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In this paper, an effective online method used for finite-horizon, nonlinear, stochastic tracking problems, is presented. The method incorporates the finite-horizon State Dependent Riccati Equation (SDRE) with Kaiman filter to account for the stochastic environment thereby extending the application spectrum to nonlinear systems and overcoming the hurdle with linear tracking systems limited to small...
In this paper, an online technique for finite-horizon nonlinear stochastic tracking problems is presented. The idea of the proposed technique is to integrate the Kalman filter algorithm and the State Dependent Riccati Equation (SDRE) technique. Unlike the ordinary methods which deal with the linearized system, this technique will estimate the unmeasured states of the nonlinear system directly, and...
This paper presents a hybrid of soft computing or control technique of adaptive neuro-fuzzy inference system (ANFIS) and hard computing or control technique of finite-time linear quadratic optimal control for the 14 degrees of freedom (DOFs), five-fingered smart prosthetic hand. In particular, ANFIS is used for inverse kinematics, and the optimal control is used for feedback linearized dynamics to...
Hard computing based optimization algorithms usually require a lot of computational resources and generally do not have the ability to arrive at the global optimum solution. Soft computing algorithms on the other hand negate these deficiencies, by allowing for reduced computational loads and the ability to find global optimal solutions, even for complex cost surfaces. This paper presents two numerical...
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