1,721,259 research outputs found
A synthetic environment for dynamic systems control and distributed simulation
No full textRapid prototyping and controlled motion evaluation of complex human-machine interfaces require hardware-in-the-loop (HIL), man-in-the-loop (MIL), and software integration. HIL reduces the need to simulate process components and increases the likelihood of good validation results. MIL is conceptually similar to HIL. HIL and MIL are very powerful tools, but an efficient simulation environment still needs a fast and reliable communication network. Workloads must be distributed among various workstations to realize sufficient computational power
A Synthetic Environment for Simulation and Visualization of Dynamic Systems
No full textThe present paper illustrates some strategies for dynamic systems simulation. Hardware in the loop, man in the loop and software integration are key points for rapid prototyping and safe design of complex man machine interfaces, from nuclear plants operation panels to deep submerged underwater vehicles to hypersonic airplanes cockpits. Specific software appears to be needed in order to give designers tools to analyze and simulate complex integrate projects. Problems of high performance, realistic environment and vehicles simulation are addressed, with particular attention to synthetic worlds creation and visualization. A new software is presented, capable of handling most of the simulation and visualization requirements highlighted in the paper
Autonomous Formation Flight
No full textAn approach to close-formation flight of autonomous aircraft was developed. A standard LQ-based structure was synthesized for each vehicle and for formation position error control using linearized equations of motion and a lifting line model of the aircraft wake. The resultant approach provides optimal path information sequencing in the nominal case, as well as the redundancy needed to accommodate failures in data transmission and reception
Cooperative path planning and task assignment for unmanned air vehicles
No full textThis article presents a review and a novel approach to the decentralized path planning and task assignment for multiple cooperative unmanned air systems, in multiple target, and multiple task environment. The vehicles (or agents) may have complete or partial a priori information about the targets that populate the scenario. Each vehicle autonomously computes the cost for servicing each task available at each target using a path planning algorithm, taking into account obstacles, pop-up threats, and weights the total path cost including potential risk areas. Vehicles assign an initial ranking to each task, and then exchange their ranking information with the others. Each agent then updates the ranking of its tasks using a non-linear dynamic programming algorithm that is proven to be stable and to converge to an equilibrium point where each vehicle is assigned to a different task. The ranking dynamics is initially formulated as a continuous time system, and then time-discretized depending on available data, and transmission rate among the network. Stability of the network and independence of steady-state values from the data rate are evaluated analytically, and via simulation
Fast Unmanned Vehicles Task Allocation with Moving Targets
No full textThis paper presents a fast algorithm for allocation at mission-time of moving targets to a group of unmanned vehicles. A fleet of UAVs must fly through a known environment to reach partially unknown locations, or targets, where three tasks: identification, attack and verification must be performed sequentially. The total mission cost is identified to be the sum of the total times that the UAVs spend completing their tasks, while respecting the task priorities and ensuring the tasks precedence laws. The problem is solved in two steps; the first step is performed off-line and is the most computationally intensive: the environment is subdivided into triangle-shaped areas forming the Tessellation Graph (TG), and the shortest path between each two vertexes couples of the plane is computed using the All-Pairs-Nodes Dijkstra algorithm. The second step, at mission-time, regards management of moving targets and adaptation to the results of the identification phase. Optimal task assignment is performed using the Hungarian algorithm; exact path lengths between vehicles and targets are computed from the off-line computed Dijkstra paths. One parameter is available to tune the optimal task allocation algorithm with respect to desired aggressive/selfish or cooperative behavior
Sliding mode control for two-time scale systems: stability issues
No full textThe paper presents some results on global exponential stability of linear time invariant systems with different time scales. The full system is decomposed in two reduced ones by means of singular perturbations and a smooth approximation of a Variable Structure Control is synthesized for each of them using Reaching Law approach. The global closed loop stability is then proved for the whole system using Lyapunov methods and a particular state space decomposition. Moreover a literal form for E-* (a parameter which measures the minimum separation between time scales) is derived
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