Abstract: This disclosure describes systems, methods, and apparatus for a plasma processing system. A method comprises receiving a reference signal defining target values for a parameter that is controlled at an output within the plasma processing system, obtaining a measure of the parameter that is controlled at the output, and calculating a delay between the target values of the setpoint signal and corresponding actual parameter values achieved at the output. The method also comprises providing, based upon the delay, a time-shifted amplitude error indicative of an error between the target values and the actual parameter values and adjusting at least one actuator, based upon the delay and the time-shifted amplitude error, in advance of when an actual parameter value is desired at an actuator output of the at least one actuator while maintaining the output within a threshold range.

Abstract: A generator and a method for controlling the generator are disclosed. The method comprises receiving a power sequence comprising a plurality of power states, creating a dynamic reference-time response within each state, and determining a dynamic average-delivered-power value within each state. An error signal is calculated within each state, and a controller output is produced using the error signal. An internal setpoint is produced based upon the error signal, and a power amplifier is controlled using the internal setpoint to control output power.

Abstract: An adaptive engine and a method of adaptive control are disclosed. The method comprises receiving an input regressor, where the input regressor comprises a reference signal, a system output measurement, and a control output. The method includes applying one or more estimation laws to the input regressor to estimate two or more sets of estimated model parameter tensors, ?; receiving two or more possible control signals; generating two or more estimated system outputs; and selecting a control signal from a set comprising at least the first possible control signal and the second possible control signal, or a combination of possible control signals blended from two or more of the sets.

Abstract: This disclosure describes systems, methods, and apparatus for a distributed controller. The distributed controller can include a traditional closed or open loop feedback controller followed by an empirically derived mapping that converts the controller output to a modified output, where the controller optimizes stability and the empirically derived mapping optimizes performance. The empirically derived mapping can be formed of coefficients representing linear controllers at inflection points, where the linear controllers are inversely related to a system model. The system model can comprise a static linear model, a dynamic linear model, and a total uncertainty. The static linear model can be derived from large signal steady state analysis, the dynamic nonlinear model can be derived from small signal transient analysis, and the uncertainty can be derived from small signal steady state analysis.

Abstract: An adaptive engine and adaptive control method. The method comprises receiving an input regressor and applying one or more estimation laws to the input regressor to estimate a plurality of estimated model parameter tensors for a nonlinear model. The method also includes computing an estimation error or a cost function using a system output measurement and an estimated system output for the previous iteration and determining a model order based at least in part on the estimation error or the cost function and receiving two or more possible control signals each using a corresponding control portion of the nonlinear model. In addition, the method includes generating two or more estimated system outputs each using a corresponding estimation portion of the nonlinear model and selecting a preferred control signal from a set comprising at least the two or more possible control signals or a preferred combination of possible control signals.

Abstract: This disclosure describes systems, methods, and apparatus for a selector and combiner of an adaptive engine. The adaptive engine can combinations of estimation and control laws to produce a multitude of possible control signals based on inputs such as a reference signal. A nonlinear model of the system can generate estimated system outputs for each of the possible controls signals. The selector and combiner can use the estimated system outputs to determine a best of the possible control signals, or a best combination of the possible control signals, such that the control approaches a desired measured output of the system.

Abstract: Fuzzy control systems and methods are disclosed. A method includes receiving a reference signal defining target values for a parameter that is controlled at an output of the plasma processing system and obtaining a measure of the parameter that is controlled at the output. A fuzzy controller provides a control signal to adjust at least one actuator based at least upon the reference signal and the measure of the controlled parameter. In addition, output membership functions of the fuzzy controller, input membership functions of the fuzzy controller, and a rule base of the fuzzy controller are adapted while controlling an output of a system based at least upon the based at least upon an estimated model parameter tensor, the reference signal and the measure of the controlled parameter, and the control signal.

Abstract: This disclosure describes systems, methods, and apparatus for an adaptive engine with a bifurcated nonlinear model. The adaptive controller uses a nonlinear model having a control portion and an estimation portion, wherein the estimation portion uses a time-varying linear system to approximate nonlinear behavior of the system. Further, the time-varying linear system receives a structure of the underlying matrices for every frame of control samples allowing the time-varying linear system to model large nonlinearities and to pre-process this linear approximation for each frame. At the same time, the time-varying linear system also uses estimated model parameter tensors in the underlying matrices that are updated or adapted every control cycle, in real-time, throughout a frame, such that the linear approximation is also able to approximate small nonlinearities in the system. This bifurcation of a linearized model provides a faster and more robust adaptive controller.

Abstract: An adaptive engine and method of adaptive control. The adaptive control method comprises receiving a reference signal, a system output measurement, and a control output. The method also includes applying one or more estimation laws to estimate an estimated model parameter tensor, ?, for a nonlinear model; generating a possible control signal or an internal possible control signal using a control portion of the nonlinear model; receiving a linear time varying system corresponding to the reference signal, and the possible control signal or the internal possible control signal; and generating one or more of a predicted system output and an estimated system output using an estimation portion of the nonlinear model.

Abstract: This disclosure describes systems, methods, and apparatus for an adaptive Lyapunov controller that can operate as a standalone controller for one or more actuators of a power system, or as one of a plurality of sub-engines in an adaptive controller. The controller or sub-engine can implement a control portion and an estimation portion of a nonlinear model of the one or more actuators and/or a power system controlled by the one or more actuators. The control portion can tensor multiply an input regressor, or partially filtered version thereof, and an estimated model parameter tensor, to produce a possible control signal. The estimation portion can apply a time-varying nonlinear system to the possible control signal to estimate an estimate system output corresponding to the possible control signal. These outputs may be used in a selection and combination process to produce a control based on one or more sub-engine outputs.

