Neural Network-Based Model Predictive Control: Fault Tolerance and Stability - 2015


This brief deals with nonlinear model predictive control designed for a tank unit. The predictive controller is realized by suggests that of a recurrent neural network, which acts as a one-step ahead predictor. Then, based on the neural predictor, the control law comes solving an optimization drawback. An vital issue in management theory is stability of the management system. During this transient, this problem is investigated by showing that a price operate is monotonically decreasing with respect to time. The derived stability conditions are then used to redefine a constrained optimization problem in order to calculate a management signal. As the automated management system can prevent faults from being observed, the management system is supplied with a fault diagnosis block. It is realized by suggests that of a multivalued diagnostic matrix, which is determined on the premise of residuals calculated employing a set of partial models. Each partial model is designed in the shape of a recurrent neural network. This temporary proposes also a technique of compensating sensor, actuator, and method faults. When a sensor fault is isolated, the system estimates its size and, based mostly on this info, the controller is fed with a determined, close to real, tank level price. Actuator and process faults will be compensated thanks to application of an unmeasured disturbance model.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : NCF: A Neural Context Fusion Approach to Raw Mobility Annotation ABSTRACT: Improving business intelligence in mobile environments requires a thorough comprehension of human mobility patterns on a point-of-interest
PROJECT TITLE : Graph Neural Network for Fraud Detection via Spatial-temporal Attention ABSTRACT: Card fraud is a significant problem that results in significant financial losses for cardholders as well as the banks that issue
PROJECT TITLE : CNN-LSTM: Hybrid Deep Neural Network for Network Intrusion Detection System ABSTRACT: The importance of network security to our day-to-day interactions and networks cannot be overstated. The importance of having
PROJECT TITLE : Traffic Anomaly Detection in Wireless Sensor Networks Based on Principal Component Analysis and Deep Convolution Neural Network ABSTRACT: Because of the proliferation of wireless networks, wireless sensor networks
PROJECT TITLE : The Devil Is in the Details An Efficient Convolutional Neural Network for Transport Mode Detection ABSTRACT: The objective of the classification problem known as transport mode detection is to devise an algorithm

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry