Linestream Technologies

Cleveland State University

Danfoss Power Electronics A/s

Gang Tian

Zhiqiang Gao

Chris Knaack

Adam Reynolds

Ahmed H El-Shaer

Girish Yajurvedi

Ahmed El-Shaer

A system is disclosed for configuring a motor controller using a one-click configuration scheme, simplifying the process of motor configuration in drives and similar devices. The system includes a specify component, a display component, and a single-action identification and configuration component. The specify component specifies a motor in communication with the motor controller. The display component displays information on the status of the motor controller. The single-action identification and configuration component, in response to performance of only a single action (i.e., a single-click or equivalent starting signal), performs an identification and configuration sequence for the motor comprising at least three identification steps to establish a single parameter for driving the motor. The at least three identification steps can include measurements of system parameters, noise, and resonance. The recommend bandwidth for motor operation can be selected from within a range of permissible bandwidths.

One-click motor configuration

A field oriented control (FOC) system and method provides smooth field-oriented startup for three-phase sensorless permanent magnet synchronous motors (PMSMs) despite the absence of load information. The system uses the rotor flux projection on the d- or q-axis to determine whether the stator flux current reference being applied during reference startup phase is sufficient to spin the PMSM, thereby providing smooth operation during the reference startup phase and saving energy relative to applying rated current. The system also determines a suitable initial value for the stator torque current reference to use at the start of closed-loop sensorless FOC control mode based on an angle difference between the reference and estimated angles. Since this angle difference is reflective of the load on the PMSM, the selected initial value allows the system to achieve a smooth transition from reference startup mode to closed-loop sensorless FOC control mode.

Load-adaptive smooth startup method for sensorless field-oriented control of permanent magnet synchronous motors

A system parameter identification system uses a combination of relay control and sinusoidal injection to derive accurate estimates of system parameters of a controlled system or process while satisfying the rate-limit associated with some control applications. The system uses rate-limited relay control with hysteresis to place the system in oscillation. The system then switches the control signal from relay-based control to open-loop sinusoidal control using oscillation frequency, amplitude, and phase information obtained during the relay control stage. During the sinusoidal control phase, the plant output passes through a bandpass filter at the oscillation frequency to get a clean sinusoidal signal. The phase difference between the input and output signals and the output/input amplitude ratio are then obtained and used to calculate of the system parameters.

System parameter identificatino method based on rate-limited relay with hysteresis and sinusoidal injection

A motion control design system implements a performance specification-oriented design approach. The system allows a designer to define desired performance specifications that are to be satisfied by a motion system, and determines tuning parameters (e.g., controller bandwidth and associated tuning parameters) that will yield performance within the defined performance specifications. An identification process identifies system parameters of interest based on collected system data. After the user has entered the desired performance specifications, an optimization process determines a range of bandwidths that will satisfy all specified performance requirements, and selects an optimal bandwidth within this range. A tuning process generates the corresponding tuning parameters for a systematically designed motion controller. Rather than using an optimal solver, the design system stores relationships between performance specifications and the major tuning parameter as matrices or mapping functions, given system parameters as inputs, making the design system suitable for embedded systems.

Application-specification-oriented control design

As speed operation range identification system for motion systems driven by permanent magnet synchronous motors (PMSMs) or induction motors leverages both characteristics of the motor as well as dynamic characteristics of the motion system&#x2014;including the friction and load&#x2014;to identify suitable maximum speeds for operation of the motion system in the normal speed and field weakening regions. The identification system can model both motor characteristics as well as real-time dynamics of the controlled mechanical system that may vary during operation. The system can apply an optimization algorithm to this model to determine suitable maximum speeds for operation in the normal speed and/or field weakening regions. The determined maximum speeds can be used to perform substantially real-time adjustments to motion profile limits or current reference values generated by the motor controller in order to ensure that the speed of the system remains below the determined maximum.

Method for automatically identifying speed operation range in a mechanical system driven by PMSM or induction motors under friction and load condition

A resonance estimation system implements resonance detection methods that can obtain accurate estimates of a motion system's resonance and amplitude without the need for a high-resolution encoder or high-frequency sampling. The system solves for resonance information by removing the slow motion dynamics and fast torque control dynamics from the measured speed transfer function in order to obtain resonance transfer function. Smoothing functions are applied to the obtained resonance frequency response data to remove spikes and obtain relatively smooth gain and phase curves for the resonance frequency response. The system then applies a searching algorithm to determine the locations of the phase peaks in the phase curve data, and uses these phase peak locations to locate the gain peaks in the gain curve data, which correspond to the resonance frequencies and amplitudes. This approach allows the gain peaks to be located even when analyzing non-ideal gain curves that are degraded by noise.

