This note studies the adaptive optimal output regulation problem for continuous-time linear systems, which aims to achieve asymptotic tracking and disturbance rejection by minimizing some predefined ...costs. Reinforcement learning and adaptive dynamic programming techniques are employed to compute an approximated optimal controller using input/partial-state data despite unknown system dynamics and unmeasurable disturbance. Rigorous stability analysis shows that the proposed controller exponentially stabilizes the closed-loop system and the output of the plant asymptotically tracks the given reference signal. Simulation results on a LCL coupled inverter-based distributed generation system demonstrate the effectiveness of the proposed approach.
This paper proposes a novel data-driven control approach to address the problem of adaptive optimal tracking for a class of nonlinear systems taking the strict-feedback form. Adaptive dynamic ...programming (ADP) and nonlinear output regulation theories are integrated for the first time to compute an adaptive near-optimal tracker without any a priori knowledge of the system dynamics. Fundamentally different from adaptive optimal stabilization problems, the solution to a Hamilton-Jacobi-Bellman (HJB) equation, not necessarily a positive definite function, cannot be approximated through the existing iterative methods. This paper proposes a novel policy iteration technique for solving positive semidefinite HJB equations with rigorous convergence analysis. A two-phase data-driven learning method is developed and implemented online by ADP. The efficacy of the proposed adaptive optimal tracking control methodology is demonstrated via a Van der Pol oscillator with time-varying exogenous signals.
A plasma approach is reported to synthesize carbon cloth supported carbon fiber and oxygen defect‐rich NiCoO/NiCoN hetero‐nanowire co‐integrated hybrid catalyst (P‐NCO/NCN‐CF@CC), which includes the ...advanced features of carbon integration, cation doping, defect/vacancy introduction, and heterostructuring. The P‐NCO/NCN shows a fascinating structure with the periphery composed of NCO and the interior co‐composed of NCO and NCN. Its formation mainly depends on the high reactivity of energetic species of NH, Ha, and Hb formed during the plasma discharge. The P‐NCO/NCN‐CF@CC exhibits the oxygen reduction reaction (ORR) activity comparable to the Pt/C and the oxygen evolution reaction (OER) activity higher than RuO2. When used in the all‐solid‐state zinc‐air batteries, it gives a high maximum power density of 109.8 mW cm−2 with no performance drop observed for >300 cycles. The DFT calculations indicate that the NCO/NCN heterostructuring and oxygen defects in NCO play the important roles in the high ORR/OER activities of the catalyst. They can modulate the electronic structure of the catalyst, lowering the energy barriers of rate determining steps.
The plasma approach is employed to the synthesis of the oxygen defective NiCoO/NiCoN heterostructure with improved ORR/OER activities, which includes the advanced features of carbon integration, cation doping, defect/vacancy introduction, and heterostructuring. The assembled flexible all‐solid‐state zinc‐air batteries exhibit an open circuit voltage of 1.48 V and deliver a maximum power density of 109.8 mW cm−2.
Many countries are devoting considerable efforts to replace fossil energy with renewable energy to achieve 'Carbon Neutrality'. Straw-based bioenergy is considered as a potential substitute of fossil ...energy. This paper investigates the government regulations (i.e. penalty and subsidy policy) for a straw-based bioenergy supply chain consisting of power plants and farmers, in which the three parties are of bounded rationality. We develop a three-party evolutionary game model and obtain the evolutionary stable strategies of the three parties. We establish the dynamic penalty model and show that the dynamic penalty policy can encourage power plants to use bioenergy and farmers to collect bioenergy than the existing static penalty policy. Our results further demonstrate if the proportion of the farmers choosing the 'Collecting bioenergy' strategy is low, the government should choose the 'Penalizing the farmer' strategy; otherwise, the government should choose the 'Penalizing the power plant' strategy. We also extend our model to the government's subsidy policy and compare it with the penalty policy. Specially, when the proportion of the power plants (farmers) using (collecting) bioenergy is high, if the government's subsidies are lower than penalties, the government should choose the subsidy policy; otherwise, the government should choose the penalty policy.
The event-based control strategy is an effective methodology for tackling the distributed control of multi-agent systems with limited on-board resources. This technical note focuses on event-based ...leader-following consensus for multi-agent systems described by general linear models and subject to input time delay between controller and actuator. For each agent, the controller updates are event-based and only triggered at its own event times. A necessary condition and two sufficient conditions on leader-following consensus are presented, respectively. It is shown that continuous communication between neighboring agents can be avoided and the Zeno-behavior of triggering time sequences is excluded. A numerical example is presented to illustrate the effectiveness of the obtained theoretical results.
