Motion control of a 1-DOF pneumatic muscle actuator positioning system

A positioning system driven by a pneumatic muscle actuator was built in order to study the applicability and adaptability of the system into real time applications such as exoskeleton robots and industrial machines. PMA system has many advantages including high power to weight and power to volume ratio, light weight, clean, autonomous and safe. However, the highly nonlinear characteristics of PMA system made it difficult to control. This has been the main challenge in proposing a robust controller for positioning and tracking performance. This study aims to clarify a practical and easy to design controller design procedure for positioning of a PMA system. In addition to positioning performance, the present study focuses on the realization of easy to design a controller without the need for exact model parameters and knowledge in control theory for systems with high nonlinearities. A PI and PID controller using Ziegler-Nicholas design law is proposed and its PTP performance is presented. Finally, the robustness of the proposed controller have been tested in a tracking environment by using triangular and sinusoidal waveform

A Supervised Machine Learning Based Intrusion Detection Model for Detecting Cyber-Attacks Against Computer System

Internet usage has become essential for correspondence in almost every calling in our digital age. To protect a network, an effective intrusion detection system (IDS) is vital. Intrusion Detection System is a software application to detect network intrusion using various machine learning algorithms. The function of the expert has been lessened by machine learning approaches since knowledge is taken directly from the data. The fact that it makes use of all the features of an information packet spinning in the network for intrusion detection is weakened by the employment of various methods for detecting intrusions, such as statistical models, safe system approaches, etc. Machine learning has become a fundamental innovation for cyber security. Two of the key types of attacks that plague businesses, as proposed in this paper, are Denial of Service (DOS) and Distributed Denial of Service (DDOS) attacks. One of the most disastrous attacks on the Internet of Things (IOT) is a denial of service.  Two diverse Machine Learning techniques are proposed in this research work, mainly Supervised learning. To achieve this goal, the paper represents a regression algorithm, which is usually used in data science and machine learning to forecast the future. An innovative approach to detecting is by using the Machine Learning algorithm by mining application-specific logs. Cyber security is a way of providing their customers the peace of mind they need knowing that they have secured their information and money

Tracking Control of Vertical Pneumatic Artificial Muscle System Using PID

The advantages of pneumatic system such as compactness, high power to weight ratio, ease of maintenance, cleanliness and inherent safety led to the development of McKibben muscle and pneumatic artificial muscle (PAM). However, the air compressibility and the lack of damping ability of PAM bring dynamic delay to the pressure response and causes oscillatory motion to occur. It is not easy to realize the motion with high accuracy and high speed due to all the non-linear characteristics of pneumatic system. In this paper, we present a vertical PAM system with a simple PID controller to control the motion of the PAM. The experiment setup is explained and Ziegler Nichols tuning method is used in getting the approximation PID parameters. The effectiveness of the proposed control algorithm is demonstrated through experiments

Frictional behaviour of AA7050/7.5B4Cp/Gr hybrid composites fabricated through stir casting

In this research, AA7050 aluminium alloy strengthened with Boron carbide (B4Cp) and Graphite (Gr) was manufactured by stir casting. The impact of the reinforcing particles on various process parameters on the friction coefficient were thoroughly examined utilizing pin-on-disc apparatus with experiments centred on design of experiments. The outcomes exposed that the coefficient of friction decreases with upsurge in percentage reinforcement and increases with applied load, and sliding distance. With respect to the sliding velocity it decreases until a saddle point, there after it starts to increase. Utilising the response surface methodology, a mathematical model for the friction coefficient was established

Exacerbation of experimental autoimmune encephalomyelitis in prion protein (PrPc)-null mice: evidence for a critical role of the central nervous system

