Semitransparent front electrodes for polymer solar cells, that are printable and roll-to-roll processable under ambient conditions using different approaches, explored in this report. The excellent smoothness of indium-tin-oxide (ITO) has traditionally been believed to be difficult achieve printed grids, as surface topographies accumulate when processing subsequent layers, leading shunts between the top bottom metallic electrodes. Here we demonstrate how aqueous nanoparticle based silver...

Consensus of a group agents in multi-agent system with and without leader is considered. All are modelled by identical linear n-th order dynamical systems while the leader, when it exists, may evolve according to different model same order. The interconnection topology between as directed weighted graph. We provide answers questions whether converges consensus what value eventually reaches. To that end, we give detailed analysis relevant algebraic properties graph Laplacian. Furthermore,...

This brief proposes a cascade voltage control strategy for the dc/dc converter utilizing model predictive (MPC) in inner loop. The proposed MPC minimizes cost function at each time step receding horizon manner and corresponding optimal solution is obtained from predefined not relying on numeric algorithm. It shown that makes capacitor inductor current globally convergent presence of input constraints. State constraints also can be taken into account MPC. Following conventional scheme,...

In order to enhance performance of robot systems in the manufacturing industry, it is essential develop motion and task planning algorithms. Especially, important for plan be generated automatically deal with various working environments. Although PRM (Probabilistic Roadmap) provides feasible paths when starting goal positions a manipulator are given, path might not smooth enough, which can lead inefficient system. This paper proposes algorithm manipulators using twin delayed deep...

Since path planning for multi-arm manipulators is a complicated high-dimensional problem, effective and fast generation not easy the arbitrarily given start goal locations of end effector. Especially, when it comes to deep reinforcement learning-based planning, high-dimensionality makes difficult existing methods have efficient exploration which crucial successful training. The recently proposed soft actor-critic (SAC) well known good ability due use entropy term in objective function....

This technical note studies robustness of synchronization against heterogeneity multi-agent systems. Here, also includes uncertainties and external disturbances in each agent. In order to effectively deal with the heterogeneous agents, we introduce concept averaged dynamics which is average all agents' dynamics, then claim that two sources enhance synchronized behavior dynamics. First, spite show strong coupling among agents makes trajectories arbitrarily close Second, effect variations...

This note proposes a dynamic controller for practical coordinated tracking of uncertain heterogeneous multi-agent systems. The agents are high-order linear systems subject to external disturbances and plant uncertainties, the input leader is not known other agents, network topology time-varying. We adopt recently developed reduced-order disturbance observer present distributed which uses only relative measurements. It shown that proposed can be tuned ensure ultimate boundedness error chosen...

In this study, an output-feedback model predictive controller (MPC) is presented for capacitor voltage regulation on the basis of a non-linear DC/DC converter. The proposed MPC scheme constructed by combining state-feedback with Luenberger-type observer. does not carry out any online optimisation. Although converter non-linear, observer gain ensures global exponential convergence state estimation errors. On observer, designed certainty equivalence. It also shown that globally converges to...

This paper presents a deep reinforcement learning-based path planning algorithm for the multi-arm robot manipulator when there are both fixed and moving obstacles in workspace. Considering problem properties such as high dimensionality continuous action, proposed employs SAC (soft actor-critic). Moreover, order to predict explicitly future position of obstacle, LSTM (long short-term memory) is used. The SAC-based developed using LSTM. In show performance algorithm, simulation results GAZEBO...

This article presents a complex gain margin of discrete-time linear quadratic regulator (DLQR) and its application to consensus problem multi-agent higher order systems. Since the can be converted into robust control with perturbation expressed by numbers, since classical phase margins are not enough handle current case, we study so-called 'disc margin' which is somehow combination margins. We first compute disc DLQR controller based on Lyapunov argument, simple but yields relaxed result...

In the workspace of robot manipulators in practice, it is common that there are both static and periodic moving obstacles. Existing results literature have been focusing mainly on This paper concerned with multi-arm periodically Due to high-dimensional property obstacles, existing suffer from finding optimal path for given arbitrary starting goal points. To solve planning problem, this presents a SAC-based (Soft actor–critic) algorithm particular, deep neural networks SAC designed such they...

This paper proposes an optimal Energy Storage System (ESS) scheduling algorithm Building Management (BEMS). In particular, the focus is placed on how to reduce peak load using ESS and forecast. To this end, first, existing deep learning-based forecast method applied a real building energy prediction it shown that leads accuracy-enhanced Second, optimization problem formulated in order devise scheduling. problem, objective function constraints are defined such reduced; cost for electricity...

The quadruped robot has to assess the feasibility of upcoming terrains before making contact safely traverse various environments. This assessment is called traversability in literature on robots. Trasversability recently posed challenges due a high-dimensional system that leads long computational times. Furthermore, exteroceptive observations often suffer from noise potentially causes misinterpretations and results an inaccurate assessment. paper proposes robust predictor tackle these...

This paper presents a robust tracking model predictive control (MPC) strategy for offset-free regulation of the output input-constrained uncertain systems to non-zero reference signal. To this end, feedback law with integral action is proposed, and feasible invariant set explicitly derived on basis law. Finally, one-step-ahead MPC devised in order improve performance. Simulation results show that proposed successfully achieves terms both performance size set.

Reinforcement learning (RL) trains an agent by maximizing the sum of a discounted reward. Since discount factor has critical effect on performance RL agent, it is important to choose properly. When uncertainties are involved in training, with constant can be limited. For purpose obtaining acceptable consistently, this paper proposes adaptive rule for based advantage function. Additionally, how use function both on-policy and off-policy algorithms presented. To demonstrate proposed rule,...

Reheating furnaces in iron and steel industry are main facilities of hot charge rolling processes. The objective such a reheating furnace is to control billet temperature uniformly, thereby resulting successful process performance high productivity. In this paper, dynamic model the derived using material energy balances. A multivariable controller design procedure then presented on basis system identification technique predictive algorithm. Simulations show effectiveness proposed scheme.

This paper presents a coordinated tracking controller for multi-agent systems. We assume that agents are uncertain, nonidentical, and affected by external disturbances. The information available to the is weighted sum of relative measurements. A based on disturbance observer, which known as robust output feedback controller, designed so disturbances acting attenuated at same time measurements approximately satisfies differential equation defined leader's dynamics, results in practical...