This paper describes the control of quadcopter that is resistant to collisions with obstacles using Monte Carlo model predictive control (MCMPC). MCMPC is a kind of model predictive control that uses Monte Calro Method to derive the optimal control. MCMPC performs only forward simulations and does not require a gradient of the cost function, hence allowing discontinuous phenomena such as collisions with obstacles to be included in the prediction model. This paper proposes the MCMPC controller that considers impact force by the collision with a wall and minimizes position and attitude errors of a quadcopter when the collision is unavoidable.
It is expected that relatively large amount of data relating to new applications, e.g. visual sensing, AI and collaboration between systems, are handled in control system networks as well as conventional real-time control data. Time-Sensitive Networking (TSN) can be one of the solutions for such coexistence of real-time and non-real-time data. On the other hand, such control system networks may be exposed to larger threats to cybersecurity under the “System of systems” architecture concepts. We propose “Real-time firewall (RT-FW) for TSN”, which can examine TSN protocol frames with filtering rule, maintaining low latency communication. It is necessary for “RT-FW for TSN” that the TSN's low-latency feature, e.g. frame priorities and preemption of high priority frame, are properly handled in frame examination functionality. We have implemented the RT-FW for TSN using FPGA and confirmed that 1) the mentioned requirements are fulfilled with frame filtering and 2) the filtering latency is almost constant at maximum of 2.12µs regardless of frame length.
The study aims to investigate how networks within and outside of an organization affect individual performance and gain insight into performance management within organizations. An online survey was conducted with two project management teams from different companies to calculate network indicators through social and multilayer network analysis. Psychological safety and knowledge/information sharing are adapted to measure performance. The results indicate the higher performance of psychological safety can be achieved through having an asymmetry of ties: cohesive ties are better for relatively close relations such as teams and inter-team networks and bridging ties for inter-team networks. On the other hand, bridging ties more affect the performance of knowledge/information sharing.
In this paper, we consider a controller tuning method of the Smith compensator for multi-input and multi-output (MIMO) systems with both input delays and output delays. Particularly, we discuss on the application of Fictitious Reference Iterative Tuning (FRIT), which is one of the data-driven controller update methods utilizing one-shot experimental data. To apply FRIT to systems where both input and output have time delays, we introduce a specific structure of the Smith compensator with tunable parameters. In addition, we consider the meaning of the cost function used in the proposed method. Finally, we illustrate a numerical example to show the validity and the effectiveness of the proposed method.