Embedded fuzzy controller for water level control

This article presents the design of a fuzzy controller embedded in a microcontroller aimed at implementing a low-cost, modular process control system. The fuzzy system's construction is based on a classical proportional and derivative controller, where inputs of error and its derivate depend on the difference between the desired setpoint and the actual level; the goal is to control the water level of coupled tanks. The process is oriented to control based on the knowledge that facilitates the adjustment of the output variable without complex mathematical modeling. In different response tests of the fuzzy controller, a maximum over-impulse greater than 8% or a steady-state error greater than 2.1% was not evidenced when varying the setpoint.

IoT-based sound-level control for audio amplifiers: mosques as a case study

<p><span>When using audio-amplifiers in the open, uneven distribution of sound makes people unpleasant because it is loud or unheared. This unfortunate situation arises because audio-amplifiers volumes are set according to the guess of sound technicians. Mosques, as an example, are distributed inside wide areas and fire Azan five times a day. Due to the relatively long distances between them, speed and direction of the wind impose setting sound levels prior to each Azan such that all the area is covered and the overlap is minimized. In this paper, we propose a system based on internet of things (IoT) model to control the sound level of each mosque in the community. An IoT device (one in a mosque) sets the level of sound fired by the audio-amplifier. To do that, a synchronized series of tones is fired from each node. Once a node hears these tones, the process of sound level control starts to indicate the distances to heared nodes. As the approximate distances between nodes are known, each node can calculate its suitable sound level. Results showed that the proposed system is effective in setting sound levels for mosques audio amplifiers.</span></p>

Adaptive Fault-Tolerant Control of a Hybrid VTOL UAV against Actuator Faults and Model Uncertainties under Fixed-Wing Mode

This paper proposes an adaptive fault-tolerant control strategy for a hybrid vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV) to simultaneously compensate actuator faults and model uncertainties. With the proposed adaptive control schemes, both actuator faults and model uncertainties can be accommodated without the knowledge of fault information and uncertainty bounds. The proposed control scheme is constructed with two separate control modules. The low-level control allocation module is used to distribute the virtual control signals among the available redundant actuators. The high-level control module is constructed with an adaptive sliding mode controller, which is employed to maintain the overall system tracking performance in both faulty and uncertain conditions. In the case of actuator faults and model uncertainties, the adaptive scheme will be triggered to generate more virtual control signals to compensate the virtual control error and maintain the desired system tracking performance. The effectiveness of the proposed control strategy is validated through comparative simulation tests under different faulty and uncertain scenarios.

Solutions to the routing problem: towards trustworthy autonomous vehicles

The general expectation is that the traffic in the cities will be almost optimal when the collective behaviour of autonomous vehicles will determine the traffic. Each member of the collective of autonomous vehicles tries to adapt to the changing environment, therefore together they execute decentralised autonomous adaptation by exploiting real-time information about their environment. The routing of these vehicles needs proper computer science models to be able to develop the best information technology for their control. We review different traffic flow models in computer science, and we evaluate their usefulness and applicability to autonomous vehicles. The classical game theory model implies flow level decision making in route selection. Non-cooperative autonomous vehicles may produce unwanted traffic patterns. Improved decentralised autonomous adaptation techniques try to establish some kind of coordination among autonomous vehicles, mainly through intention awareness. The aggregation of the intentions of autonomous vehicles may help to predict future traffic situations. The novel intention-aware online routing game model points out that intention-awareness helps to avoid that the traffic generated by autonomous vehicles be worse than the traffic indicated by classical traffic flow models. The review helps to make the first steps towards research on global level control of autonomous vehicles by highlighting the strengths and weaknesses of the different formal models. The review also highlights the importance of research on intention-awareness and intention-aware traffic flow prediction methods.

Four weeks of electrical stimulation improves glucose tolerance in sedentary overweight or obese Hispanic population

Introduction/Purpose: Most U.S. adults (54%) do not meet minimum exercise recommendations by American College of Sports Medicine (ACSM). Neuromuscular electrical stimulation (NMES) is a novel alternate strategy to induce muscle contraction. However, effectiveness of NMES to improve insulin sensitivity and energy expenditure is unclear. The purpose of this study was to investigate the effects of four weeks of NMES on glucose tolerance in a sedentary overweight or obese population. Methods: Participants (n=10; age: 36.8 ± 3.8 years; BMI=32 ± 1.3 kg/ m2) were randomized into either control or NMES group. All participants received bilateral quadriceps stimulation (12 sessions; 30 minutes/session; 3 times/week at 50 Hz and 300 µs pulse width) altering pulse amplitude to either provide low intensity sensory level (control; tingling sensation) or at high intensity neuromuscular level (NMES; maximum tolerable levels with visible muscle contraction). Glucose tolerance was assessed by three-hour oral glucose tolerance test (OGTT), substrate utilization was measured by indirect calorimetry and body composition via dual X-ray absorptiometry at baseline and after four weeks of NMES intervention. Results: Control and NMES groups had comparable fasting blood glucose, glucose tolerance, substrate utilization, and muscle mass at baseline. Four weeks of NMES resulted in a significant improvement in glucose tolerance measured by OGTT, whereas no change was observed in control group. There was no change in substrate utilization and in muscle mass in both control and NMES groups. Conclusion: NMES is a novel and effective strategy to improve glucose tolerance in an at-risk overweight or obese sedentary population.