Abstract:
A process is modeled by a dynamic model, handling time dependent relations between manipulated variables of different process sections (10A-D) and measured process output variables. Suggested input trajectories for manipulated variables for a subsequent time period are obtained by optimizing an objective function over a prediction time period, under constraints imposed by the dynamic process model and/or preferably a production plan for the same period. The objective function comprises relations involving predictions of controlled process output variables as a function of time using the process model, based on the present measurements, preferably by a state estimation procedure. By the use of a prediction horizon, also planned future operational changes can be prepared for, reducing any induced fluctuations. In pulp and paper processes, process output variables associated with chemical additives can be used, adapting the optimization to handle chemical additives aspects.
Abstract:
For determination as to whether there is a possibility that temperature control satisfying conditions according to an upper limit LH_i and a lower limit LL_i of the annealing control temperatures of annealing object steel sections i will be realized under restrictions on limit values U and D of the control temperature increase and decrease rates, computation is performed without using dynamic programming requiring an enormous amount of data on a continuous annealing line of a steelwork. Annealing object steel sections in an annealing object steel band 12 to be computed are assigned numbers 1, 2, . . . , n in order from the first time division in the direction of movement. T_i is a time required to pass the annealing object steel section i through a predetermined point at which the steel section undergoes temperature control. LH_1nullLL_1nullb is given. X_inullnullIL_inullD*T_i, IH_inullU*T_inull is computed. When X_ L_i1 f, Y_inullX_i L_i. When X_i L_inullf, Y_inullX_i. Ynulli is computed from inull1 to inulln in ascending order.
Abstract:
A computer system for controlling a nonlinear physical process. The computer system comprises a linear controller and a neural network. The linear controller receives a command signal for control of the nonlinear physical process and a measured output signal from the output of the nonlinear physical process. The linear controller generates a control signal based on the command signal, a measured output signal, and a fixed linear model for the process. The neural network receives the control signal from the linear controller and the measured output signal from the output of the nonlinear physical process. The neural network uses the measured output signal to modify the connection weights of the neural network. The neural network also generates a modified control signal supplied to the linear controller to iterate a fixed point solution for the modified control signal used to control the nonlinear physical process.
Abstract:
Methods, apparatus and computer program products combine recursive least squares system identification operations and generalized predictive control operations to yield recursive generalized predictive control (RGPC) operations that can simultaneously achieve robust performance and robust stability characteristics. These RGPC operations can be applied in real-time without prior system (plant) information for control design because the operations for system identification are performed continuously. Moreover, the RGPC operations can be applied in the presence of changing operating environments because the control design is updated adaptively.
Abstract:
A control system for controlling a position of a mass, such as, for example, a substrate holder in a lithographic apparatus, is presented herein. The control system comprises a first input to receive a desired position of the mass, a second input signal to receive a feedback signal indicative of the actual position of the mass, a control unit that produces a signal indicative of the required control force based on the difference between the desired mass position and the actual mass position, and an estimator unit that calculates an estimated relation between the control force and mass status information indicative of at least one of a position of said mass, a velocity of said mass, and an acceleration of said mass, and a third input to receive a feed-forward signal indicative of the desired mass acceleration. The control system then determines the control force needed to accelerate the mass and move it to a desired position based on the estimated relation and the desired mass acceleration.
Abstract:
A method for identifying a control path of a controlled system, and more particularly to a method for identifying a control path in the presence of deterministic perturbations is described. At least one deterministic perturbation correcting signal is determined in a first identification process, and the perturbation correcting signal is stored in the form of a function. A control path of the controlled system is identified in a second identification process by adding to the controlled system the at least one stored deterministic perturbation correcting signal with a negative feedback. The method can be used with machine tools, production machines and/or robots which demand a high control accuracy and/or a high-quality control characteristic. In particular, perturbation effects due to slot latching in motors, in particular linear motors, can be minimized.
Abstract:
A system and method for tuning a raw mix proportioning controller used in a cement plant. A fuzzy logic supervisory controller tracks the performance of a cement plant simulator to target set points for attaining a correct mix and composition of raw materials. A genetic algorithm adjusts the fuzzy logic supervisory controller's performance by adjusting its parameters in a sequential order of significance.
Abstract:
An end-to-end process modeler comprising a vertically integrated process modeler to provide a design aspect for a non-technical user and an implementation aspect for a technical user, the vertically integrated process modeler designed to create a complete executable process.
Abstract:
An on-screen calibration system for disc drives and the operating method thereof. The calibration system includes an autocollimator detecting the inclined angle of the stage of a disc drive. A control module is connected to the on-screen display module and a bar code scanner to receive the bar code of the pick-up module and compute a predetermined position data. A monitor displays a moving point according to the inclined angle and a target point according to the predetermined position data through an on-screen display module. The tilt-adjusting mechanism supporting the pick-up module is adjusted to shift the moving point overlapping the target point.
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.