Abstract:
The present invention provides a controller for controlling a modeled plant robustly against disturbance. The controller comprises an estimator and a control unit. The estimator estimates disturbance applied to the plant. The control unit determines an input to the plant so that an output of the plant converges to a desired value. The input to the plant is determined to include a value obtained by multiplying the estimated disturbance by a predetermined gain. Since estimated disturbance is reflected in the input to the plant, control having robustness against disturbance is implemented. The controller may comprise a state predictor. The state predictor predicts the output of the plant based on the estimated disturbance and dead time included in the plant. The control unit determined the input to the plant so that the predicted output converges to a desired value. Since the state predictor allows for the dead time, the accuracy of the control is improved. The estimated disturbance is reflected in the predicted output, an error between the predicted output and an actual output of the plant is removed.
Abstract:
A control system for a plant is disclosed. The control system includes a controller which controls the plant based on a controlled object model which is obtained by modeling the plant. The controlled object model is modeled using an input and an output of the plant which are sampled at intervals of a period which is longer than a control period of the controller. The controller carries out a control process of the plant at intervals of the control period.
Abstract:
A control system for a plant is disclosed. In this control system, a model parameter vector of a controlled object model which is obtained by modeling said plant, is calculated. A sliding mode controller is included in the control system. The sliding mode controller controls the plant using the identified model parameter vector. A damping input is calculated according to a speed of change in an output of the plant, and an element of the model parameter vector. A control input form the sliding mode controller to the plant includes the calculated damping input.
Abstract:
A control system for a plant is disclosed. According to this system, a model parameter vector of a controlled object model which is obtained by modeling the plant, is identified. A controller controls the plant using the identified model parameter vector. An identifying error of the model parameter vector is calculated, and an updating vector is calculated according to the identifying error. The updating vector has at least one first element which is relevant to an input or an output of the plant, and a second element which is irrelevant to the input and the output of the plant. The updating vector is corrected by multiplying a past value of at least one first element of the updating vector by a predetermined value which is greater than “0” and less than “1”, and multiplying a past value of the second element of the updating vector by “1”. The model parameter vector is calculated by adding the corrected updating vector to a reference vector of the model parameter vector.
Abstract:
An exhaust purification system for an internal combustion engine is provided that can steadily maintain a NOx purification rate of a selective reduction catalyst to be high without allowing the fuel economy or marketability to deteriorate. The exhaust purification system includes a NO2—NOx ratio adjustment mechanism that causes a NO2—NOx ratio to change; and a NO2—NOx ratio perturbation controller that executes NO2—NOx ratio perturbation control so that a NO2 balance of the selective reduction catalyst in a predetermined time period, with NO2 adsorption being positive and NO2 release being negative, is 0. Herein, NO2—NOx ratio perturbation control is defined as control that alternately executes NO2 increase control to cause the NO2—NOx ratio to be greater than a reference value near 0.5, and NO2 decrease control to cause the NO2—NOx ratio to be less than the reference value.
Abstract:
A catalyst degradation determination device is provided that can determine the degradation of a selective reduction catalyst with high precision while also suppressing a temporary decline in purification performance. By way of controlling a urea injection device, the catalyst degradation determination device increases, in a selective reduction catalyst in a state in which the storage amount is a maximum, the storage amount thereof by a detection reduced-amount portion DSTNH3—JD, and then decreases the amount until it is determined that ammonia slip has occurred. Then, degradation is determined based on the time at which the slip determination flag FNH3—SLIP was set to “1” when fluctuating the storage amount. The detection reduced-amount portion DSTNH3—JD is set to a value that is larger than the storage capacity of the selective reduction catalyst in a degraded state and smaller than the storage capacity of the selective reduction catalyst in a normal state.
Abstract:
An exhaust purification system for an internal combustion engine is provided that can steadily maintain a NOx purification rate of a selective reduction catalyst to be high without allowing the fuel economy or marketability to deteriorate. The exhaust purification system includes a NO2—NOx ratio adjustment mechanism that causes a NO2—NOx ratio to change; and a NO2—NOx ratio perturbation controller that executes NO2—NOx ratio perturbation control so that a NO2 balance of the selective reduction catalyst in a predetermined time period, with NO2 adsorption being positive and NO2 release being negative, is 0. Herein, NO2—NOx ratio perturbation control is defined as control that alternately executes NO2 increase control to cause the NO2—NOx ratio to be greater than a reference value near 0.5, and NO2 decrease control to cause the NO2—NOx ratio to be less than the reference value.
Abstract:
A control system for a plant is disclosed. The control system includes a controller for controlling the plant based on a controlled object model which is obtained by modeling the plant. The controlled object model is modeled using an input and an output of the plant which are sampled at intervals of a sampling period which is longer than a control period of the controller. The sampled input of the plant is a filtered control output which is obtained by filtering an output of the controller. The controller carries out a control process of the plant at intervals of the control period.
Abstract:
The present invention provides a controller for controlling a modeled plant robustly against disturbance. The controller comprises an estimator and a control unit. The estimator estimates disturbance applied to the plant. The control unit determines an input to the plant so that an output of the plant converges to a desired value. The input to the plant is determined to include a value obtained by multiplying the estimated disturbance by a predetermined gain. Since estimated disturbance is reflected in the input to the plant, control having robustness against disturbance is implemented. The controller may comprise a state predictor. The state predictor predicts the output of the plant based on the estimated disturbance and dead time included in the plant. The control unit determined the input to the plant so that the predicted output converges to a desired value. Since the state predictor allows for the dead time, the accuracy of the control is improved. The estimated disturbance is reflected in the predicted output, an error between the predicted output and an actual output of the plant is removed.
Abstract:
A control system for a plant is disclosed. The control system includes a response specifying type controller for controlling the plant with a response specifying type control. The response specifying type controller calculates a nonlinear input according to a sign of a value of a switching function and an output of the plant. The switching function is defined as a linear function of a deviation between the output of the plant and a control target value. A control input from the response specifying type controller to the plant includes the nonlinear input.