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This paper presents a physically intuitive method for altering a vehicle's handling characteristics through active steering intervention. A full state feedback controller augments the driver's steering command via steer-by-wire to achieve desired handling behavior. Accurate estimates of vehicle states are available from a combination of Global Positioning System (GPS) and Inertial Navigation System (INS) sensor measurements. By canceling the effects of steering system dynamics and tire disturbance forces, the steerby-wire system is able to track commanded steer angle with minimal error. Experimental results verify that with precise steering control and accurate state information, a vehicle's handling characteristics can be modified to match driver preference or to compensate for changes in operating conditions.

This paper demonstrates a method of estimating several key vehicle states—sideslip angle, longitudinal velocity, roll and grade—by combining automotive grade inertial sensors with a Global Positioning System (GPS) receiver. Kinematic Kalman filters that are independent of uncertain vehicle parameters integrate the inertial sensors with GPS to provide high update estimates of the vehicle states and the sensor biases. Using a two-antenna GPS system, the effects of pitch and roll on the measurements can be quantified and are demonstrated to be quite significant in sideslip angle estimation. Employing the same GPS system as an input to the estimator, this paper develops a method that compensates for roll and pitch effects to improve the accuracy of the vehicle state and sensor bias estimates. In addition, calibration procedures for the sensitivity and cross-coupling of inertial sensors are provided to further reduce measurement error. The resulting state estimates compare well to the results from calibrated models and Kalman filter predictions and are clean enough to use in vehicle dynamics control systems without additional filtering.

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This paper presents a reconfigurable ankle rehabilitation robot to cover various rehabilitation exercise modes. The designed robot can allow desired ankle and foot motions, including toe and heel raising as well as traditional ankle rotations, since the mechanism can generate relative rotation between the fore and rear platforms as well as pitch and roll motions. In addition, the robotic device can be reconfigured from a range of motion ͑ROM͒/strengthening exercise device to a balance/proprioception exercise device by simply incorporating an additional plate. Further, the action of the device is twofold in the sense that while a patient's foot is fastened firmly to the ROM/strengthening device for task specific training, that person can also stand on the balance/proproception device. To perform each mode of ROM, strengthening, and proproception exercises, a unified position-based impedance control is systematically developed taking into account the desired position and velocity.

Stability is a challenging issue when controlling haptic interaction systems because unstable behavior may injure human operators or deteriorate the realism of the provided cues. Based on the passivity condition for sampled-data haptic systems, we propose a novel energy-bounding algorithm to ensure robustly stable haptic interactions. The proposed algorithm limits the energy generated by a sample-and-hold operator within the energy consumable by the effective damping elements in the haptic system. The algorithm also ensures that the VE and controller are passive. This guarantees robustly stable haptic interactions, regardless of the sampling frequency and its variations, but compromises the displayable impedance range of the VE. Simulations and experiments using a commercial haptic device are used to demonstrate the effectiveness of the proposed algorithm.KEY WORDS-haptics1 passivity1 sampled-data system1 stability.

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