Solar Engineering Of Thermal Processes

Several simplified design procedures for solar energy systems require monthly average meteorological data. Monthly average daily totals of the solar radiation incident on a horizontal surface are available. However, radiation data on tilted surfaces, required by the design procedures, are generally not available. A simple method of estimating the average daily radiation for each calendar month on surfaces facing directly towards the equator has been presented by Liu and Jordan [1]. This method is verified with experimental measurements and extended to allow calculation of monthly average radiation on surfaces of a wide range of orientations.

Calculation of monthly average insolation on tilted surfaces

Race Car Vehicle Dynamics

This review presents various control strategies for application systems utilizing smart magneto-rheological fluid (MRF) and magneto-rheological elastomers (MRE). It is well known that both MRF and MRE are actively studied and applied to many practical systems such as vehicle dampers. The mandatory requirements for successful applications of MRF and MRE include several factors: advanced material properties, optimal mechanisms, suitable modeling, and appropriate control schemes. Among these requirements, the use of an appropriate control scheme is a crucial factor since it is the final action stage of the application systems to achieve the desired output responses. There are numerous different control strategies which have been applied to many different application systems of MRF and MRE, summarized in this review. In the literature review, advantages and disadvantages of each control scheme are discussed so that potential researchers can develop more effective strategies to achieve higher control performance of many application systems utilizing magneto-rheological materials.

/pdf/state-of-the-art-of-control-schemes-for-smart-systems-3hwy929fi6.pdf

State of the art of control schemes for smart systems featuring magneto-rheological materials

Much research has gone into developing advanced control algorithms for semi-active suspension. Experimental validation of these control algorithms is critical for their practical applications. This paper investigates a state-observer-based Takagi–Sugeno fuzzy controller (SOTSFC) design for a semi-active quarter-car suspension installed with a magnetorheological (MR) damper and provides proof of the effectiveness of the proposed controller. To conduct the test, a quarter-car test rig and control system hardware were used. Then, a new MR damper was designed and built to fit with the test rig. After that, the SOTSFC for the quarter-car test rig was developed. Finally, several tests were conducted on the quarter-car suspension in order to investigate the real effect of the SOTSFC. It was then compared with the use of a skyhook controller to demonstrate its benefits.

Takagi–Sugeno Fuzzy Control for Semi-Active Vehicle Suspension With a Magnetorheological Damper and Experimental Validation

The Internet of Things (IoT) represents a mean to share resources (memory, storage computational power, data, etc.) between computers and mobile devices, as well as buildings, wearable devices, electrical grids, and automobiles, just to name few. The IoT is leading to the development of advanced information services that will require large storage and computational power, as well as real-time processing capabilities. The integration of IoT with emerging technologies such as Fog Computing can complement these requirements with pervasive and cost-effective services capable of processing large-scale geo-distributed information. In any IoT application, communication availability is essential to deliver accurate and useful information, for instance, to take actions during dangerous situations, or to manage critical infrastructures. IoT components like gateways, also called Fog Nodes, face outstanding security challenges as the attack surface grows with the number of connected devices requesting communication services. These Fog nodes can be targeted by an attacker, preventing the nodes from delivering important information to the final users or to perform accurate automated actions. This paper introduces an Anomaly Behavior Analysis Methodology based on Artificial Neural Networks, to implement an adaptive Intrusion Detection System (IDS) capable of detecting when a Fog node has been compromised, and then take the required actions to ensure communication availability. The experimental results reveal that the proposed approach has the capability for characterizing the normal behavior of Fog Nodes despite its complexity due to the adaptive scheme, and also has the capability of detecting anomalies due to any kind of sources such as misuses, cyber-attacks or system glitches, with high detection rate and low false alarms.

/pdf/artificial-neural-networks-based-intrusion-detection-system-31icju3jd4.pdf

Artificial Neural Networks Based Intrusion Detection System for Internet of Things Fog Nodes

This research work presents an H ∞ controller based on a Takagi–Sugeno (T–S) fuzzy model for a two-degrees-of-freedom (2-DOF) one-quarter-vehicle semi-active suspension with a magnetorheological damper where the actuator dynamics are included in the control synthesis. These dynamics enclose nonlinear damper phenomena, avoided in many other studies, and that can improve the suspension system by means of a more accurate model. The objective is to obtain a semi-active suspension that considerably improves the passive suspension efficiency based on some frequency domain performance criteria. The advantage of having the T–S system as a reference is that each piecewise linear system can be exposed to the well-known control theory. Besides, the proposed solution is compared with the recent reported work to highlight its advantages. A case of study is included and simulation work supports the results. The methodology applied herein can be extended to a half-vehicle model, and to the four wheels to have a global c...

H ∞ control of a suspension with a magnetorheological damper

Reported researches on semi-active suspension neglect the actuador dynamics, missing important information that can deteriorate the suspension's performance. The present research proposes a new semi-active suspension model with a magnetorheological damper, including its dynamics. Three control approaches are applied to this suspension model to improve passenger comfort and vehicle stability. The well known control strategies: skyhook, groundhook and hybrid, are adequated for the model and simulated using Matlab. Exhaustive simulation results compare comfort and stability between an average city car passive suspension and the proposed semi-active suspension. The suspension with hybrid control shows the best performance complying, at the same time, with vehicle stability and passenger comfort.

Modeling and Control for a Semi-active Suspension with a Magnetorheological Damper Including the Actuator Dynamics

http://www.scielo.org.mx/pdf/jart/v14n3/1665-6423-jart-14-03-00173.pdf

H2 control of a one-quarter semi-active ground vehicle suspension

In this work, four different semi-active controllers for a quarter of vehicle and full vehicles are evaluated and compared when used in internal combustion engine (ICE) vehicles vs electric vehicles (EVs) with in-wheel motor configuration as a way to explore the use of semi-active suspension systems in this kind of EVs First, the quarter of vehicle vertical dynamics is analyzed and then a full vehicle approach explores the effectiveness of the control strategies and the effects of the traction in the vertical Control performances Aspects like the relation between traction and suspension performances, and the resonance frequencies are also discussed

https://www.mdpi.com/2076-3417/10/13/4522/pdf

L. C. Félix-Herrán

Papers

Artificial Neural Networks Based Intrusion Detection System for Internet of Things Fog Nodes

H ∞ control of a suspension with a magnetorheological damper

Modeling and Control for a Semi-active Suspension with a Magnetorheological Damper Including the Actuator Dynamics

H2 control of a one-quarter semi-active ground vehicle suspension

Control of Automotive Semi-Active MR Suspensions for In-Wheel Electric Vehicles