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نتیجه جستجو - Adaptive law

تعداد مقالات یافته شده: 3
ردیف عنوان نوع
1 Nonlinear analysis and active management of production-distribution in nonlinear supply chain model using sliding mode control theory
تحلیل غیرخطی و مدیریت فعال تولید-توزیع در مدل غیر خطی زنجیره تامین با استفاده از تئوری کنترل حالت کشویی-2021
This paper deals with system dynamics approach for dynamical behaviors and control synthesis of supply chain system by utilizing three-stage production-distribution model. The presented approach offers systematic tools for determining fundamental relationships between multi-echelons in the supply chain dynamics by using eigenvalues, bifurcation, and time history investigation. By exploring system dynamics on time series analysis, it is found that system performance has suffered severely from the bullwhip effect under impacts of model uncertainties and perturbed demand. The novel fractional-order sliding mode control algorithm has been presented based on adaptation mechanism, ensuring that the shipment flows are robustly stable in supply chain networks against disruptions. This is a smarter way of getting sufficient strength to sustain existing competitive market for mitigating the risks and improving the supply chain performance. The system stability has been thoroughly analyzed by using Routh-Hurwitz criterion and Lyapunov theory. Extensive numerical simulations have been conducted to obtain insights into the system behaviors and to validate effectiveness of active control policies by matching the shipment sent to customer demand, ensuring supply chains resilience. Finally, it is found that the presented approach can help decision-makers develop more efficient supply chain management system against severe market disruptions.
Keywords: System dynamics | Supply chain management | Production-distribution model | Fractional order | Sliding mode control | Adaptive law
مقاله انگلیسی
2 Motion control of a space manipulator using fuzzy sliding mode control with reinforcement learning
کنترل حرکت یک مکانیزم فضا با استفاده از کنترل حالت کشویی فازی با یادگیری تقویتی-2020
The free-flying space manipulators present challenges in controlling the motions of both the spacecraft bus and the manipulator, because of the highly-coupling system dynamics and the unknown space environment disturbances. Although the sliding mode controllers are robust to the unknown disturbances and system uncertainties, the chattering effect could affect the pointing accuracy and the lifetime of the actuators. This paper first introduces the dynamics of a CuBot, which is a 3-rigid-link manipulator based on the CubeSat platform. To maintain the robustness while decreasing the chattering effect, an innovative reinforcement learning based fuzzy adaptive sliding mode controller is proposed. To maintain the robustness while reducing the chattering effect, an innovative reinforcement learning based fuzzy adaptive sliding mode controller is proposed. The switching gain is updated to estimate the lumped upper bound of the system uncertainties and the unknown disturbances, and then a new fuzzy logic adaptive law is applied on the switching gain to decrease the chattering effects. On top of that, the fuzzy logic rules are tuned by an innovative modified reinforcement learning mechanism to achieve the better tracking performance. The uniformly ultimately bounded tracking errors are guaranteed by the proposed control scheme, and the effectiveness is validated by the simulation results.
Keywords: CubeSat | Fuzzy logic inference | Reinforcement learning | Sliding mode control | Space manipulator
مقاله انگلیسی
3 Eigenvalue assignment enabled control law for multivariable nonlinear systems with mismatched uncertainties
انتساب مقادیر ویژه قانون کنترل فعال برای سیستم های غیر خطی چند متغیره با عدم قطعیت عدم تطابق-2020
This paper presents an adaptive filtering output feedback control architecture for multivariable nonlinear systems with mismatched uncertainties enabled by an eigenvalue assignment method. A piecewise con- stant adaptive law updates the adaptive parameters which represent the uncertainty estimates by solving the error dynamics between the output predictor and the real system with the neglection of unknowns. By employing a computationally efficient eigenvalue assignment method, the multivariable nonlinear sys- tem is transformed into Frobenius canonical form. A novel filtering control law which allows the desired system to be nonminimum-phase and does not require dynamic inversion of the desired system is de- signed to compensate the nonlinear uncertainties and track a given trajectory, following a performance determined by the eigenvalues assigned to the controller. The uniform performance bounds are derived for the system state and control input as compared to the corresponding signals of a bounded virtual reference system, which defines the best performance that can be achieved by the closed-loop system. Numerical examples are provided to illustrate the effectiveness of the eigenvalue assignment enabled control law, comparisons between the proposed controller and funnel controller are carried out.
Keywords: Eigenvalue assignment | Mismatched uncertainties | Multivariable nonlinear system | Nonminimum phase | Output feedback | Tracking
مقاله انگلیسی
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