Torsten Bertram

Modeling and Identification of Elastic Robot Joints With Hysteresis and Backlash

This paper presents a novel approach to the modeling and identification of elastic robot joints with hysteresis and backlash. The model captures the dynamic behavior of a rigid robotic manipulator with elastic joints. The model includes electromechanical submodels of the motor and gear from which the relationship between the applied torque and the joint torsion is identified. The friction behavior in both presliding and sliding regimes is captured by generalized Maxwell-slip model. The hysteresis is described by a Preisach operator. The distributed model parameters are identified from experimental data obtained from internal system signals and external angular encoder mounted to the second joint of a 6-DOF industrial robot. The validity of the identified model is confirmed by the agreement of its prediction with independent experimental data not previously used for model identification. The obtained models open an avenue for future advanced high-precision control of robotic manipulator dynamics.

Emergency path planning for autonomous vehicles using elastic band theory

In this paper a path planning method for emergency maneuvers of autonomous vehicles is presented. The path planning method is based on the theory of elastic bands. Due to the local disturbances caused by obstacles on the nominal trajectory the elastic behavior allows sufficient flexibility of the emergency trajectory and minimal local changes of curvature. The minimization of local changes of curvature ensures the drivability of the emergency trajectory under vehicle dynamics aspect, which is also considered in this paper. The results of the described method is demonstrated for emergency situations in lane change maneuvers for autonomous vehicles.

Use of Jiles–Atherton and Preisach Hysteresis Models for Inverse Feed-Forward Control

Hysteresis effects hinder the accurate control of electromagnetic actuators and require auxiliary sensors for properly determining the hysteretic system state. The physics-based Jiles-Atherton and the phenomenological Preisach hysteresis models provide powerful means to describe the magnetic hysteresis and its inverse. In this paper, we consider both hysteresis models in the scalar form from the control points of view, with a primary objective of the sensorless inverse feed-forward control. The identification complexity, the runtime, and the space efficiency of the control-oriented implementation are analyzed and compared for both modeling approaches. Their control performance for an inverse hysteresis compensation is experimentally evaluated on a specific force-controlled electromagnet system.

Track-to-Track Fusion With Asynchronous Sensors Using Information Matrix Fusion for Surround Environment Perception

Driver-assistance systems and automated driving applications in the future will require reliable and flexible surround environment perception. Sensor data fusion is typically used to increase reliability and the observable field of view. In this paper, a novel approach to track-to-track fusion in a high-level sensor data fusion architecture for automotive surround environment perception using information matrix fusion (IMF) is presented. It is shown that IMF produces the same good accuracy in state estimation as a low-level centralized Kalman filter, which is widely known to be the most accurate method of fusion. Additionally, as opposed to state-of-the-art track-to-track fusion algorithms, the presented approach guarantees a globally maintained track over time as an object passes in and out of the field of view of several sensors, as required in surround environment perception. As opposed to the often-used cascaded Kalman filter for track-to-track fusion, it is shown that the IMF algorithm has a smaller error and maintains consistency in the state estimation. The proposed approach using IMF is compared with other track-to-track fusion algorithms in simulation and is shown to perform well using real sensor data in a prototype vehicle with a 12-sensor configuration for surround environment perception in highly automated driving applications.

Attitude estimation and control of a quadrocopter

The research interest in unmanned aerial vehicles (UAV) has grown rapidly over the past decade. UAV applications range from purely scientific over civil to military. Technical advances in sensor and signal processing technologies enable the design of light weight and economic airborne platforms. This paper presents a complete mechatronic design process of a quadrotor UAV, including mechanical design, modeling of quadrotor and actuator dynamics and attitude stabilization control. Robust attitude estimation is achieved by fusion of low-cost MEMS accelerometer and gyroscope signals with a Kalman filter. Experiments with a gimbal mounted quadrotor testbed allow a quantitative analysis and comparision of the PID and Integral-Backstepping (IB) controller design for attitude stabilization with respect to reference signal tracking, disturbance rejection and robustness.

Optimal State Space Control of DC Motor

Abstract In comparison to classical cascade control architecture of DC motors, the state feedback control offers advantages in terms of design complexity, hardware realization and adaptivity. This paper presents a methodic approach to state space control of a DC motor. The state space model identified from experimental data provides the basis for a linear quadratic regulator (LQR) design. The state feedback linear control is augmented with a feedforward control for compensation of Coulomb friction. The controller is successfully applied and the closed loop behavior is evaluated on the experimental testbed under various reference signals.

Observer-Based Compensation of Additive Periodic Torque Disturbances in Permanent Magnet Motors

The impact of additive periodic torque disturbances on the controlled motion of permanent magnet motors can be significant. The paper shows how an observer-based drive control can efficiently reject the harmonic torque disturbances providing smooth angular velocity. The proposed control design is based on the state-space torque harmonics representation and Luenberger observer that proved to be adequate. The designed control algorithms are verified using an experimental setup with a permanent magnet synchronous motor with well-detectable torque harmonics. The rejection of additive position periodic torque disturbances is experimentally demonstrated for two first harmonics and that for different angular velocities.

Discrete dynamic Preisach model for robust inverse control of hysteresis systems

Hysteresis effects are present in diverse systems including structural mechanics, tribology, and electromagnetism. Hysteresis systems are generally known as exhibiting a memory effect which aggravates their accurate prediction and control. The classical Preisach model provides powerful means to describe arbitrary hysteresis with rate-independent behavior. In this paper, we address the problem of the robust inverse control of hysteresis systems while presenting a novel formulation of the discrete dynamic Preisach model and its inverse. The control-oriented features, among the advanced computational efficiency and the handling of hysteresis uncertainties are shown and discussed. The properly developed inverse hysteresis control is augmented by an auxiliary disturbance observer which captures uncertainties of the modeled hysteresis and its time-variant behavior. The performance of the proposed observer based control strategy is compared with a standard feedback of the controlled hysteretic value. The proposed approach is experimentally evaluated for linearizing the torsional hysteresis compliance. Providing an universal character the method is suitable for a broad class of hysteresis systems independent of the source and form of underlying hysteresis.

Control of Magnetic Shape Memory Actuators Using Observer-Based Inverse Hysteresis Approach

Magnetic shape memory (MSM) actuators belong to active material technologies with a high energy density and outstanding field-strain relation. Large-scale multivariate field-stress-strain hysteresis effects, however, antagonize their broad use because of the inherent difficulties with control. In this brief, we describe and compare experimentally several MSM control strategies, including the observer-based inverse hysteresis approach proposed in the previous works and combined here with a linear feedback controller by connecting both in parallel. For a prototypic MSM actuator with return spring, it is shown that the actuator plant can be approximated by an appropriate hysteresis operator and a linear transfer function of residual dynamics. The positioning profiles with a bandwidth 0.1-10 Hz and amplitudes between 0.01 and 0.1 mm have been evaluated by the experiments.

Modified Maxwell-slip Model of Presliding Friction

Abstract The distributed Maxwell-slip model provides a convenient way to describe the presliding friction behavior. The modified single-state Maxwell-slip (MMS) model is proposed with the main benefit to require two concentrated parameters only when describing the smooth hysteresis of the presliding friction. The model is rate-independent at both, saturated and unsaturated hysteresis, and is consistent with the generalized empirical friction model structure. Some novel perceptions on the frictional memory and drift are considered and proved in experiments. The evaluation performed on an actuator system with multiple coupled frictional surfaces reveals the proposed model as easily identifiable and accurate in prediction.