Abstract: The present invention provides an algorithm that does not relax the problem at the very onset, even if xf is infeasible. Instead, it solves the EQP with the initial guess for the active set without relaxing the problem. If this solution to the first EQP is not optimal, but nevertheless feasible, we can use this as our guess for the feasible point. This has the advantage of being a feasible point that is consistent with the initial active set, whereas the initial guess used in the previous method is not necessarily so.

Abstract: Real-time control of a dynamical system is provided by determining control variables that get as close as possible to producing a desired response. Additional consideration of physical limitations leads to a convex Quadratic Program with inequality constraints that needs to be solved in real-time. A new active set algorithm is described to solve the convex Quadratic Program efficiently that meets real-time requirements. Based on the key observation that the physical limitations of the system translate to optimal active sets that remain relatively unchanged over time (even though the actual optimal controls may be varying), starting guesses for the active set obtained from the final iterate in the previous time period greatly reduces the number of iterations and hence allows the Quadratic Programs to be solved to convergence in real-time.

Abstract: The present invention provides an algorithm that does not relax the problem at the very onset, even if xf is infeasible. Instead, it solves the EQP with the initial guess for the active set without relaxing the problem. If this solution to the first EQP is not optimal, but nevertheless feasible, we can use this as our guess for the feasible point. This has the advantage of being a feasible point that is consistent with the initial active set, whereas the initial guess used in the previous method is not necessarily so.

Abstract: An active set algorithm exploits a ‘hot start’ for the set of binding constraints at optimality along with efficient linear algebra to make rapid progress towards the solution. The linear algebra is designed to deal with degenerate constraints as the required factorizations are performed and as degeneracy emerges, and not via a mostly unnecessary pre-process step. Combined together, these novel approaches enable solution of the control problem in real-time.

Abstract: A system and method more accurately solves equality-constrained a quadratic program without significantly increasing computational load. The solver can be used to iteratively determine the solution to a general quadratic program via an active set method. The algorithm determines which of the equality constraints are binding and which constraints are not. The non-binding constraints are dropped from the active set and the objective function improved. The non-binding constraints are identified based upon the signs of the Lagrange multipliers of the equality constraints. The algorithm determines the optimization variables and the Lagrange multipliers independently of one another based upon a single matrix factorization.

Abstract: A Model Predictive Control System, particularly useful in controlling gas turbine engines, formulates a problem of controlling the engine to achieve a desired dynamic response as a solution to a quadratic programming problem. The Model Predictive Control System also includes a quadratic programming problem solver solving the quadratic programming problem in real time using an interior point algorithm that searches for an optimal solution.

Abstract: A method and computer program product are presented for selecting and arranging an appropriate combination of network components, or elements, in a communications network. The selection of network components is done in a manner that maximizes the net present value of cash flow resulting from the provision of communications services between nodes of the network. The method comprises the steps of receiving information that constrains network design and price establishment, and then using the constraint information to select a combination of network components for each link in the communications network. According to the invention, the selection of network components is performed for each of several successive time periods, effectively planning the evolution of the network. The selections are made so that the network components satisfy demand over time while maximizing the net present value of the cash flow that results from the provision of communications services.

Abstract: A method and computer program product are presented for selecting and arranging an appropriate combination of network components, or elements, in a communications network. The selection of network components is done in a manner that maximizes the net present value of cash flow resulting from the provision of communications services between nodes of the network. The method comprises the steps of receiving information that constrains network design and price establishment, and then using the constraint information to select a combination of network components for each link in the communications network. According to the invention, the selection of network components is performed for each of several successive time periods, effectively planning the evolution of the network. The selections are made so that the network components satisfy demand over time while maximizing the net present value of the cash flow that results from the provision of communications services.

Abstract: A method of controlling a multivariable system includes the step of receiving a plurality of sensor signals indicating current conditions of the system and receiving a plurality of commands. The desired dynamic response of the system is then determined based upon the commands and the sensor signals. The problem of controlling the system to achieve the desired dynamic response without violating numerous actuator and physical constraints is then formulated as a quadratic programming problem. By solving the quadratic programming problem, the effector commands are determined and the physical constraints are enforced.

Abstract: An active set algorithm exploits a ‘hot start’ for the set of binding constraints at optimality along with efficient linear algebra to make rapid progress towards the solution. The linear algebra is designed to deal with degenerate constraints as the required factorizations are performed and as degeneracy emerges, and not via a mostly unnecessary pre-process step. Combined together, these novel approaches enable solution of the control problem in real-time.

Abstract: A method of controlling a multivariable system includes the step of receiving a plurality of sensor signals indicating current conditions of the system and receiving a plurality of commands. The desired dynamic response of the system is then determined based upon the commands and the sensor signals. The problem of controlling the system to achieve the desired dynamic response without violating numerous actuator and physical constraints is then formulated as a quadratic programming problem. By solving the quadratic programming problem, the effector commands are determined and the physical constraints are enforced.

Abstract: Real-time control of a dynamical system is provided by determining control variables that get as close as possible to producing a desired response. Additional consideration of physical limitations leads to a convex Quadratic Program with inequality constraints that needs to be solved in real-time. A new active set algorithm is described to solve the convex Quadratic Program efficiently that meets real-time requirements. Based on the key observation that the physical limitations of the system translate to optimal active sets that remain relatively unchanged over time (even though the actual optimal controls may be varying), starting guesses for the active set obtained from the final iterate in the previous time period greatly reduces the number of iterations and hence allows the Quadratic Programs to be solved to convergence in real-time.

Abstract: A method and computer program product are presented for selecting and arranging an appropriate combination of network components, or elements, in a communications network. The selection of network components is done in a manner that maximizes the net present value of cash flow resulting from the provision of communications services between nodes of the network. The method comprises the steps of receiving information that constrains network design and price establishment, and then using the constraint information to select a combination of network components for each link in the communications network. According to the invention, the selection of network components is performed for each of several successive time periods, effectively planning the evolution of the network. The selections are made so that the network components satisfy demand over time while maximizing the net present value of the cash flow that results from the provision of communications services.