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Advancements in machining technology demand higher speeds and precision, necessitating improved control systems in equipment like CNC machine tools. Due to lead errors, structural vibrations, and thermal deformation, commercial CNC controllers commonly use rotary encoders in the motor side to close the position loop, aiming to prevent insufficient stability and premature wear and damage of components. This paper introduces a multivariable iterative learning control (MILC) method tailored for flexible feed drive systems, focusing on enhancing dynamic positioning accuracy. The MILC employs error data from both the motor and table sides, enhancing precision by injecting compensation commands into both the reference trajectory and control command through a norm-optimization process. This method effectively mitigates conflicts between feedback control (FBC) and traditional iterative learning control (ILC) in flexible structures, achieving smaller tracking errors in the table side. The performance and efficacy of the MILC system are experimentally validated on an industrial biaxial CNC machine tool, demonstrating its potential for precision control in modern machining equipment. [ABSTRACT FROM AUTHOR]

The motion of nonholonomic mobile manipulators (NMMs) is inherently constrained by joint limits, joint velocity limits, self-collisions and singularities. Most motion planning algorithms consider some of the aforementioned constraints, however, a unified framework to deal with all of them is lacking. This paper proposes a motion planning solution for the kinematic trajectory tracking of redundant NMMs that include all the constraints needed for practical implementation, which improves the manipulability of both the entire system and the manipulator to prevent singularities. Experiments using a 10-DOF NMM demonstrate the good performance of the proposed method for executing 6-DOF trajectories while satisfying all the constraints and simultaneously maximizing manipulability. [ABSTRACT FROM AUTHOR]

In this article, we aim to achieve manual guidance of a robot manipulator to perform tasks that require strict path following and would benefit from collaboration with a human to guide the motion. The robot can be used as a tool to increase the accuracy of a human operator while remaining compliant with the human instructions. We propose a dual-loop control structure where the outer admittance control loop allows the robot to be compliant along a path considering the projection of the external force to the tangential-normal-binormal (TNB) frame associated with the path. The inner motion control loop is designed based on a modified sliding mode control (SMC) law. We evaluate the system behavior to forces applied from different directions to the end-effector of a 6-DOF industrial robot in a linear motion test. Next, a second test using a 3D path as a tracking task is conducted, where we specify three interaction types: free motion (FM), force-applied motion (FAM), and combined motion with virtual forces (CVF). Results show that the difference of root mean square error (RMSE) among the cases is less than 0.1 mm, which proves the feasibility of applying this method for various path-tracking applications in compliant human–robot collaboration. [ABSTRACT FROM AUTHOR]

Slip-ratio-based methods are commonly used to control the wheel torque such that the wheel dynamics is stabilized and the desired traction/braking force is attained; however, slip-ratio-based controllers are incompetent for precise longitudinal tire force tracking due to nonparametric tire model uncertainties. Force tracking performance further deteriorates whenever the tire is under combined longitudinal and lateral motion. In this paper, we propose an observer-based tire force control scheme that guarantees to achieve the desired longitudinal tire force accurately and robustly with respect to tire model uncertainties, changes in road conditions, and simultaneous lateral motion. Convergence of the force estimation and tracking errors is rigorously proved by the Lyapunov method. Then, simulations are conducted to verify the robust and accurate performance in longitudinal tire force estimation and tracking under a series of severe driving conditions. [ABSTRACT FROM PUBLISHER]

Most manipulator motion controllers require joint velocity feedback. Whenever joint velocities are not measurable, they are estimated from the joint positions. However, ve-locity estimates tend to be inaccurate under low-speed motion or low sensor resolution conditions. Moreover, velocity estimators may either be susceptible to model uncertain-ties or introduce additional dynamics (e.g., phase lag) to the control loop. Consequently, direct substitution of velocity estimates into the controller results in the deterioration of the control peiformance and robustness margin. Therefore, this paper proposes a robust position-feedback motion controller which gets rid of the problems of uncompensated dy-namics and model uncertainties introduced by velocity estimators. Furthermore, a glob-ally asymptotically stable system, which is robust with respective to model parameter variations, is guaranteed. Theoretical analysis and experimental verifications are carried out. The results demonstrate that the proposed controller is robust and outperforms the conventional computed torque plus proportional integral differential (PID) controller. [ABSTRACT FROM AUTHOR]

Due to increasingly demanding requirements for driving safety, precise and robust control of tire traction forces is essential to implement high-performance vehicle-control systems. However, traditional slip-ratio-based methods cannot guarantee achievement of desired traction forces due to a lack of tire force feedback. This paper proposes an observer-based traction force control scheme that is robust with respect to variations of road conditions and tire model uncertainties. Moreover, achievement of desired traction forces is guaranteed. Simulation results verify the robust and satisfactory performance, even under suddenly changing road conditions, as well as parametric and nonparametric tire model uncertainties. [ABSTRACT FROM PUBLISHER]

Active noise cancellation in ducts using multiple feedforward sensors have been investigated by many researchers. When adaptive algorithms were applied, usually a lumped parameter model was assumed and the model includes the dynamics of the duct, sensors and actuators (e.g., microphone and loudspeaker). The distributed nature of the duct usually leads to a large parameter space and is difficult to implement direct adaptive control. This brief presents a control architecture which separates the duct's dynamics from those of sensors and actuators. An adaptive control algorithm is proposed to cope with the unknown dynamics of sensors and actuators. Experiments were conducted to show the effectiveness of the control law. [ABSTRACT FROM AUTHOR]

Lower-limb exoskeletons as walking assistive devices have been intensively investigated in recent decades. In these studies, intention detection and performance evaluation are important topics. In our previous studies, we proposed a disturbance observer (DOB)-based torque estimation algorithm and an admittance control law to shape the admittance of the human-exoskeleton system (HES) and comply with the user's walking intention. These algorithms have been experimentally verified under the condition of no ground reaction force (GRF) in our previous studies. In this paper, we devised and integrated with the exoskeleton control system a sensing and communication module on each foot to measure and compensate for GRF. Rigorous theoretical analysis was performed and the sufficient conditions for the robust stability of the closed-loop system were derived. Then, we conducted level ground assistive walking repeatedly with different test subjects and exhaustive combinations of admittance parameters. In addition, we proposed two tractable and physically insightful performance indices called normalized energy consumption index (NECI) and walking distance in a fixed period of time to quantitatively evaluate the performance for different admittance parameters. We also compared the energy consumption for users walking with and without the exoskeleton. The results show that the proposed admittance control law reduces the energy consumption of the user during level ground walking. [ABSTRACT FROM AUTHOR]