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Considers the use of dBASE to combine SaveScreen output with OCLC software to produce custom reports. Discusses the problems with the two report programs, ILLSORT and ILLCOUNT, processing with ILLFILE, transfer into dBASE, reporting by dBASE, and archiving dBASE records.

This paper aims to discuss the precise altitude and velocity tracking control of a hypersonic vehicle, a global adaptive neural backstepping controller was studied based on a disturbance observer (DOB).

The DOB combined with a radial basis function (RBF) neural network (NN) was used to estimate the disturbance terms that are generated by the flexible modes of the hypersonic vehicle system. A global adaptive neural method was introduced to approximate the unknown system dynamics, with robust control terms pulling the system transient states back into the neural approximation domain externally.

The globally uniformly ultimately bounded for all signals of a closed-loop system can be guaranteed by the proposed control algorithm. Additionally, the command filtered backstepping methods can avoid the explosion of the complexity problem caused by the backstepping design process. In addition, the effectiveness of the proposed controller can be verified by the simulation used in this study.

Normally lateral dynamics issue should be discussed in the process of control system designed, the lateral dynamics are not included in the nonlinear dynamic model of hypersonic vehicle used in this paper, merely the longitudinal flight dynamics are discussed in this paper.

The flexible states in rigid modes are considered as the disturbance of the system, which is estimated by structuring DOB with NN approximations. The compensating tracking error and prediction error are used in the update law of RBF NN weight. The differential explosions complexity derived from the backstepping procedure is dealt with by using command filters.

Robonaut is a humanoid robot designed by the Robotic Systems Technology Branch at NASA's Johnson Space Center in a collaborative effort with Defense Advanced Research Projects Agency. This paper describes the implementation of haptic feedback into Robonaut and Robosim, the computer simulation of Robotonaut. In the first experiment, we measured the effects of varying feedback to a teleoperator during a handrail grasp task. Second, we conducted a teleoperated task, inserting a flexible beam into an instrumented receptacle. In the third experiment, we used Robonaut to perform a two‐arm task where a compliant ball was translated in the robot's workspace. The experimental results are encouraging as the Dexterous Robotics Lab continues to implement force feedback into its teleoperator hardware architecture.

The purpose of this paper is to investigate limit cycles in digitally Proportional, Integral and Derivative (PID) controlled buck regulators. Filtering is examined as a means of removing the limit cycles in digitally controlled buck regulators.

The paper explains why limit cycles occur in a digitally PID controlled buck converter. It then proceeds to propose two filters for their elimination. Results indicate the effectiveness of each of the filters.

The paper gives a mathematical analysis of the occurrence of limit cycles in digitally controlled PID buck regulators. It finds that notch and comb filters are effective for the purpose of eliminating limit cycles in buck regulators.

The paper employs a model of the buck regulator inclusive of the inductor loss – this was not done to date for this type of work. The paper analyses PID control. This was not done in the manner given. The paper addresses filtering as a means of removing limit cycles. It examines the effect of changing the digital controller parameters on the requirements of the filters.

There has been a massive investment in the installation of online catalogs: in selection, in the supporting infrastructure of terminals and networks, in catalog record conversion, in training, and, lately, in linking online catalogs with other online systems. In contrast, the state‐of‐the‐art of the functionality of online library catalogs has advanced little in the past few years. Rather it has been a matter of existing systems being upgraded towards the functionality of the better systems and of refinements being added. It is time for a further advance in online catalog design. We believe that the next generation of online catalogs should and will have features such as those discussed and illustrated in this article.

The purpose of this paper is to design a new trajectory error compensation method to improve the trajectory tracking performance and compliance of the knee exoskeleton in human–exoskeleton interaction motion.

A trajectory error compensation method based on admittance-extended Kalman filter (AEKF) error fusion for human–exoskeleton interaction control. The admittance controller is used to calculate the trajectory error adjustment through the feedback human–exoskeleton interaction force, and the actual trajectory error is obtained through the encoder feedback of exoskeleton and the designed trajectory. By using the fusion and prediction characteristics of EKF, the calculated trajectory error adjustment and the actual error are fused to obtain a new trajectory error compensation, which is feedback to the knee exoskeleton controller. This method is designed to be capable of improving the trajectory tracking performance of the knee exoskeleton and enhancing the compliance of knee exoskeleton interaction.

Six volunteers conducted comparative experiments on four different motion frequencies. The experimental results show that this method can effectively improve the trajectory tracking performance and compliance of the knee exoskeleton in human–exoskeleton interaction.

The AEKF method first uses the data fusion idea to fuse the estimated error with measurement errors, obtaining more accurate trajectory error compensation for the knee exoskeleton motion control. This work provides great benefits for the trajectory tracking performance and compliance of lower limb exoskeletons in human–exoskeleton interaction movements.

This paper seeks to present a feedback error learning neuro‐controller for an unstable research helicopter.

