Direct Adaptive Soft Computing Neural Control of a Continuous Bioprocess via Second Order Learning
نویسندگان
چکیده
. Abstrad This paper proposes a new Kalman Filter Recurrent Neural Network (I0 topology and a recursive Levenberg-Marquardt (L-M) second order learning algorithm capable to estimate parameters and states of highly nonlinear bioprocess in a noisy environment The proposed KFRNN identifier, learned by the Backpropagation and L-M learning algorithm, was incorporated in a direct adaptive neural control scheme. The proposed control scheme was applied for redealtime soft computing identification and control of a continuous stirred tank bioreactor model, where fast convergence, noise filtering and low mean squared error of reference tracking were achieved.
منابع مشابه
Direct and Indirect Neural Identification and Control of a Continuous Bioprocess via Marquardt Learning
This paper applied a new Kalman Filter Recurrent Neural Network (KFRNN) topology and a recursive Levenberg-Marquardt (L-M) learning algorithm capable to estimate parameters and states of highly nonlinear unknown plant in noisy environment. The proposed KFRNN identifier, learned by the Backpropagation and L-M learning algorithm, was incorporated in a direct and indirect adaptive neural control s...
متن کاملDecentralized Adaptive Fuzzy-Neural Control of an Anaerobic Digestion Bioprocess Plant
The paper proposed to use recurrent Fuzzy-Neural Multi-Model (FNMM) identifier for decentralized identification of a distributed parameter anaerobic wastewater treatment digestion bioprocess, carried out in a fixed bed and a recirculation tank. The distributed parameter analytical model of the digestion bioprocess is used as a plant data generator. It is reduced to a lumped system using the ort...
متن کاملA Hybrid Neural Network Approach for Kinematic Modeling of a Novel 6-UPS Parallel Human-Like Mastication Robot
Introduction we aimed to introduce a 6-universal-prismatic-spherical (UPS) parallel mechanism for the human jaw motion and theoretically evaluate its kinematic problem. We proposed a strategy to provide a fast and accurate solution to the kinematic problem. The proposed strategy could accelerate the process of solution-finding for the direct kinematic problem by reducing the number of required ...
متن کاملRobot Motion Control
This paper considers the problem of the robot motion control in the presence of the major uncertainties such as it is varying load. Efficiency of one conventional and two soft computing model based control algorithms is investigated and compared trough the results of application on a direct drive robot. First control algorithm is a conventional computed torque based on the Lagrangian dynamic eq...
متن کاملAdaptive Quaternion Attitude Control of Aerodynamic Flight Control Vehicles
Conventional quaternion based methods have been extensively employed for spacecraft attitude control where the aerodynamic forces can be neglected. In the presence of aerodynamic forces, the flight attitude control is more complicated due to aerodynamic moments and inertia uncertainties. In this paper, a robust nero-adaptive quat...
متن کامل