Differential Dynamic Programming for time-delayed systems

Trajectory optimization considers the problem of deciding how to control a dynamical system to move along a trajectory which minimizes some cost function. Differential Dynamic Programming (DDP) is an optimal control method which utilizes a second-order approximation of the problem to find the control. It is fast enough to allow real-time control and has been shown to work well for trajectory optimization in robotic systems. Here we extend classic DDP to systems with multiple time-delays in the state. Being able to find optimal trajectories for time-delayed systems with DDP opens up the possibility to use richer models for system identification and control, including recurrent neural networks with multiple timesteps in the state. We demonstrate the algorithm on a two-tank continuous stirred tank reactor. We also demonstrate the algorithm on a recurrent neural network trained to model an inverted pendulum with position information only.Comment: 7 pages, 6 figures, conference, Decision and Control (CDC), 2016 IEEE 55th Conference o

Solar and geothermal energy for low-carbon space heating and energy independence.

In developed countries, space heating is highly dependent on fossil fuels consumption. Also, the non-renewable fuels combustion emits CO2 which is claimed to impact the most on greenhouse effect. The utilization of Renewable Energy Sources (RES) for space heating, instead of fossil fuels, has been found to be feasible for systems’ greater energy independence and reduction in CO2 emissions. Solar Assisted Ground Source Heat Pump (SAGSHP) systems are a promising technology which can be used to accomplish the above framed target. A mathematic model of a SAGSHP system was built and a parametric analysis for Birmingham which is a city located in the UK’s West Midlands was conducted. Two scenarios based on two different dwellings were investigated, the one was a house recently erected and the other was a refurbished house. As regards the new house, simulation results showed that the utilized energy for space heating and Domestic Hot Water (DHW) can vary from 33% up to 73% RES dependent and, at the same time, electricity generation can be 2.21 times higher than the system’s demand. As regards the energy renovated dwelling, the RES contribution to the delivered heat was found to be between the 33% and 63%, while the electricity generation did not result in any surplus energy from the consumed. Finally, by making use of SAGSHP system instead of a natural Gas boiler, the reduction of CO2 emissions was found to be between 300kg/year and 2,170kg/year for the new building and from 245kg/year up to 3,221kg/year for the refurbished house, respectively. In both cases, SAGSHP systems proved to be a feasible practice for greater energy independence from non-renewable energy sources with substantial positive impact on the greenhouse gasses emissions

Safe Learning of Quadrotor Dynamics Using Barrier Certificates

To effectively control complex dynamical systems, accurate nonlinear models are typically needed. However, these models are not always known. In this paper, we present a data-driven approach based on Gaussian processes that learns models of quadrotors operating in partially unknown environments. What makes this challenging is that if the learning process is not carefully controlled, the system will go unstable, i.e., the quadcopter will crash. To this end, barrier certificates are employed for safe learning. The barrier certificates establish a non-conservative forward invariant safe region, in which high probability safety guarantees are provided based on the statistics of the Gaussian Process. A learning controller is designed to efficiently explore those uncertain states and expand the barrier certified safe region based on an adaptive sampling scheme. In addition, a recursive Gaussian Process prediction method is developed to learn the complex quadrotor dynamics in real-time. Simulation results are provided to demonstrate the effectiveness of the proposed approach.Comment: Submitted to ICRA 2018, 8 page

Polymerically Modified Layered Silicates: An Effective Route to Nanocomposites

Polymer/clay nanocomposites have been under an extensive investigation for about 15 years. Traditional methods to modify the clay are usually limited to small organic cations, preferably containing long alkyl chain(s), which are exchanged with the inorganic cations in the clay gallery. This article provides a comprehensive review on the strategies for clay modification using polymeric surfactants or polycations: from the synthesis of such surfactants, through the preparation of the polymerically modified clays, and to the fabrication of the respective polymer nanocomposites and their properties