Three neural‐aided flight controllers are designed to satisfy the ADS‐33 handling qualities specifications in pitch, roll and yaw axes. The proposed controller scheme is based on feedback error learning strategy in which the outer loop neural controller enhances the inner loop conventional controller by compensating for unknown non‐linearity and parameter uncertainties. The basic building block of the neuro‐controller is a nonlinear auto regressive exogenous (NARX) input neural network. For each neural controller, the parameter update rule is derived using Lyapunov‐like synthesis. An offline finite time training is used to provide asymptotic stability and on‐line learning strategy is employed to handle parameter uncertainty and nonlinearity.

The theoretical results are validated using simulation studies based on a nonlinear six degree‐of‐freedom helicopter undergoing an agile maneuver. The neural controller performs well in disturbance rejection is the presence of gust and sensor noise.

The neuro‐control approach presented in this paper is well suited to unmanned and small‐scale helicopters.

The study shows that the neuro‐controller meets the requirements of ADS‐33 handling qualities specifications of a helicopter.

This paper aims to propose and verify an improved cascade active disturbance rejection control (ADRC) scheme based on output redefinition for hypersonic vehicles (HSVs) with nonminimum phase characteristic and model uncertainties.

To handle the nonminimum phase characteristic, a tuning factor stabilizing internal dynamics is introduced to redefine the system output states; its effective range is determined by analyzing Byrnes–Isidori normalized form of the redefined system. The extended state observers (ESOs) are used to estimate the uncertainties, which include matched and mismatched items in the system. The controller compensates observations in real time and appends integral terms to improve robustness against the estimation errors of ESOs.

Theoretical and simulation results show that the stability of internal dynamics is guaranteed by the tuning factor and the tracking errors of external commands are globally asymptotically stable.

The control scheme in this paper is expected to generate a reliable way for dealing with nonminimum phase characteristic and model uncertainties of HSVs.

In the framework of ADRC, a concise form of redefined outputs is proposed, in which the tuning factor performs a decisive role in stabilizing the internal dynamics of HSVs. By introducing an integral term into the cascade ADRC scheme, the compensation accuracy of matched and mismatched disturbances is improved.

This study presents a method for simultaneous motion and vibration control of light-weight slender robotic arms, known as flexible manipulators. In this paper, a new control algorithm is proposed for a two-link manipulator with elastic links.

The controller includes a MIMO H∞ Loop-Shaping Design (H∞LSD) as the feedback controller, and a command pre-shaping filter as the feed-forward controller. The conventional inputs and outputs of a typical two-link manipulator , that consists of the torques applied by the actuators at the joints, and the joint angles are chosen for the feedback control.

It is shown that by selecting a proper desired loop shape, the H∞LSD is able to control the joint angles of the manipulator, and simultaneously, suppress vibrations of the system so that the high frequency chatter due to the structural vibration modes does not appear at the outputs. Then it is shown that when the H∞LSD is equipped with a command pre-shaping filter, more efficient suppression of the chatter at the tip of the manipulator is achieved. The capability and effectiveness of the proposed control strategy in driving and stabilizing the manipulator to desired positions and simultaneously suppressing structural vibrations is shown by the simulation of the flexible manipulator in rest-to-rest maneuvers.

Flexible Manipulator, Space Manipulators

A robust MIMO controller is proposed for simultaneous motion and vibration control of flexible manipulator.

The purpose of this paper is to present a surgical robot for spinal fusion and its control framework that provides higher operation accuracy, greater flexibility of robot position control, and improved ergonomics.

A human‐guided robot for the spinal fusion surgery has been developed with a dexterous end‐effector that is capable of high‐speed drilling for cortical layer gimleting and tele‐operated insertion of screws into the vertebrae. The end‐effector is position‐controlled by a five degrees‐of‐freedom robot body that has a kinematically closed structure to withstand strong reaction force occurring in the surgery. The robot also allows the surgeon to control cooperatively the position and orientation of the end‐effector in order to provide maximum flexibility in exploiting his or her expertise. Also incorporated for improved safety is a “drill‐by‐wire” mechanism wherein a screw is tele‐drilled by the surgeon in a mechanically decoupled master/slave system. Finally, a torque‐rendering algorithm that adds synthetic open‐loop high‐frequency components on feedback torque increases the realism of tele‐drilling in the screw‐by‐wire mechanism.

Experimental results indicated that this assistive robot for spinal fusion performs drilling tasks within the static regulation errors less than 0.1 μm for position control and less than 0.05° for orientation control. The users of the tele‐drilling reported subjectively that they experienced torque feedback similar to that of direct screw insertion.

Although the robotic surgery system itself has been developed, integration with surgery planning and tracking systems is ongoing. Thus, the screw insertion accuracy of a whole surgery system with the assistive robot is to be investigated in the near future.

The paper arguably pioneers the dexterous end‐effector appropriately designed for spinal fusion, the cooperative robot position‐control algorithm, the screw‐by‐wire mechanism for indirect screw insertion, and the torque‐rendering algorithm for more realistic torque feedback. In particular, the system has the potential of circumventing the screw‐loosening problem, a common defect in the conventional surgeon‐operated or robot‐assisted spinal fusion surgery.