P. Vedagarbha

Tracking control of mechanical systems in the presence of nonlinear dynamic friction effects

In this paper, we design an observer-based exact model knowledge position tracking controller for a second-order mechanical system with nonlinear load dynamics and a nonlinear dynamic friction model. Since the controller requires an estimate of the unmeasurable friction state, we demonstrate how the friction dynamics can be exploited to design three different observers which foster different transient response characteristics for the composite closed-loop system. We then present two adaptive controllers which utilize nonlinear observer/filter structures to provide for asymptotic position tracking while compensating for selected parametric uncertainty. Dynamic simulation and experimental results are utilized to illustrate control performance.

A redesigned DCAL controller without velocity measurements: theory and demonstration

A link position tracking controller is formulated for an n-link, rigid, revolute, serially-connected robot. The controller generates torque commands to the individual robot links based on adaptive estimates of the system parameters and measurements of only link positions. A filtering technique, based on the link position signal, is used to alleviate the need for velocity measurements. A complete development of the controller is presented along with a proof of semiglobal asymptotic link position-velocity tracking performance. Experimental validation of the proposed controller on the Integrated Motion Inc. (IMI) two-link direct drive robot is also presented. Several extensions to the basic controller are described that consider the use of fixed parameter estimates.

Adaptive control techniques forfrictioncompensation

Abstract In this paper, we design two adaptive controllers for a second-ordermechanicalsystem which incorporates frictional effects such as Coulomb, static, Stribeck, andviscousfriction. First, we design a modular position tracking controller that can accommodate avarietyof adaptive update laws. The proposed controller is shown to compensate foruncertaintyassociated with the friction parameters which appear linearly in the model. In thesecond controlscheme, we show how a Lyapunov-based adaptive position setpoint controller canbe designed tocompensate for parametric uncertainty throughout the mechanical systemincluding the Stribeckeffect related constant which does not appear linearly in the model.Experimental results areprovided to illustrate the performance of the proposed controllers.

Boundary control of a cantilevered flexible beam with point-mass dynamics at the free end☆

In this paper, we develop boundary controllers for a cantilevered Euler-Bernoulli beam with point-mass dynamics at the free end. Specifically, we develop an exact model knowledge controller which exponentially stabilizes the beam displacement and an adaptive controller which asymptotically stabilizes the beam displacement. Experimental results are utilized to validate the performance of the controllers.

Adaptive control techniques for friction compensation

We design two adaptive controllers for a second-order mechanical system which incorporates frictional effects such as Coulomb, static, Stribeck, and viscous friction. First, we design a modular position tracking controller that can accommodate a variety of adaptive update laws. The proposed controller is shown to compensate for uncertainty associated with the friction parameters which appear linearly in the model. In the second control scheme, we show how a Lyapunov-based adaptive position setpoint controller can be designed to compensate for parametric uncertainty throughout the mechanical system including the Stribeck effect related constant which does not appear linearly in the model. Experimental results are provided to illustrate the performance of the proposed controllers.

An adaptive controller for a class of induction motor systems

In this paper, we present an adaptive, partial-state feedback, position/velocity tracking controller for the full-order, nonlinear dynamic model representing an induction motor actuating a mechanical subsystem. The proposed controller compensates for parametric uncertainty in the mechanical subsystem while yielding global asymptotic rotor position/velocity tracking. The proposed controller does not require measurement of rotor flux or rotor current; furthermore, the controller does not exhibit any singularities. Experimental results are provided to verify the effectiveness of the approach.

Non-linear adaptive control of induction motors

Given measurements of rotor position, rotor velocity, and stator currents, we design an adaptive control scheme that is free of singularities, does not require rotor flux measurements, and provides for simultaneous asymptotic rotor position/rotor flux tracking despite the uncertainty associated with the mechanical subsystem parameters and the rotor resistance parameter. For the case when the rotor resistance parameter is known exactly, we modify the structure of the controller to achieve global asymptotic rotor position/rotor flux tracking while accommodating for parameter uncertainty associated with the mechanical subsystem parameters and the stator electrical subsystem parameters. Experimental results are presented to illustrate the performance of the control structure. Copyright

Advanced motion control of mechatronic systems via a high-speed dsp and a parallel processing transputer network

A system for implementing an advanced motion controller using a floating-point digital signal processor (DSP) and a transputer-based parallel processing system is presented. The discussion includes a brief look at the advantages of using DSPs in real-time control applications and the architecture for integrating DSPs with parallel processing transputer networks to enhance computing power. The main focus of this paper is on the design of a system that combines the Texas Instruments TMS320C30 floating-point DSP with a parallel processing system based on Intel i860 RISC processors and Inmos transputers to achieve excellent real-time response and superior computational power. The software of the system is hosted in the popular MATLAB program which furnishes a simple user interface and programming environment. The system is ideal for implementing advanced motion control experiments that require high-speed floating-point computations as well as fast sampling rates. In addition to real-time experiment, the system also includes a simulation package to allow rapid verification of the users program and control algorithm. A complex adaptive motor control experiment is presented to illustrate the application of the system.

Experimental verification of adaptive and robust trajectory tracking controllers for switched reluctance rotors

Integrator backstepping design techniques have previously been used to develop voltage level control algorithms for various classes of electric machines. The resulting control algorithms yield rigorous stability results that are attractive for motor drive applications for several reasons: (i) they can compensate for typically neglected electrical dynamics associated with the motor drive system, (2) they can compensate for a variety of uncertainties throughout the entire drive system (i.e., both modeled and unmodeled electromechanical dynamics), and (3) they can be designed to operate with only partial state measurements (i.e., sensorless control). Despite this promising outlook, few backstepping based algorithms have been experimentally verified, primarily due to their recent theoretical emergence. This paper examines two backstepping based algorithms for switched reluctance (SR) machines which use full-state measurements (i.e., motor position, velocity, and per phase winding currents), to yield rigorous theoretical stability results on the rotor trajectory tracking error despite uncertainty in the SR motor drive system. The controllers incorporate a smooth commutation strategy for the shared specification of the individual SR phase currents. The proposed controllers are experimentally verified using a digital signal processor based data acquisition and control system, and the performance results compared to a backstepping based, exact model knowledge control algorithm.<<ETX>>

An adaptive controller for a general class of switched reluctance motor models

In this paper, we utilize a general, nonlinear model of the switched reluctance (SR) motor to develop an adaptive controller for the full-order electromechanical model. The proposed controller requires measurement of the rotor position, rotor velocity, and stator current, does not exhibit any control singularities, achieves global asymptotic position/velocity tracking, and compensates for uncertain electromechanical parameters which are independent of the flux linkage model. To illustrate the generality of the approach, we show how the control can be designed to account for magnetic saturation associated with a proposed flux linkage model. Experimental results are also provided.