FES rehabilitation platform with real-time control and performance feedback.

Osteoporosis after spinal cord injury is associated with low-trauma fractures, and consequently with increased risk of morbidity and mortality. The loss of bone mass density (BMD) due to paraplegia can be reduced through cyclical electrically-induced muscle contractions. Here we propose an FES control system based on posture switching, that induces transient loading of the lower limbs during a set of standing postures. This aims to produce an increased, evenly distributed BMD, whilst minimising FES-induced muscle fatigue. Here we describe the design and assessment of the FES exercising platform, comprising a controllable multi-channel electrical stimulator and an instrumented standing frame. The platform supports standing and postural shifting, provides real-time human-in-the-loop FES control with on-line feedback to the user. The platforms is used to investigate the effect of regular exercise on the distribution of BMD in people with paraplegia

A feedback simulation procedure for real-time control of urban drainage systems

This paper presents a feedback simulation procedure for the real-time control (RTC) of urban drainage systems (UDS) with the aim of providing accurate state evolutions to the RTC optimizer as well as illustrating the optimization performance in a virtual reality. Model predictive control (MPC) has been implemented to generate optimal solutions for the multiple objectives of UDS using a simplified conceptual model. A high-fidelity simulator InfoWorks ICM is used to carry on the simulation based on a high level detailed model of a UDS. Communication between optimizer and simulator is realized in a feedback manner, from which both the state dynamics and the optimal solutions have been implemented through realistic demonstrations. In order to validate the proposed procedure, a real pilot based on Badalona UDS has been applied as the case study.Peer ReviewedPostprint (author's final draft

Neural Feedback Scheduling of Real-Time Control Tasks

Many embedded real-time control systems suffer from resource constraints and dynamic workload variations. Although optimal feedback scheduling schemes are in principle capable of maximizing the overall control performance of multitasking control systems, most of them induce excessively large computational overheads associated with the mathematical optimization routines involved and hence are not directly applicable to practical systems. To optimize the overall control performance while minimizing the overhead of feedback scheduling, this paper proposes an efficient feedback scheduling scheme based on feedforward neural networks. Using the optimal solutions obtained offline by mathematical optimization methods, a back-propagation (BP) neural network is designed to adapt online the sampling periods of concurrent control tasks with respect to changes in computing resource availability. Numerical simulation results show that the proposed scheme can reduce the computational overhead significantly while delivering almost the same overall control performance as compared to optimal feedback scheduling.Comment: To appear in International Journal of Innovative Computing, Information and Contro

Real time control for NASA robotic gripper

Control laws (in some optimal sense) are being developed for the gripper/nut runner end effector. Control laws for the gripper and nut runner portions of the end effector may be developed independently since these two systems are decoupled. A hybrid force/position controller will be used for both the gripper and nut runner. The development of the gripper controller is explained. Sensory data available to the controller is obtained from an array of strain gages as well as a linear potentiometer. Applying well known optimal control theoretic principles, the control which minimizes the transition time between positions is obtained. In addition, a robust force control scheme is developed to contend with the strain gage drift caused by extreme temperature variations encountered in space

PC Based Real TIME Control of DC Motor

– This final project report present a Pc based real time control of DC motor. Real time control systems can be defined as a technology which is related to mechanical application, electronic, and computer-based systems. In general, the equipment that is often used for controlling speed system is Arduino Mega 2560, DC motor, motor driver IC L298N, speed sensor IC LM393, and voltage sensor. Software in the system I used Matlab Simulink to monitor and control the speed of dc motor will show real data, they are displayed in signal RPM and signal Voltage, Matlab Simulink is used program to let the operator operates the system well. This monitor and control system can improve the effectiveness and efficiency in various industrial fields. Keyword – PC, Real Time, Control, DC Moto

Execution environment for intelligent real-time control systems

Modern telerobot control technology requires the integration of symbolic and non-symbolic programming techniques, different models of parallel computations, and various programming paradigms. The Multigraph Architecture, which has been developed for the implementation of intelligent real-time control systems is described. The layered architecture includes specific computational models, integrated execution environment and various high-level tools. A special feature of the architecture is the tight coupling between the symbolic and non-symbolic computations. It supports not only a data interface, but also the integration of the control structures in a parallel computing environment