# US 2013/0158680 A1 · Hybrid Control System > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2013/0158680 A1 - Document ID: US20130158680A1 - Status: Published application - Kind: A1 - Application number: 13/331,844 - Filed: 2011-12-20 - Published: 2013-06-20 - Earliest claimed: 2011-12-20 - Assignees: Pratt & Whitney - Inventors: James W. Fuller - Web page: https://patentgrep.com/patent/US20130158680A1 ## CPC - G05B 13/048: {using a predictor} - G05B 2219/42017: Mimo controller with many inputs and outputs - G05B: CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS (systems for controlling or regulating non-electric variables G05D; systems for regulating electric or magnetic variables G05F; control devices or systems insofar as characterised by mechanical features only G05G) ## Abstract A hybrid control system and a method for predicting a behavior of a physical system using the hybrid control system is disclosed. The hybrid control system may include a model inverting control system capable of implementing a model inverting control law and determining an active set of goals and limits and a model predictive control system capable of implementing a model predictive control law and utilizing the active set of goals and limits to determine current effector requests, the current effector requests being used to control behavior of the physical system. ## Claims ### Claim 1 A hybrid control system for predicting a behavior of a physical system, the hybrid control system comprising: a model inverting control system capable of implementing a model inverting control law and determining an active set of goals and limits; and a model predictive control system capable of implementing a model predictive control law and utilizing the active set of goals and limits to determine current effector requests, the current effector requests being used to control behavior of the physical system. ### Claim 2 (depends on 1) The hybrid control system of claim 1, further comprising an actuator servo loop that receives the current effector requests from the model predictive control system and generates actuator commands. ### Claim 3 (depends on 2) The hybrid control system of claim 2, further comprising one or more actuators that receive the actuator commands and manipulate the behavior of the physical system. ### Claim 4 (depends on 1) The hybrid control system of claim 1, further comprising one or more sensors capable of determining a current state of the physical system. ### Claim 5 (depends on 1) The hybrid control system of claim 1, further comprising an estimator capable of receiving information from one or more sensors of the physical system and providing feedback to the model predictive control system and the model inverting control system based upon a current state of the physical system. ### Claim 6 (depends on 1) The hybrid control system of claim 1, wherein the model inverting control system receives one or more commands and one more limits as inputs. ### Claim 7 (depends on 1) The hybrid control system of claim 1, wherein the model inverting control system implements a constrained optimization to predict one future controller update. ### Claim 8 (depends on 1) The hybrid control system of claim 1, wherein the model predictive control system implements a constrained optimization to predict a plurality of future controller updates. ### Claim 9 (depends on 8) The hybrid control system of claim 8, wherein the model predictive control system predicts the plurality of future controller updates in a single iteration. ### Claim 10 (depends on 8) The hybrid control system of claim 8, wherein the constrained optimization utilizes the active set of goals and limits from the model inverting control system to predict the plurality of future controller updates. ### Claim 11 (depends on 1) The hybrid control system of claim 1, wherein the model inverting control law is a constrained dynamic inversion control law. ### Claim 12 (depends on 1) The hybrid control system of claim 1, wherein the physical system is an engine. ### Claim 13 A method for predicting behavior of a physical system, the method comprising: providing a hybrid control system having (a) a model inverting control system capable of implementing a model inverting control law; and (b) a model predictive control system capable of implementing a model predictive control law; receiving one or more commands and limits as inputs; determining by the model inverting control system an active set of goals and limits based upon the one or more commands and limits; inputting the active set of goals and limits along with the one or more commands and limits into the model predictive control system; and computing current effector requests based upon the active set of goals and limits for controlling behavior of the physical system. ### Claim 14 (depends on 13) The method of claim 13, wherein computing the current effector requests comprises performing a constrained optimization in a single iteration. ### Claim 15 (depends on 13) The method of claim 13, further comprising an actuator servo loop for receiving the current effector requests and generating one or more actuator commands. ### Claim 16 (depends on 15) The method of claim 15, further comprising one or more actuators for receiving the one or more actuator commands and manipulating the behavior of the physical system. ### Claim 17 (depends on 13) The method of claim 13, further comprising determining a current state of the physical system for determining the active set of goals and limits and the current effector requests. ### Claim 18 A hybrid control system, comprising: a model inverting control system capable of receiving one or more commands and limits and generating an active set of limits and goals; a model predictive control system capable of receiving the one or more commands and limits and the active set of goals and limits to generate current effector requests in a single iteration; an actuator servo loop capable of converting the current effector requests into actuator commands; one or more actuators capable of receiving the actuator commands and controlling a behavior of a physical system; and an estimator capable of providing feedback to the model predictive control system and the model inverting control system. ### Claim 19 (depends on 18) The hybrid control system of claim 18, wherein the model predictive control system determines a performance index that utilizes a diagonal weighting matrix T to determine the current effector requests. ### Claim 20 (depends on 19) The hybrid control system of claim 19, wherein elements of the diagonal weighting matrix T are big numbers if a corresponding limit is active and the elements are zero if the corresponding limit is inactive.