A New 4-DOF Robot for Rehabilitation of Knee and Ankle-Foot Complex: Simulation and Experiment

Stationary robotic trainers are lower limb rehab robots which often incorporate an exoskeleton attached to a stationary base. The issue observed in the stationery trainers for simultaneous knee and ankle-foot complex joints is that they restrict the natural motion of ankle-foot in the rehab trainings due to the insufficient Degrees of Freedom (DOFs) of these trainers. A new stationary knee-ankle-foot rehab robot with all necessary DOFs is developed here. A typical rehab training is first implemented in simulation, and then tested on a healthy subject. Results show that the proposed system functions naturally and meets the requirements of the desired rehab training.Comment: 23 pages, 14 figure

Nonlinear Active Noise Control Using Adaptive Wavelet Filters

This paper deals with nonlinear active noise control using adaptive wavelet filters. The ability of wavelets in signal reconstruction and function approximation make them appealing for black box system identification. Moreover, the intrinsic similarity between wavelet filters and noise/vibration signals implies that better approximation of these signals can be achieved by employing wavelet filters. Here, a new simple structure for using in active noise control system is proposed comprises a nonlinear static mapping cascaded with an IIR filter to take care of the dynamics of the system. With this strategy, one can avoid using multi-dimensional wavelet networks and thus eliminate curse of dimensionality. The performance of the proposed ANC system is examined for typical linear/nonlinear cases. The simulation results demonstrate superior performance of this method in terms of fast convergence rate and noise attenuation as well as computational complexity reduction while avoiding curse of dimensionality

Energy management and control of a hybrid electric vehicle with an integrated low temperature combustion (LTC) engine

Copyright © 2014 by ASME. Low Temperature Combustion (LTC) provides a promising solution for clean energy-efficient engine technology which has not yet been utilized in Hybrid Electric Vehicle (HEV) engines. In this study, a variant of LTC engines, known as Homogeneous Charge Compression Ignition (HCCI), is utilized for operation in a series HEV configuration. An experimentally validated dynamic HCCI model is used to develop required engine torquefuel consumption data. Given the importance of EnergyManagement Control (EMC) on HEV fuel economy, three different types of EMCs are designed and implemented. The EMC strategies incorporate three different control schemes including thermostatic Rule-Based Control (RBC), Dynamic Programming (DP), and Model Predictive Control (MPC). The simulation results are used to examine the fuel economy advantage of a series HEV with an integrated HCCI engine, compared to a conventional HEV with a modern Spark Ignition (SI) engine. The results show 12.6% improvement in fuel economy by using a HCCI engine in a HEV compared to a conventional HEV using a SI engine. In addition, the selection of EMC strategy is found to have a strong impact on vehicle fuel economy. EMC based on DP controller provides 15.3% fuel economy advantage over the RBC in a HEV with a HCCI engine