The Modulation and Control of the Gecko's Foot Movement

The modulation and control of gecko＇s foot movements were studied electrophysiologically in order to design the motor control system of a gecko-mimic robot. In this study （1） the anatomy of the peripheral nerves controlling the gecko＇s foot movements was determined; （2） the relationship between the limb nerves of the gecko and its foot motor patterns was studied; （3） the afferent impulses of the nerves evoked by rubbing the gecko＇s toes and palm were recorded; （4） copying the natural patterns of movement of the gecko＇s foot （abduction, adduction, flexion, and revolution） and its limb nerve modulation and control mechanism, the nerves were stimulated under computer control, and the results recorded by CCD. Results suggest that gecko＇s foot movements can be successfully controlled by artificial electrical signals.

Temperature Intelligent Control System of Large-Scale Standing Quench Furnace

Considering some characteristics of large-scale standing quench furnace, such as great heat inertia, evident time lag, strong coupling influence, hard to establish exact mathematical models of plant and etc, an artificial intelligent fuzzy control algorithm is put forward in this paper. Through adjusting the on-off ratio of electric heating elements, the temperature in furnace is controlled accurately. This paper describes structure and qualities of the large-scale standing quench furnace briefly, introduces constitution of control system, and expounds principle and implementation of intelligent control algorithm. The applied results prove that the intelligent control system can completely satisfy the technological requirements. Namely, it can realize fast increasing temperature with a little overshoot, exact holding temperature, and well-distributed temperature in quench furnace. It has raised the output and quality of aluminum material, and brought the outstanding economic and social benefits.

Hand Gesture-based Artificial Neural Network Trained Hybrid Human–machine Interface System to Navigate a Powered Wheelchair

Individuals with cerebral palsy and muscular dystrophy often lack fine motor control of their fingers which makes it difficult to control traditional powered wheelchairs using a joystick.Studies have shown the use of surface electromyography to steer powered wheelchairs or automobiles either through simulations or gaming controllers.However,these studies significantly lack issues with real world scenarios such as user’s safety,real-time control,and efficiency of the controller mechanism.The purpose of this study was to design,evaluate,and implement a hybrid human–machine interface system for a powered wheelchair that can detect human intent based on artificial neural network trained hand gesture recognition and navigate a powered wheelchair without colliding with objects around the path.Scaled Conjugate Gradient(SCG),Bayesian Regularization(BR),and Levenberg Marquart(LM)supervised artificial neural networks were trained in offline testing on eight participants without disability followed by online testing using the classifier with highest accuracy.Bayesian Regularization architecture showed highest accuracy at 98.4%across all participants and hidden layers.All participants successfully completed the path in an average of 5 min and 50 s,touching an average of 22.1%of the obstacles.The proposed hybrid system can be implemented to assist people with neuromuscular disabilities in near future.

Experimental verification of chopper fed DC series motor with ANN controller

In this article an artificial neural network （ANN） has been designed for the control of DC series motor through a DC chopper （DC-DC buck converter）. The proportional-integral-derivative （PID）-ANN speed controller controls the motor voltage by controlling the duty cycle of the chopper thereby the motor speed is regulated. The PID-ANN controller performances are analyzed in both steady-state and dynamic operating condition with various set speeds and various load torques. The rise time, maximum overshoot, settling time, steady-state error, and speed drops are taken for comparison with conventional PID controller and existing work. The training samples for the neuron controller are acquired from the conventional PID controller. The PID-ANN controller performances are analyzed in respect of various load torques and various speeds using MATLAB simula-tion. Then the designed controllers were experimentally verified using an NXP 80C51 based microcontroller （P89VSIRD2BN）. It was found that the hybrid PID-ANN controller with DC chopper can have better control compared with conventional PID controller.

Changes in respiratory and circulatory functions during sequential invasive-noninvasive mechanical ventilation

Objective To investigate the changes in respiratory and circulatory functions in chronic obstructive pulmonary disease (COPD) patients during sequential invasive-noninvasive mechanical ventilation therapy,and evaluate the effects of this new technique.Methods Twelve COPD patients with type Ⅱ respiratory failure due to severe pulmonary infection were ventilated through an endotracheal tube. When the pulmonary infection control window (PIC-Window) occurred,the patients were extubated and were ventilated with a facial mask using pressure support ventilation combined with positive end-expiratory pressure. The parameters of hemodynamics,oxygen dynamics,and esophageal pressure were measured at the PIC-Window during invasive mechanical ventilation,one hour after oxygen therapy via a naso-tube,and three hours after non-invasive mechanical ventilation. Results The variation in esophageal pressure was 20.0±6 cmH 2O during naso-tube oxygen therapy,and this variation was higher than that during non-invasive mechanical ventilation (10±6 cmH 2O, P <0.01). The changes in respiratory and circulatory parameters were not significantly different between invasive mechanical ventilation and noninvasive mechanical ventilation ( P >0.05).Conclusions The respiratory and circulatory functions of COPD patients remained stable during sequential invasive-noninvasive mechanical ventilation therapy using PIC-Window as a switch point for early extubation. The COPD patients can tolerated the transition from invasive mechanical ventilation to noninvasive mechanical ventilation.

ATC simulation for flight training:The missing link

This paper presents the state of piloted flight simulation fidelity with a focus on the missing link needed to complete the flight simulation experience,namely the simulated ATC environment(SATCE).To date,there has been a great deal of effort invested in providing the highest level of flight realism possible.However,little investment has gone into systems which are used to improve communication skills with ATC while in a populated active airspace.It is important to note that the relatively few SATCEs is not due to the lack of technology,since such products have been available for about a decade.The primary reason for its absence is the inability and unwillingness for operators to justify the investment in such a training tool.In the meantime,the aviation industry has recognized that pilots need to have better communication skills while operating in various conditions.Consequently ICAO,with help from ARINC Industry Activities/FSEMC,has already taken steps to recommend the inclusion of SATCE characteristics in flight simulation devices.The aviation and research communities need to assist efforts by producing the necessary studies and metrics which can be used to evaluate and validate SATCEs used in the flight training.