Abstract: An adaptive controller and method for adaptive control. The method comprises receiving a plurality of error signals and an input regressor, applying one or more estimation laws to the error signals and the input regressor to produce an estimated model parameter tensor, generating a plurality of subcomponents of a possible control signal, combining two or more subcomponents of the plurality of subcomponents of the possible control signal to produce the possible control signal, generating an estimated system output, and selecting a preferred control signal from a set comprising the possible control signals or a best combination of possible control signals blended from two or more possible control signals of the set.

Abstract: This disclosure describes systems, methods, and apparatus for estimation law modules of an adaptive engine. The estimation law modules estimate estimated model parameter tensors for each control sample within a frame. These estimated model parameter tensors are passed to control law modules and used to determine possible control signals as well as being passed to an estimation portion of a nonlinear model of the system, along with the possible control signals, to estimate estimated system outputs corresponding to each of the possible control signals. A selector module can then select a control as one of the possible control signals or a combination of two or more of the possible control signals, based on comparing the corresponding estimated system outputs to a reference signal, and/or measured system outputs.

Abstract: This disclosure describes systems, methods, and apparatus for an adaptive engine with a bifurcated nonlinear model partially represented by a mapping function. The adaptive engine uses a nonlinear model able to produce a possible control signal via a mapping function. The model also has estimation portion using a time-varying linear system to approximate nonlinear behavior of a power system. A boot up phase can be used wherein the mapping function provides possible control signals based on measured system outputs rather than an estimated model parameter tensor.

Abstract: This disclosure describes systems, methods, and apparatus for adjusting at least one actuator using at least one control output value to control a plasma processing system. More specifically, the controlling is based on receiving a reference signal defining target values for a parameter that is controlled at an output within the plasma processing system; obtaining a measure of the parameter, where the parameter is measured at a first sampling frequency; calculating one or more internal control signal values at a second sampling frequency; predicting, using an internal model, one or more internal measurements of the controlled parameter at the second sampling frequency; and adjusting, based upon the one or more control output values, at least one actuator at the first sampling frequency, where the control output values are based on the internal control signal values and the predicted internal measurements.

Abstract: This disclosure describes systems, methods, and apparatus for generating a control signal for one or more actuators that is adjusted from a control signal dictated by setpoints, where the adjustment accounts for predicted delays and amplitude errors. More specifically, cross correlation between measurements of the actuator(s) outputs and time-shifted setpoints can be optimized for a time-shift that minimizes the cross correlation. The time-shifted setpoints along with the measurements can then be used to determine an amplitude difference and to remove noise from the amplitude difference. Dynamic uncertainty can then be found from this denoised data set and further optionally used to find the noise that was removed. The time delay, noise, and dynamic uncertainty can be used to preemptively adjust the control signal.

Abstract: This disclosure describes systems, methods, and apparatus for a plasma processing system. A method comprises receiving a reference signal defining target values for a parameter that is controlled at an output within the plasma processing system, obtaining a measure of the parameter that is controlled at the output, and calculating a delay between the target values of the setpoint signal and corresponding actual parameter values achieved at the output. The method also comprises providing, based upon the delay, a time-shifted amplitude error indicative of an error between the target values and the actual parameter values and adjusting at least one actuator, based upon the delay and the time-shifted amplitude error, in advance of when an actual parameter value is desired at an actuator output of the at least one actuator while maintaining the output within a threshold range.

Abstract: This disclosure describes systems, methods, and apparatus for generating a multi-level pulsed waveform using a DC section and a power amplifier. To improve DC section efficiency, a master state is used to determine when the rail voltage can be lowered, and to only allow a state assigned as the master state to lower the rail voltage. Selection of the master state is based on (1) any state having to raise the rail voltage to meet a power demand or (2) a state having the highest drive voltage as determined at the end of each pulse cycle. Further, to avoid challenges from integrator controller, drive voltage is carried over from a last state of one pulse cycle to a first state of a next pulse cycle and assignment of master state in the first state of each pulse cycle is not important and can be arbitrarily selected.

Abstract: Various illustrative aspects are directed to a system that comprises a tensor data pre-processing circuit and a tensor data write/read circuit. One or more output ports of the tensor data pre-processing circuit are operably coupled to one or more input ports of the tensor data write/read circuit.

Abstract: Various illustrative aspects are directed to a system. The system comprises a setpoint waveform streaming progenitor module, configured to receive inputs indicative of a desired setpoint waveform, and to output a data package based at least in part on the inputs indicative of the desired setpoint waveform, wherein the data package comprises a plurality of points, an interpolation method, and one or more interpolation parameters. The system further comprises a setpoint waveform streaming processing module, configured to receive the data package from the setpoint waveform streaming progenitor module, and to output a streaming setpoint waveform based at least in part on the data package.

Abstract: A generator and a method for controlling the generator are disclosed. The method comprises receiving a power sequence comprising a plurality of power states, creating a dynamic reference-time response within each state, and determining a dynamic average-delivered-power value within each state. An error signal is calculated within each state, and a controller output is produced using the error signal. An internal setpoint is produced based upon the error signal, and a power amplifier is controlled using the internal setpoint to control output power.