Adaptive Optimal Output Regulation of Interconnected Singularly Perturbed Systems With Application to Power Systems

This article studies the adaptive optimal output regulation problem for a class of interconnected singularly perturbed systems(SPSs) with unknown dynamics based on reinforcement learning(RL).Taking into account the slow and fast characteristics among system states,the interconnected SPS is decomposed into the slow time-scale dynamics and the fast timescale dynamics through singular perturbation theory.For the fast time-scale dynamics with interconnections,we devise a decentralized optimal control strategy by selecting appropriate weight matrices in the cost function.For the slow time-scale dynamics with unknown system parameters,an off-policy RL algorithm with convergence guarantee is given to learn the optimal control strategy in terms of measurement data.By combining the slow and fast controllers,we establish the composite decentralized adaptive optimal output regulator,and rigorously analyze the stability and optimality of the closed-loop system.The proposed decomposition design not only bypasses the numerical stiffness but also alleviates the high-dimensionality.The efficacy of the proposed methodology is validated by a load-frequency control application of a two-area power system.

Distributed Adaptive Fault-Tolerant Output Regulation of Heterogeneous Multi-Agent Systems With Coupling Uncertainties and Actuator Faults

In this paper, we consider the distributed adaptive fault-tolerant output regulation problem for heterogeneous multiagent systems with matched system uncertainties and mismatched coupling uncertainties among subsystems under the influence of actuator faults. First, distributed finite-time observers are proposed for all subsystems to observe the state of the exosystem. Then, a novel fault-tolerant controller is designed to compensate for the influence of matched system uncertainties and actuator faults. By using the linear matrix inequality technique, a sufficient condition is provided to guarantee the solvability of the considered problem in the presence of mismatched coupling uncertainties. Moreover, it is shown that the system in closed-loop with the developed controller can achieve output regulation by using the Lyapunov stability theory and cyclic-small-gain theory.Finally, a numerical example is given to illustrate the effectiveness of the obtained result.

Data-Driven Global Robust Optimal Output Regulation of Uncertain Partially Linear Systems

In this paper, a data-driven control approach is developed by reinforcement learning (RL) to solve the global robust optimal output regulation problem (GROORP) of partially linear systems with both static uncertainties and nonlinear dynamic uncertainties. By developing a proper feedforward controller, the GROORP is converted into a global robust optimal stabilization problem. A robust optimal feedback controller is designed which is able to stabilize the system in the presence of dynamic uncertainties. The closed-loop system is ensured to be input-to-output stable regarding the static uncertainty as the external input. This robust optimal controller is numerically approximated via RL. Nonlinear small-gain theory is applied to show the input-to-output stability for the closed-loop system and thus solves the original GROORP. Simulation results validates the efficacy of the proposed methodology.

A novel inflatable rings supported design and buoyancy-weight balance deformation analysis of stratosphere airships

Owing to the unique advantages in flight altitude,dwelling time and wide coverage area,stratospheric airships provide permanent monitoring and surveillance for both civil and military applications.Here we propose a semi-rigid stratosphere airship design with circumferential high-pressure inflatable rings and a longitudinal carbon fiber skeleton supported inside.We perform numerical simulations to analyze the deformation characteristics during the whole ascending and descending process.An equivalent internal gradient pressure model of helium is established based on the capsule shape and buoyancy-weight equilibrium conditions.The implicit dynamic method is used to deal with the large deformation of the airship capsule under a low negative pressure condition.Deformation and load-bearing performance of the airship capsule,inflatable ring,skeleton,and suspension line are obtained under different working conditions.The results show that the airship,supported with the inflatable rings and the suspension lines,effectively maintains the shape and ensures the stiffness during the ascending,dwelling,and descending stages,especially suffering from negative pressure.

Learning-based adaptive optimal output regulation of linear and nonlinear systems:an overview

This paper reviews recent developments in learning-based adaptive optimal output regulation that aims to solve the problem of adaptive and optimal asymptotic tracking with disturbance rejection.The proposed framework aims to bring together two separate topics—output regulation and adaptive dynamic programming—that have been under extensive investigation due to their broad applications in modern control engineering.Under this framework,one can solve optimal output regulation problems of linear,partially linear,nonlinear,and multi-agent systems in a data-driven manner.We will also review some practical applications based on this framework,such as semi-autonomous vehicles,connected and autonomous vehicles,and nonlinear oscillators.

Eco-friendly non-acid intercalation and exfoliation of graphite to graphene nanosheets in the binary-peroxidant system for EMI shielding

The development of the preparation strategy for high-quality and large-size graphene via eco-friendly routes is still a challenging issue.Herein,we have successfully developed a novel route to chemically exfoliate natural graphite into high-quality and large-size graphene in a binary-peroxidant system.This system is composed of urea peroxide(CO(NH_(2))_(2)·H_(2)O_(2))and hydrogen peroxide(H_(2)O_(2)),where CO(NH_(2))_(2)·H_(2)O_(2)is used in preparing graphene for the first time.Benefiting from the complete decomposition of CO(NH_(2))_(2)·H_(2)O_(2)and H_(2)O_(2)into gaseous species under microwave(MW)irradiation,no water-washing and effluent-treatment are needed in this chemical exfoliation procedure,thus the preparation of graphene in an eco-friendly way is realized.The resultant graphene behaves a large-size,high-quality and few-layer feature with a yield of~100%.Then 4µm-thick ultrathin graphene paper fabricated from the as-exfoliated graphene is used as an electromagnetic interference(EMI)shielding material.And its absolute effectiveness of EMI shielding(SSE/t)is up to 34,176.9 dB cm^(2)/g,which is,to the best of our knowledge,among the highest values so far reported for typical EMI shielding materials.The EMI shielding performance demonstrates a great application potential of graphene paper in meeting the ever-increasingly EMI shielding demands in miniaturized electronic devices.