Cascade PID controller optimization using bison algorithm

Meta-heuristic algorithms are reliable tools for modern optimization. Yet their amount is so immense that it is hard to pick just one to solve a specific problem. Therefore many researchers hold on known, approved algorithms. But is it always beneficial? In this paper, we use the meta-heuristics for the design of cascade PID controllers and compare the performance of the newly developed Bison Algorithm with well-known algorithms like the Differential Evolution, the Genetics Algorithm, the Particle Swarm Optimization, and the Cuckoo Search. Also, in the proposed approach, the controller parameters were encoded to increase the chance of reducing the controller structure, and thus facilitate the automatic selection of its configuration. The simulations were performed for three different control problems and checked whether the use of cascade structures could bring significant benefits in comparison to the use of classic PID controllers. © 2020, Springer Nature Switzerland AG

A Novel Self-Organizing Neuro-Fuzzy based Intelligent Control System for a AR. Drone Quadcopter

In recent times, readily available autopilots like the AR.Drone boost the implementation of Unmanned Aerial Vehicles (UAVs) in profuse civilian and military applications. Some open confrontations in developing high performance control mechanism for the UAVs are namely their complex nonlinear dynamics, craving to their full-autonomy, and various associated uncertainties. To prevail such challenges, the conventional first principle technique based controllers confront predicaments due to their static structure and dependency on model’s accuracy. It entails interest on the self-organizing intelligent controller. In this work, a self-organizing controller namely Generic evolving Neuro-fuzzy controller (G-controller) is employed to regulate the position of an AR.Drone quadcopter’s simulated plant. The self-organizing architecture of G-controller is rooted with an algorithm namely Generic Evolving Neuro-Fuzzy Inference System (GENEFIS). Besides, the Sliding Mode Control (SMC) theory is integrated to ensure the convergence of tracking error to zero. Performance of the G-controller has been evaluated by monitoring the position for various trajectories of a AR.Drone simulated plant. Furthermore, g-controller’s performance is compared with a standard PID controller

Advancement in energy harvesting magneto-rheological fluid damper: A review

© 2016 The Korean Society of Rheology and Springer. In this paper, a comprehensive review of the present literature on energy generated magnetorheological (MR) fluid based damper, modeling and applications of the MR damper are presented. The review starts with an introduction of the basic of MR fluid and their different modes, consequences with different types of MR fluids based devices, and their relevant applications. Besides, various forms of MR damper and its applications are presented. Following this, the modeling of the MR fluids and the modeling of the MR fluid based damper are deliberated according to arrangement and configurations. Finally, the review ends with the design and advancement issues, performance analysis matters, and analytical modeling of energy generated magnetorheological fluid damper systems

A state of art on magneto-rheological materials and their potential applications

Smart materials are kinds of designed materials whose properties are controllable with the application of external stimuli such as the magnetic field, electric field, stress, and heat. Smart materials whose rheological properties are controlled by externally applied magnetic field are known as magneto-rheological materials. Magneto-rheological materials actively used for engineering applications include fluids, foams, grease, elastomers, and plastomers. In the last two decades, magneto-rheological materials have gained great attention of researchers significantly because of their salient controllable properties and potential applications to various fields such as automotive industry, civil environment, and military sector. This article offers a recent progressive review on the magneto-rheological materials technology, especially focusing on numerous application devices and systems utilizing magneto-rheological materials. Conceivable limitations, challenges, and comparable advantages of applying these magneto-rheological materials in various sectors are analyzed critically, which provides a clear pathway to the researchers in selecting and utilizing these materials. The review starts with an introduction to the elementary description of magneto-rheological materials and their significant contribution in various fields. Following this, different types of the magneto-rheological materials, modeling of the magneto-rheological materials, magneto-rheological material–based devices, and their applications have been extensively reviewed to promote practical use of magneto-rheological materials in a wide spectrum of the application from the automobile to medical device

Development of C-Means Clustering Based Adaptive Fuzzy Controller for a Flapping Wing Micro Air Vehicle

