Influence of thermal radiation on non-Darcian natural convection in a square cavity filled with fluid saturated porous medium of uniform porosity

Influence of thermal radiation on natural-convection flow in a square cavity filled with a porous medium of uniform porosity having isothermal vertical walls and adiabatic horizontal walls, has been studied numerically by using finite-difference method with staggered grid distribution. The simulation is performed by considering both Darcian and non-Darcian models. Governing momentum and energy equations are solved numerically to obtain velocity and temperature fields for various values of different physical parameters. It is seen that increasing the thermal radiation parameter enhances the local Nusselt number on the left vertical wall whereas the reverse effects are observed due to increase in the heat generating parameter when Ra = 109. The temperature at the mid-horizontal plane decreases with increase in the value of Rayleigh number up to a certain distance from the left vertical wall and beyond that distance the opposite trend is observed. The temperature at the mid-horizontal plane increases with increase in the value of heat generating parameter

Weakly Nonlinear Stability Analysis of a Nanofluid in a Horizontal Porous Layer Using a Multidomain Spectral Collocation Method

In this chapter, we present a weakly nonlinear stability analysis of the flow of a nanofluid in a porous medium with stress-free boundary conditions. Some previous studies have investigated cross-diffusion in a nanofluid layer although in most cases these studies mostly deal with linear stability analysis. It is important to study the nonlinear stability in flows subject to cross-diffusion due to the wide range of applications where such flows arise such as in hydrothermal growth, compact heat exchanges, the solidification of binary mixtures, geophysical systems, solar pond, etc. Here we consider flow between parallel plates with an applied magnetic field and zero nanoparticle flux at the boundaries. A truncated Fourier series is introduced reducing the flow equations to a Lorenz-type system of nonlinear evolution equations. The multidomain spectral method is used to solve the equations that describe the growth of the convection amplitudes. The solutions are obtained as sets of trajectories in the phase space. Some interesting spiral trajectories and their sensitivity to the Rayleigh number are given

Neuro-adaptive augmented distributed nonlinear dynamic inversion for consensus of nonlinear agents with unknown external disturbance

This paper presents a novel neuro-adaptive augmented distributed nonlinear dynamic inversion (N-DNDI) controller for consensus of nonlinear multi-agent systems in the presence of unknown external disturbance. N-DNDI is a blending of neural network and distributed nonlinear dynamic inversion (DNDI), a new consensus control technique that inherits the features of Nonlinear Dynamic Inversion (NDI) and is capable of handling the unknown external disturbance. The implementation of NDI based consensus control along with neural networks is unique in the context of multi-agent consensus. The mathematical details provided in this paper show the solid theoretical base, and simulation results prove the effectiveness of the proposed scheme.Engineering and Physical Sciences Research Council (EPSRC): EP/R009953/1

Fault-tolerant consensus of nonlinear agents considering switching topology in the presence of communication noise

In this paper, the consensus of nonlinear multi-agent systems (MASs) is discussed, considering actuator fault and switching topology in the presence of communication noise. The actuator fault and communication noise are both considered to be random. The switching of the topologies is considered random as well. These issues are handled by Distributed Nonlinear Dynamic Inversion (DNDI), which is designed for Multi-Agent Systems (MASs) operation. The convergence proof with actuator fault is provided, which shows the robustness of the controller. The simulation results show that DNDI successfully dealt with the actuator fault and communication events simultaneously

Bipartite consensus of nonlinear agents in the presence of communication noise

In this paper, a Distributed Nonlinear Dynamic Inversion (DNDI)-based consensus protocol is designed to achieve the bipartite consensus of nonlinear agents over a signed graph. DNDI inherits the advantage of nonlinear dynamic inversion theory, and the application to the bipartite problem is a new idea. Moreover, communication noise is considered to make the scenario more realistic. The convergence study provides a solid theoretical base, and a realistic simulation study shows the effectiveness of the proposed protocol.Engineering and Physical Sciences Research Council (EPSRC): EP/R009953/

Autonomous addition of agents to an existing group using genetic algorithm

This paper presents an idea of how new agents can be added autonomously to a group of existing agents without changing the existing communication topology among them. Autonomous agent addition to existing Multi-Agent Systems (MASs) can give a strategic advantage during the execution of a critical beyond visual line-of-sight (BVLOS) mission. The addition of the agent essentially means that new connections with existing agents are established. It is obvious that the consensus control energy increases as the number of agent increases considering a specific consensus protocol. The objective of this work is to establish the new connections in a way such that the consensus energy increase due to the new agents is minimal. The updated topology, including new connections, must contain a spanning tree to maintain the stability of the MASs network. The updated optimal topology is obtained by solving minimum additional consensus control energy using the Two-Dimensional Genetic Algorithm. The results obtained are convincin

Optimal topology for consensus using genetic algorithm

In the Multi-Agent Systems (MAS), graph network topologies play a crucial role in building consensus among the connected agents. Consensus may be achieved on many network graphs using distributed control theory. However, the optimal network topology is not addressed in most of the literature, which is an important part of building stable consensus among networked agents. In this paper, the optimal topology is obtained irrespective of the agent dynamics by using two-dimensional Genetic Algorithm (GA), which is a new approach in this context. Simulation result for agents with first, and second-order linear dynamic is obtained. These results show that the proposed method achieves consensus using the optimal network topology satisfactorily

Two-dimensional quantum genetic algorithm: application to task allocation problem

This paper presents a Two-Dimensional Quantum Genetic Algorithm (2D-QGA), which is a new variety of QGA. This variety will allow the user to take the advantages of quantum computation while solving the problems which are suitable for two-dimensional (2D) representation or can be represented in tabular form. The performance of 2D-QGA is compared to two-dimensional GA (2D-GA), which is used to solve two-dimensional problems as well. The comparison study is performed by applying both the algorithm to the task allocation problem. The performance of 2D-QGA is better than 2D-GA while comparing execution time, convergence iteration, minimum cost generated, and population size

Constrained quasi-spectral MPSP with application to high-precision missile guidance with path constraints

This paper extends the recently developed quasi-spectral model predictive static programming (QS-MPSP) to include state and control path-constraints and yet retain its computational efficiency. This is achieved by (i) formulating the entire problem in the control variables alone by (a) converting the system dynamics to an equivalent algebraic constraint and (b) converting the state constraints to equivalent control constraints, both of which is done by manipulating the system dynamics, (ii) representing the control variables in Quasi-spectral form, which makes the number of free-variables independent of time-grids and (iii) using a computationally efficient optimization algorithm to solve this low-dimensional problem. This generic computationally efficient technique is utilized next as an effective lead angle, and lateral acceleration constrained optimal missile guidance to intercept incoming high-speed ballistic targets with high precision successfully. Both of these constraints, as well as near-zero miss-distance, are of high practical significance for this challenging problem. Extensive three-dimensional simulation studies show the effectiveness of the newly proposed constrained QS-MPSP guidance algorithm. Six degrees-of-freedom simulation studies have also been carried out using autopilot in the loop to validate the results more realistically