<p>Abstract</p> <p>Background</p> <p>The cellular prion protein (PrPc) is a host-encoded glycoprotein whose transconformation into PrP scrapie (PrPSc) initiates prion diseases. The role of PrPc in health is still obscure, but many candidate functions have been attributed to the protein, both in the immune and the nervous systems. Recent data show that experimental autoimmune encephalomyelitis (EAE) is worsened in mice lacking PrPc. Disease exacerbation has been attributed to T cells that would differentiate into more aggressive effectors when deprived of PrPc. However, alternative interpretations such as reduced resistance of neurons to autoimmune insult and exacerbated gliosis leading to neuronal deficits were not considered.</p> <p>Method</p> <p>To better discriminate the contribution of immune cells versus neural cells, reciprocal bone marrow chimeras with differential expression of PrPc in the lymphoid or in the central nervous system (CNS) were generated. Mice were subsequently challenged with MOG_35-55peptide and clinical disease as well as histopathology were compared in both groups. Furthermore, to test directly the T cell hypothesis, we compared the encephalitogenicity of adoptively transferred PrPc-deficient versus PrPc-sufficient, anti-MOG T cells.</p> <p>Results</p> <p>First, EAE exacerbation in PrPc-deficient mice was confirmed. Irradiation exacerbated EAE in all the chimeras and controls, but disease was more severe in mice with a PrPc-deleted CNS and a normal immune system than in the reciprocal construction. Moreover, there was no indication that anti-MOG responses were different in PrPc-sufficient and PrPc-deficient mice. Paradoxically, PrPc-deficient anti-MOG 2D2 T cells were less pathogenic than PrPc-expressing 2D2 T cells.</p> <p>Conclusions</p> <p>In view of the present data, it can be concluded that the origin of EAE exacerbation in PrPc-ablated mice resides in the absence of the prion protein in the CNS. Furthermore, the absence of PrPc on both neural and immune cells does not synergize for disease worsening. These conclusions highlight the critical role of PrPc in maintaining the integrity of the CNS in situations of stress, especially during a neuroinflammatory insult.</p

Protease-Resistant Prions Selectively Decrease Shadoo Protein

The central event in prion diseases is the conformational conversion of the cellular prion protein (PrPC) into PrPSc, a partially protease-resistant and infectious conformer. However, the mechanism by which PrPSc causes neuronal dysfunction remains poorly understood. Levels of Shadoo (Sho), a protein that resembles the flexibly disordered N-terminal domain of PrPC, were found to be reduced in the brains of mice infected with the RML strain of prions [1], implying that Sho levels may reflect the presence of PrPSc in the brain. To test this hypothesis, we examined levels of Sho during prion infection using a variety of experimental systems. Sho protein levels were decreased in the brains of mice, hamsters, voles, and sheep infected with different natural and experimental prion strains. Furthermore, Sho levels were decreased in the brains of prion-infected, transgenic mice overexpressing Sho and in infected neuroblastoma cells. Time-course experiments revealed that Sho levels were inversely proportional to levels of protease-resistant PrPSc. Membrane anchoring and the N-terminal domain of PrP both influenced the inverse relationship between Sho and PrPSc. Although increased Sho levels had no discernible effect on prion replication in mice, we conclude that Sho is the first non-PrP marker specific for prion disease. Additional studies using this paradigm may provide insight into the cellular pathways and systems subverted by PrPSc during prion disease

Motion control of pneumatic muscle actuator: experimental setup and modeling

This paper discusses experimental setup (mechanical testing) & modelling result of pneumatic muscle actuator. In recent times, the Pneumatic Muscle Actuator (PMA) has achieved popularity in the field of research, robotics and industrial application due to its advantages such as light weight actuator, dynamic, powerful and resistant to dust and clean. Due to its nonlinear dynamics, the muscle actuator is difficult to be controlled. In this paper a pneumatic muscle actuator system is developed for motion control purpose. The dynamic system modeling is discussed. Open loop test and static load experiment have been conducted and validated with mathematical model. Finally, a brief conclusion of the pneumatic muscle actuator experimental setup and dynamic system modeling is made