‎This ‎paper ‎presents ‎the‎ modified function projective synchronization (MFPS) in a system with complex variables related to the permanent magnet synchronous motor (PMSM) with unknown parameters.‎ In this method, by defining a suitable adaptive More
‎This ‎paper ‎presents ‎the‎ modified function projective synchronization (MFPS) in a system with complex variables related to the permanent magnet synchronous motor (PMSM) with unknown parameters.‎ In this method, by defining a suitable adaptive controller and other desired functions and with the aid of Lyapunov stability theory, the asymptotic stability of the error function can be proved. This can lead to a modified function projective synchronization between two complex chaotic systems with completely unknown parameters. Also, the error of estimating the parameters and the value of the coupling strength is accurately expressed using the proposed method.‎‎Because in the modified projective synchronization (MPS) and function projective synchronization (FPS) methods, fixed coupling strength is considered, this limits the range of applications of these methods. MFPS is, therefore, a more general definition of MPS and FPS when the scaling function matrix is chosen by a constant matrix and a scaling function, respectively. This method can be used on other complex dynamic systems. Numerical simulations are presented to show the effectiveness and validity of the above theoretical results.
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According to the critical role of gas turbines in the industry, monitoring the performance of gas turbines is an important issue since it can prevent unexpected shutdowns and the serious consequent financial harms. One of the most important parts of a gas turbine is the More
According to the critical role of gas turbines in the industry, monitoring the performance of gas turbines is an important issue since it can prevent unexpected shutdowns and the serious consequent financial harms. One of the most important parts of a gas turbine is the combustion chamber. Although the internal pressure and temperature of the combustion chamber can directly affect the performance and useful life of this part, however, it is not possible to measure it directly through sensors. Therefore, estimation of pressure variable is a good choice to achieve greater performance and more relative stability comparing with the methods in which there is no access to the internal pressure of the chamber. In this research, a suitable nonlinear dynamic model with produced power and exhausted gas temperature as its outputs is chosen. Thereafter, an adaptive surface sliding observer is designed in order to estimate the combustion pressure and temperature which are the state variables of the gas turbine. Afterward, utilizing a sliding mode controller and applying the estimated states, the produced power and exhaustion gas temperature of the gas turbine is controlled. In this paper, the stability of the closed-loop system in the presence of the state observer through the Lyapunov approach is guaranteed. Finally, simulation results are provided to verify the validity and efficiency of the proposed method.
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The purpose of this paper is design of a neuro-adaptive controller for SCARA mechanical arm. First, a brief description of the work that has been done on similar systems will be presented and then using the Euler - Lagrange, based on kinetic and potential energy of More
The purpose of this paper is design of a neuro-adaptive controller for SCARA mechanical arm. First, a brief description of the work that has been done on similar systems will be presented and then using the Euler - Lagrange, based on kinetic and potential energy of the system, the dynamical equations of system will be calculated. The proposed controller is used to provide a suitable Lyapunov function, expression and comparative law will guarantee the stability of the closed loop system. All signals in the closed loop system are limited and the error signal tends asymptotically to origin. The control system is designed to demonstrate the efficacy of proposed controller on three links SCARA robot is implemented, the results of the controller performance guarantees.
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This paper presents a control approach to the fuzzy-adaptive control scheme for rigid manipulators with unknown parameters. Lagrange’s method is employed for computing robot motion dynamics. Stability analysis guaranteed through Lyapunov’s theory using some More
This paper presents a control approach to the fuzzy-adaptive control scheme for rigid manipulators with unknown parameters. Lagrange’s method is employed for computing robot motion dynamics. Stability analysis guaranteed through Lyapunov’s theory using some suitable adaptive rules that make sure all signals in the closed-loop system are bounded and tracking error ones asymptotically reaches to zero. Compared with other controllers, there are some numerical simulations that verify effectiveness of the proposed method. Also, simulation results verify that the proposed controller can deal with uncertainties in the system.
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