In this paper we have designed and implemented a predictive automatic flight controller for an airplane that takes as input the estimated pose obtained from the visual data and provides control outputs for an inner-loop augmented aircraft. In order to make the predictive controller suitable for flight control, it had to be modified. The most important modification was the introduction of the sh...

This paper is concerned with the design of Direct Adaptive Model Based Predictive Control (DAMBPC) using subspace identification technique to identify and implement the controller parameters. The direct identification of controller parameters reduces the design effort and computation load which is usually involved with classical adaptive control techniques. The proposed method requires a single...

In this paper, a hybrid predictive controller is proposed for a class of uncertain switched nonlinear systems based on high-order differential state observers and Lyapunov functions. The main idea is to design an output feedback bounded controller and a predictive controller for each subsystem using high-order differential state observers and Lyapunov functions, to derive a suitable switched la...

The paper presents an advanced control strategy that uses the neural network predictive controller and the fuzzy controller in the complex control structure with an auxiliary control variable. The controlled tubular heat exchanger was used for pre-heating of petroleum by hot water. The heat exchanger was modelled as a nonlinear system with interval parametric uncertainty. The set point tracking...

With an increase in power transfer, transient stability is increasingly becoming important for secure operation. With the advent of FACTS devices, the problem of transient stability is being addressed and efforts are under way to utilize the systems to their full capacity. The focus of this work is a neural network predictive controller for a versatile FACTs device, Unified Power Flow Controlle...

During the last decade, there has been a growing interest in developing nonlinear model-based control methods. This interest has led to substantial progress mainly within the two frameworks of model predictive control (MPC) and differential geometric control. MPC is an optimization-based control methodology which explicitly accounts for process constraints and in general leads to a controller w...

In this paper, we present a model predictive controller to reduce road traffic congestion in freeway networks. The model predictive controller regulates traffic in the freeway through the use of ramp metering and variable speed limits. The controller uses a Link-Node Cell transmission model (LN-CTM) to represent freeway dynamics. We modify the standard LN-CTM to account for the capacity drop ph...

In this work, a model predictive control method combined with fuzzy identification, is applied to the design of the thermoelectric (TE) power control in the SP-100 space reactor. The future TE power is predicted by using the fuzzy model identified by a subtractive clustering method of a fast and robust algorithm. The objectives of the proposed fuzzy model predictive controller are to minimize b...

The increasing complexity of Cyber Physical Systems (CPS) found in a variety of domains, and the unforeseen fluctuations in operating conditions caused by the open nature of these systems makes it significantly challenging to appropriately configure and adapt the operating parameters of CPS to ensure reliability and desired quality-of-service (QoS). Material handling and packaging is one such d...

the present sought to draw a comparison between model predictive control performance and two other controllers named simple pi and selective pi in controlling large-scale natural gas transport networks. a nonlinear dynamic model of representative gas pipeline was derived from pipeline governing rules and simulated in simulink® environment of matlab®. control schemes were designed to provide a s...