This work investigates the consensus problem for multi-agent nonlinear systems through the distributed real-time nonlinear receding horizon control methodology. With this work, we develop a scheme to reach the consensus for nonlinear multi agent systems under fixed directed/undirected graph(s) without the need of any linearization techniques. For this purpose, the problem of consensus is converted into an optimization problem and is directly solved by the backwards sweep Riccati method to generate the control protocol which results in a non-iterative algorithm. Stability analysis is conducted to provide convergence guarantees of proposed scheme. In addition, an extension to the leader-following consensus of nonlinear multi-agent systems is presented. Several examples are provided to validate and demonstrate the effectiveness of the presented scheme and the corresponding theoretical results.

This paper discusses the creation of a genetic algorithm to locate and optimize interplanetary trajectories using gravity assist maneuvers to improve fuel efficiency of the mission. The algorithm is implemented on two cases: (i) a Centaur-class target close to the ecliptic plane and (ii) a Centaur-class target with a high inclination to the ecliptic plane. Cases for multiple numbers of flybys (up to three) are discussed and compared. It is shown that, for the targets considered here, a single flyby of Jupiter is the most efficient trajectory to either target with the conditions and limitations discussed in this paper. In this paper, we also iterate on possible reasons for certain results seen in the analysis and show how these previously observed behaviors could be present in any trajectory found. The parameters and methods used in the algorithm are explained and justified over multiple real-life interplanetary missions to provide deeper insights into the development choices.

The vertical stabilizer is the key aerodynamic surface that provides an aircraft with its directional stability characteristic while ailerons and rudder are the primary control surfaces that give pilots control authority of the yawing and banking maneuvers. Losing the vertical stabilizer will, therefore, result in the consequential loss of lateral/directional stability and control, which is likely to cause a fatal crash. In this paper, we construct a scenario of a damaged aircraft model which has no physical rudder control surface, and then a strategy based on differential thrust is proposed to be utilized as a control input to act as a "virtual" rudder to help maintain stability and control of the damaged aircraft. The H∞ loop-shaping approach based robust control system design is implemented to achieve a stable and robust flight envelope, which is aimed to provide a safe landing. Investigation results demonstrate successful application of such robust differential thrust methodology as the damaged aircraft can achieve stability within feasible control limits. Finally, the robustness analysis results conclude that the stability and performance of the damaged aircraft in the presence of uncertainty remain within desirable limits, and demonstrate not only a robust, but a safe flight mission through the proposed H∞ loop-shaping robust differential thrust control methodology.

This paper presents a novel framework which combines a non-iterative solution of Real-Time Nonlinear Receding Horizon Control (NRHC) methodology to achieve consensus within complex network topologies with existing timedelays and in presence of switching topologies. In this formulation, we solve the distributed nonlinear optimization problem for multi-agent network systems directly, in real-time, without any dependency on iterative processes, where the stability and convergence guarantees are provided for the solution. Three benchmark examples on non-linear chaotic systems provide validated results which demonstrate the significant outcomes of such methodology.

This paper discusses the creation of a genetic algorithm to locate and optimize interplanetary trajectories using gravity assist maneuvers to improve fuel efficiency of the mission. The algorithm is implemented on two cases: (i) a Centaur-class target close to the ecliptic plane and (ii) a Centaur-class target with a high inclination to the ecliptic plane. Cases for multiple numbers of flybys (up to three) are discussed and compared. It is shown that, for the targets considered here, a single flyby of Jupiter is the most efficient trajectory to either target with the conditions and limitations discussed in this paper. In this paper, we also iterate on possible reasons for certain results seen in the analysis and show how these previously observed behaviors could be present in any trajectory found. The parameters and methods used in the algorithm are explained and justified over multiple real-life interplanetary missions to provide deeper insights into the development choices.