Method for automatically identifying resonance

Systems and methods for estimating an inertia, a Coulomb friction coefficient, and a viscous friction coefficient for a controlled mechanical system are provided. In one or more embodiments, an inertia and friction estimation system can generate a torque command signal that varies continuously over time during a testing sequence. The velocity of a motion system in response to the time-varying torque command signal is measured and recorded during the testing sequence. The estimation system then estimates the inertia and the friction coefficients of the motion system based on the torque command data sent to the motion system and the measured velocity data. In some embodiments, the estimation system estimates the inertia and the friction coefficients based on integrals of the torque command data and the velocity data.

Method for automatically estimating inertia, coulomb friction, and viscous friction in a mechanical system

A curve fitting system implements a multi-level curve fitting approach to obtain a mapping between variables of interest. According to this approach, the system establishes first curve fitting relationships between a first variable of interest and a second variable of interest for sets of values of the independent variables. Then, second curve fitting relationships are established between the coefficients of the previously established curve fitting relationships and one of the independent variables for multiple value sets of the remaining independent variables. These recursive curve fitting operations are repeated until curve fitting relationships are obtained for all of the independent variables. The system then generates mapping data based on the curve fitting relationships, where the mapping data defines a mapping from the first independent variable to the second independent variable. This technique can be applied to determine functional relationships between tuning parameters and performance parameters of a motion system.

Multiple independent variable curve fitting method

A system for tuning a control system uses a simplified tuning procedure to generate robustly stabilizing tuning parameters that reduce or eliminate undesired system oscillations in the presence of long system dead times or phase lag. A control method is used to establish a relationship between the plant parameters of a controlled system and the tuning parameters of a parameterized active disturbance rejection controller determined to be optimal or substantially optimal for the control system. The plant parameters include the system gain, time constant, and dead time. Corresponding tuning parameters include the controller bandwidth and a system gain estimate. Using the system gain estimate as a tuning parameter can alleviate the influence of large dead times or phase lags on system response. Once established, these fixed relationships can be used to determine suitable tuning parameters for specific motion or process control applications based on the system gain and dominant constraints of the system.

Optimized parameterization of active disturbance rejection control

A maximum acceleration identification system determines a suitable maximum acceleration for transitioning a given motion/motor system to a target position or velocity, taking the friction of the motion system into consideration. The maximum acceleration determined by the maximum acceleration identification system can then be used by the motion control system as the acceleration limit for generating motion profiles. Thus, motion profiles can be generated that are closer to the true maximum acceleration supported by the motion system without violating the mechanical and electrical constraints of the system as characterized in part by the viscous friction, resulting in a more time-optimal move. In some embodiments, the maximum acceleration identification system can automatically set the maximum acceleration of the control system's profile generator to be equal to the derived value, thereby eliminating the need for the maximum acceleration to be selected and set by the system designer.

Automatic determination of maximum acceleration for motion profiles

Robustly stabilizing controller bandwidth for a controlled mechanical system is determined as a function of the system's estimated inertia and dominant system parameters that define constraints on the bandwidth. In one or more embodiments, a bandwidth model is derived that defines a relationship between robustly stabilizing controller bandwidth and system gain over a range of reasonable system uncertainties. Using the model, a suitable controller bandwidth can be determined for a given motion control system given only estimates of the system gain and the dominant parameters(s) that constrain the bandwidth. In an example two-inertia system, the system gain and dominant parameter can comprise system inertia and mechanical coupling stiffness, respectively. Accordingly, estimates of the system inertia and coupling stiffness can be provided to the system, which determines a suitable controller bandwidth for the motion control system characterized by the estimates.

Method for automatically setting responsiveness parameters for motion control systems

Multiple designs, systems, methods and processes for controlling a system or plant using an extended active disturbance rejection control (ADRC) based controller are presented. The extended ADRC controller accepts sensor information from the plant. The sensor information is used in conjunction with an extended state observer in combination with a predictor that estimates and predicts the current state of the plant and a co-joined estimate of the system disturbances and system dynamics. The extended state observer estimates and predictions are used in conjunction with a control law that generates an input to the system based in part on the extended state observer estimates and predictions as well as a desired trajectory for the plant to follow.

Extended active disturbance rejection controller

Systems and methods for estimating an inertia and a friction coefficient for a controlled mechanical system are provided. In one or more embodiments, an inertia estimator can generate a torque command signal that varies continuously over time during a testing sequence. The velocity of a motion system in response to the time-varying torque command signal is measured and recorded during the testing sequence. The inertia estimator then estimates the inertia and/or the friction coefficient of the motion system based on the torque command data sent to the motion system and the measured velocity data. In some embodiments, the inertia estimator estimates the inertia and the friction coefficient based on integrals of the torque command data and the velocity data.

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Westlake, OH, United States of America

Gang Tian