and a feedforward control in a linear MPC to minimize effect of model uncertainty. An externally computed feedforward signal, which is more accurate and reliable, can be utilized in association with the MPC. A steady state relation between system parameters can be determined in order to compute the feedforward signal for a set of actuators associated with a non-linear system. A feedback MPC controller can then be designed. A state observer can be configured as an unknown input observer to estimate the effect of the feedforward signal. A strategy for manipulating the constraints of the MPC feedback signal can be implemented. A resulting control action for the actuators can be provided as a sum of corresponding feedback and feedforward signal while ensuring the constraints satisfaction.