Advanced and accurate modelling of a Flapping Wing Micro Air Vehicle (FW MAV) and its control is one of the recent research topics related to the field of autonomous MAVs. Some desiring features of the FW MAV are quick flight, vertical take-off and landing, hovering, and fast turn, and enhanced manoeuvrability contrasted with similar-sized fixed and rotary wing MAVs. Inspired by the FW MAV's advanced features, a four-wing Nature-inspired (NI) FW MAV is modelled and controlled in this work. The Fuzzy C-Means (FCM) clustering algorithm is utilized to construct the data-driven NIFW MAV model. Being model free, it does not depend on the system dynamics and can incorporate various uncertainties like sensor error, wind gust etc. Furthermore, a Takagi-Sugeno (T-S) fuzzy structure based adaptive fuzzy controller is proposed. The proposed adaptive controller can tune its antecedent and consequent parameters using FCM clustering technique. This controller is employed to control the altitude of the NIFW MAV, and compared with a standalone Proportional Integral Derivative (PID) controller, and a Sliding Mode Control (SMC) theory based advanced controller. Parameter adaptation of the proposed controller helps to outperform it static PID counterpart. Performance of our controller is also comparable with its advanced and complex counterpart namely SMC-Fuzzy controller

Online identification of a rotary wing Unmanned Aerial Vehicle from data streams

Until now the majority of the neuro and fuzzy modeling and control approaches for rotary wing Unmanned Aerial Vehicles (UAVs), such as the quadrotor, have been based on batch learning techniques, therefore static in structure, and cannot adapt to rapidly changing environments. Implication of Evolving Intelligent System (EIS) based model-free data-driven techniques in fuzzy system are good alternatives, since they are able to evolve both their structure and parameters to cope with sudden changes in behavior, and performs perfectly in a single pass learning mode which is suitable for online real-time deployment. The Metacognitive Scaffolding Learning Machine (McSLM) is seen as a generalized version of EIS since the metacognitive concept enables the what-to-learn, how-to-learn, and when-to-learn scheme, and the scaffolding theory realizes a plug-and-play property which strengthens the online working principle of EISs. This paper proposes a novel online identification scheme, applied to a quadrotor using real-time experimental flight data streams based on McSLM, namely Metacognitive Scaffolding Interval Type 2 Recurrent Fuzzy Neural Network (McSIT2RFNN). Our proposed approach demonstrated significant improvements in both accuracy and complexity against some renowned existing variants of the McSLMs and EISs

A review of advances in magnetorheological dampers: their design optimization and applications

© 2017, Zhejiang University and Springer-Verlag GmbH Germany, part of Springer Nature. In recent years, magnetorheological (MR) fluid technology has received much attention and consequently has shown much improvement. Its adaptable nature has led to rapid growth in such varied engineering applications as the base isolation of civil structures, vehicle suspensions, and several bio-engineering mechanisms through its implementation in different MR fluid base devices, particularly in MR dampers. The MR damper is an advanced application of a semi-active device which performs effectively in vibration reduction due to its control ability in both on and off states. The MR damper has the capacity to generate a large damping force, with comparatively low power consumption, fast and flexible response, and simplicity of design. With reference to the huge demand for MR dampers, this paper reviews the advantages of these semi-active systems over passive and active systems, the versatile application of MR dampers, and the fabrication of the configurations of various MR dampers, and provides an overview of various MR damper models. To address the increasing adaptability of the MR dampers, their latest design optimization and advances are also presented. Because of the tremendous interest in self-powered and energy-saving technologies, a broad overview of the design of MR dampers for energy harvesting and their modeling is also incorporated in this paper

Molecular diagnosis of bovine tuberculosis in bovine and human samples: implications for zoonosis

Aim: To develop emerging diagnostic technique for bovine tuberculosis and to identify its potential risk factors. Materials & methods: Bacterial genomic DNA was isolated from bovine milk and human sputum samples and subjected to PCR using specific primer pairs. PCR results were validated using bacteriological cultures. Results: PCR amplification of the targeted DNA fragment of Mycobacterium bovis was successful in 12.33% (37/300) of the bovine samples. Interestingly, 500-bp DNA fragment was also amplified in 6.67% (6/90) of the sputum indicating the possibility of zoonotic transmission. Rearing of livestock in household, unpasteurized milk consumption and smoking were identified as potential risk factors. Conclusion: Results of the study may add value to bovine tuberculosis eradication campaigns to achieve the One Health initiative