The next generation of high-power lasers enables repetition of experiments at orders of magnitude higher frequency than what was possible using the prior generation. Facilities requiring human intervention between laser repetitions need to adapt in order to keep pace with the new laser technology. A distributed networked control system can enable laboratory-wide automation and feedback control loops. These higher-repetition-rate experiments will create enormous quantities of data. A consistent approach to managing data can increase data accessibility, reduce repetitive data-software development and mitigate poorly organized metadata. An opportunity arises to share knowledge of improvements to control and data infrastructure currently being undertaken. We compare platforms and approaches to state-of-the-art control systems and data management at high-power laser facilities, and we illustrate these topics with case studies from our community.

Backstepping represents a promising control law for fixed-wing Unmanned Aerial Vehicles (UAVs). Its non-linearity and its adaptation capabilities guarantee adequate control performance over the whole flight envelope, even when the aircraft model is affected by parametric uncertainties. In the literature, several works apply backstepping controllers to various aspects of fixed-wing UAV flight. Unfortunately, many of them have not been implemented in a real-time controller, and only few attempt simultaneous longitudinal and lateral–directional aircraft control. In this paper, an existing backstepping approach able to control longitudinal and lateral–directional motions is adapted for the definition of a control strategy suitable for small UAV autopilots. Rapidly changing inner-loop variables are controlled with non-adaptive backstepping, while slower outer loop navigation variables are Proportional–Integral–Derivative (PID) controlled. The controller is evaluated through numerical simulations for two very diverse fixed-wing aircraft performing complex manoeuvres. The controller behaviour with model parametric uncertainties or in presence of noise is also tested. The performance results of a real-time implementation on a microcontroller are evaluated through hardware-in-the-loop simulation.

Responding to growing concerns regarding energy-efficient facades, this paper describes the structure and process followed in the design of a responsive sun-shading system based on the use of rotating plates with two degrees of freedom. The proposal considers, among others, the definition of variable design parameters, areas of performance evaluation and control, and construction detailing development represented by a first 1:2 unit (module) model. In the process, computational simulation procedures were employed to explore configurational possibilities that would provide high-performance solutions to the light requirements of the particular covered spaces. In developing the system, it was noticed that due to the highly subjective requirements of users in terms of quantity and quality of lighting, a purely Boolean control system would not always be appropriate. Following from that, and taking advantage of the dynamic nature of the system, a further approach of control supported by fuzzy logic was also implemented at the operative state, whose logic is explained. Digital simulations were carried out to assess the performance of the system, and their results demonstrate more even light distribution levels compared to traditional systems.

Prior research has suggested a number of potential benefits to firm membership in business groups. These benefits include availability of capital and other resources not readily accessible in an open market, the facilitation of entrepreneurship, plus information and risk sharing advantages. We suggest that another important benefit is the assistance of group control systems in helping the firm to manage conflicting pressures in the institutional environment and facilitate coevolution of these conflicting pressures. To empirically demonstrate the relevance of this viewpoint, we examine the case of China where business groups facilitate institutional transition, actively balancing market pressures to increase levels of innovativeness in firms with institutional pressures emanating from the government to maintain high employment levels. Using data from a broad sample of more than 1,000 Chinese affiliate firms in more than 200 business groups, we find that government policy, ownership and managerial mindset influence the political goal of maintaining high employment levels, while interdependence among group affiliate firms is related to lower employment levels. However, while government ownership and the government managerial mindset were negatively related to market innovation activities, group financial and cultural control systems positively affected the tendency of affiliate firms to focus on market innovation.

Geometric control theory and Riemannian techniques are used to describe the reachable set at time t of left invariant single-input control systems on semi-simple compact Lie groups and to estimate the minimal time needed to reach any point from identity. This method provides an effective way to give an upper and a lower bound for the minimal time needed to transfer a controlled quantum system with a drift from a given initial position to a given final position.The bounds include diameters of the flag manifolds; the latter arealso explicitly computed in the paper.

Neuroevolution, or evolving neural networks with evolution algorithms such as genetic algorithms, is becoming one of the hottest areas in hybrid systems research. One of the areas that become under research using neuroevolutions is the controllers. In this paper, we shall present two engineering controllers based on neuroevolutions techniques. One of the controllers is used to monitor the temperature and humidity in an industry. This controller is having a linear behavior. The second controller is concerned with scheduling parts in queues in an industry. The scheduling controller is having a nonlinear behavior. The results obtained by the proposed controllers based on neuroevolution are compared with results obtained by traditional methods such as neural networks with backpropagation and ordinary simulation for the controller. The results show that the neuroevolution approaches outperform the results obtained by other methods.

Control systems of robot manipulators offer many challenges in education where the students must learn robot dynamics and control structures, and understand relations between the control parameters and the systems performance. Interactive simulation is aimed at improving the understanding of and intuition for the abstract parts of the control of robot courses. This paper presents an application of interactive simulation to teach control systems of robots. The application considers a nonlinear robot arm and two control modules: position control and motion control. Students can directly manipulate graphical representation of the systems such as a choice among seven control structures, controller gains, and desired trajectories, and obtain instant feedback on the effects. These features make the interactive learning tool stimulating and of high pedagogical value.

This paper deals with the problem of stabilizing a system in the presence of small measurement errors. It is known that, for general stabilizable systems, there may be no possible memoryless state feedback which is robust with respect to such errors. In contrast, a precise result is given here, showing that, if a (continuous-time, finite-dimensional) system is stabilizable in any way whatsoever (even by means of a dynamic, time varying, discontinuous, feedback) then it can also be semiglobally and practically stabilized in a way which is insensitive to small measurement errors, by means of a hybrid strategy based on the idea of sampling at a “slow enough” rate.