25 research outputs found
Tracking Control using Sensor Technology Solar Cell: In Real Time Domain Analysis
Get PDFSolar Tracking (ST) is employed to maximize output power due to the nonlinear characteristics of renewable energy sources. Sunlight is considered the most reliable traditional source of energy when energy emergencies arise. First, we present some basic characteristics of the motor in the form of Tables and Figures. Solar panel tracking is, therefore, necessary to enhance their efficiency. In this article, we present the sensor based viz. STM32 microcontroller has been implemented in real-time using the PV arrays. In addition, we did an analysis of stateof-the-art reviews of solar photo-voltaic systems for this research article. Researchers have developed sensor-based techniques to improve renewable energy systems. This technique performs better than other traditional methods
Quantized Dissipative Observer-Based Output Feedback Control for a Class of Markovian Descriptor Jump Systems with Communication Delay
No full textThis paper investigates the problem of quantized dissipative observer-based output feedback control of Markovian descriptor jump systems with unavailable states, appearing networked-induced delay. The descriptor systems are presented as Markovian jump systems which give a more realistic presentation for a variety of nonlinear dynamical systems than conventional state-space representation. To accomplish the objective, a uniform framework is employed to design the delayed Markov observer-based controller and event-triggered scheme. Additionally, we provided the ℋ∞ and ℒ2-ℒ∞ and dissipative performance indices which are robust against the disturbances with time-varying delays. Moreover, a novel Lyapunov–Krasovskii functional is considered to guarantee the closed loop for stochastic stability analysis of the Markovian descriptor jump system. The solvability of Lyapunov–Krasovskii functional results in the formation of linear matrix inequalities. The controller and observer gains can be obtained by solving the linear matrix inequalities. Simulations are performed to validate the proposed scheme
Modeling a Takagi-Sugeno (T-S) fuzzy for unmanned aircraft vehicle using fuzzy controller
No full textDrone technology has the potential to disrupt and augment our quality of life, as it is rapidly growing in popularity and being utilized in various applications, such as agriculture, emergency response, border control, asset inspection, and intelligent transportation. On the other side, Artificial intelligent instruments that possess a variety of input and output (I/O) mechanisms are employed to achieve model stabilizing with data estimation. Firstly, in the present study, a linear mathematical model was developed for a quad–copter Unmanned Aerial Vehicle (UAV), in which the Takagi–Sugeno (T–S) Fuzzy logic framework was integrated. The crisp variables have been used to make the interference between the input and output of the T–S fuzzy system. Secondly, to control a quadcopter model with inherent dynamic instability, these state space models are crucial. Inputs of fuzzy controller are data generated by sensors and Bluetooth connected to IoT. The state–space model of the quad copter, which consists of six Degrees Of Freedom (6–DOF), is derived by utilizing fundamental Newtonian equations. This establishment of the model holds significant value in effectively governing the quad copter system. Thirdly, the system stabilizing has been proved by linear matrix inequalities (LMIs) with an associated Lyapunov function with the γ performance index. Simulation results have been presented to demonstrate the efficiency of our proposed algorithm with additional computational burden analysis
Event-triggered reliable dissipative filtering for the delay nonlinear system under networked systems with the sensor fault
No full textStochastic Stability Analysis for Networked Markov Jump System
No full text552-557In the paper, we describe the development and implementation of reliable H∞filters for a class of Networked Markov
Jump Systems (NMJS) with random sensor failures that are triggered by events. The plant's nonlinear dynamic is
approximated with a NMJS. Failures of sensors are described using stochastic variables. The Event-Triggered Mechanism
(ETM) is introduced to NCS, which offers some positive points over other schemes. Using the event-triggered mechanism,
data of sensors from the plant will be only transmitted if it contradicts the specified condition. By considering the effects of
an ETM and the sensor faults, the event-based filter is developed for NMJS. The design parameters of the filter as well as
sufficient conditions for its existence are given accurately based on Linear Matrix Inequality (LMI)
Design of Hybrid Controller using Qualitative Simulation Internal Modeling for Inverted Pendulum
Get PDFMultiple model methods for nonlinear dynamical system control are appealing because local models can be simple and obvious, and global dynamics can be studied in terms of transitions between small operating zones. In this study, we propose that using qualitative models strengthens the multiple model method even more by enabling each local model to explain a huge class of effective nonlinear dynamical systems. Furthermore, reasoning using qualitative models reveals weak necessary conditions sufficient to verify qualitative features like stability analysis. The authors show the method by creating a global controller for the free pendulum. In addition, local controllers are specified and validated by comparing their patterns to basic general qualitative models. Our proposed procedure establishes qualitative limitations on controller designs that are sufficient to ensure the necessary local attributes and to establish feasible transitions between local areas for the existing problems. As a result, the continuous phase picture may be reduced to a simple transitional graph. The degrees of freedom in the system that are not bound by the qualitative description are still accessible to the designer for optimization for any other purpose. An example of a pendulum plant illustrates the effectiveness of the proposed method
Fault detection for asynchronous T–S fuzzy networked Markov jump systems with new event‐triggered scheme
No full textAbstract In this article, an adaptive event‐triggered fault detection problem for the asynchronous Takagi–Sugeno fuzzy networked Markov jump systems is investigated based upon the time‐varying delays. The purpose of designing a fault detection filter is to detect the fault signal under the influence of disturbance with network transmission. In the design process, one essential factor, time‐varying delay in the fuzzy filter with appearing in the residual signal, is taken into consideration. In order to rationally utilise network resources and elaborately avoid unnecessary continuous monitoring, an adaptive event‐triggered scheme is designed to guarantee the Takagi–Sugeno fuzzy networked Markov jump systems. Thus it helps to lower the energy consumption of communication while ensuring the performance of the system. Different from the conventional triggering mechanism, in this article, the parameters of the triggering function are based on a new adaptive law which is obtained online rather than a predefined constant. Based on the associated Lyapunov stability theory and appropriate inequality, some sufficient criteria in the form of linear matrix inequalities are obtained to ensure the stability of the resulting error system. Finally, a tunnel diode example is employed to illustrate the effectiveness of the proposed methods
Event-triggered fuzzy filtering in networked control system for a class of non-linear system with time delays
No full textExtended Dissipative Filter for Delayed T-S Fuzzy Network of Stochastic System with Packet Loss
No full text450-459This research investigates a time-varying delay-based adaptive event-triggered dissipative filtering problem for the
interval type-2 (IT-2) Takagi-Sugeno (T-S) fuzzy networked stochastic system. The concept of extended dissipativity is used
to solve the ∞, ∞ and dissipative performances for (IT-2) T-S fuzzy stochastic systems in a unified manner. Data
packet failures and latency difficulties are taken into account while designing fuzzy filters. An adaptive event-triggered
mechanism is presented to efficiently control network resources and minimise excessive continuous monitoring while
assuring the system’s efficiency with extended dissipativity. A new adaptive event triggering scheme is proposed which
depends on the dynamic error rather than pre-determined constant threshold. A new fuzzy stochastic Lyapunov-Krasovskii
Functional (LKF) using fuzzy matrices with higher order integrals is built based on the Lyapunov stability principle for
mode-dependent filters. Solvability of such LKF leads to the formation of appropriate conditions in the form of linear matrix
inequalities, ensuring that the resulting error mechanism is stable. In order to highlight the utility and perfection of the
proposed technique, an example is presented
