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It is shown by examples that using the dynamics of one of the modes to obtain the control law based on the SMC approach gives satisfactory closed loop performance for the other mode as well.
We describe in Section 3.1 the core of the general specialization framework based on the SMC filter.
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In this paper, we propose a novel implementation of the probability hypothesis density (PHD) filter based on the sequential Monte Carlo (SMC) method called SMC-PHD filter.
Control mechanism based on classical SMC is designed and compared with the super twisting control algorithm which is based on the higher order SMC.
In this paper, we explore and compare two sampling alternatives, one based on the principles of DA-SMC methods and another where importance sampling (IS) of the parameters is carried out.
Based on the combination of the SMC with fuzzy control, this paper presents a new and feasible design algorithm to synthesize a robust fuzzy sliding mode controller which can easily tackle the stabilizing and tracking problem of a class of MIMO nonlinear systems in the presence of uncertainties and external disturbance.
Based on the anisotropy of SMCs, the shear wave speed along the fiber could be significantly higher than that across the fiber.
Based on the above-mentioned linearization, the SMC method can then be used to design the controller of the vehicle height and leveling adjustment system of EAS.
In the first place, this paper proposes two adaptive nonlinear control algorithms based on the sliding mode control (SMC), which are designed for small satellite attitude control system.
In this research work closed loop control algorithm is proposed based on the sliding mode control (SMC) for type 1 diabetes patient.
Based on the sliding mode control (SMC) theory, a discontinuous attitude control law in the form of the input voltage of the reaction wheel is derived to control the orientation of the spacecraft, incorporating the L2-gain performance criterion constraint.
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