This paper presents a novel method of global adaptive dynamic programming (ADP) for the adaptive optimal control of nonlinear polynomial systems. The strategy consists of relaxing the problem of ...solving the Hamilton-Jacobi-Bellman (HJB) equation to an optimization problem, which is solved via a new policy iteration method. The proposed method distinguishes from previously known nonlinear ADP methods in that the neural network approximation is avoided, giving rise to significant computational improvement. Instead of semiglobally or locally stabilizing, the resultant control policy is globally stabilizing for a general class of nonlinear polynomial systems. Furthermore, in the absence of the a priori knowledge of the system dynamics, an online learning method is devised to implement the proposed policy iteration technique by generalizing the current ADP theory. Finally, three numerical examples are provided to validate the effectiveness of the proposed method.
This paper presents a new approach to event-triggered control for nonlinear uncertain systems by using the notion of input-to-state stability (ISS) and the nonlinear small-gain theorem. The ...contribution of this paper is threefold. First, it is proved that infinitely fast sampling can be avoided if the system is input-to-state stabilizable with the sampling error as the external input and the corresponding ISS gain is locally Lipschitz. No assumption on the existence of known ISS-Lyapunov functions is made in the discussions. Moreover, the forward completeness problem with event-triggered control is studied systematically by using ISS small-gain arguments. Second, the proposed approach gives rise to a new self-triggered sampling strategy for a class of nonlinear systems subject to external disturbances. If an upper bound of the external disturbance is known, then the closed-loop system can be designed to be robust to the external disturbance, and moreover, the system state globally asymptotically converges to the origin if the external disturbance decays to zero. Third, a new design method is developed for event-triggered control of nonlinear uncertain systems in the strict-feedback form. It is particularly shown that the ISS gain with the sampling error as the input can be designed to satisfy the proposed condition for event-triggered control and self-triggered control.
This article studies the distributed optimal output agreement problem for multiagent systems described by uncertain nonlinear models. By using the partial information of an objective function, the ...design aims to steer the outputs of the agents to an agreement on the optimal solution to the objective function. To solve this problem, this article introduces distributed coordinators to calculate the desired outputs, and designs reference-tracking controllers for the agents to follow the desired outputs. To deal with the nonlinear uncertain dynamics, the closed-loop multiagent system is considered as a dynamical network, and Sontag's input-to-state stability is employed to characterize the interconnections. It is shown that output agreement in multiagent nonlinear systems is achievable by means of distributed optimal controllers via a small-gain approach. The proposed design features a three-layer architecture, and the reference-tracking controllers can be implemented as successive nonlinear proportional-integral loops. A numerical example is employed to show the effectiveness of the design.
To design a clinically translatable nanomedicine for photodynamic theranostics, the ingredients should be carefully considered. A high content of nanocarriers may cause extra toxicity in metabolism, ...and multiple theranostic agents would complicate the preparation process. These issues would be of less concern if the nanocarrier itself has most of the theranostic functions. In this work, a poly(ethylene glycol)‐boron dipyrromethene amphiphile (PEG‐F54‐BODIPY) with 54 fluorine‐19 (19F) is synthesized and employed to emulsify perfluorohexane (PFH) into a theranostic nanoemulsion (PFH@PEG‐F54‐BODIPY). The as‐prepared PFH@PEG‐F54‐BODIPY can perform architecture‐dependent fluorescence/photoacoustic/19F magnetic resonance multimodal imaging, providing more information about the in vivo structure evolution of nanomedicine. Importantly, this nanoemulsion significantly enhances the therapeutic effect of BODIPY through both the high oxygen dissolving capability and less self‐quenching of BODIPY molecules. More interestingly, PFH@PEG‐F54‐BODIPY shows high level of tumor accumulation and long tumor retention time, allowing a repeated light irradiation after a single‐dose intravenous injection. The “all‐in‐one” photodynamic theranostic nanoemulsion has simple composition, remarkable theranostic efficacy, and novel treatment pattern, and thus presents an intriguing avenue to developing clinically translatable theranostic agents.
A versatile theranostic nanoemulsion is synthesized by using a PEG‐F54‐BODIPY amphiphile as the emulsifier. Taking advantage of the delicate interactions of the nanocarrier and interior perfluorocarbon, both architecture‐dependent trimodal imaging and highly efficient photodynamic therapy are achieved.
Here we present a modular, chemo‐, regio‐, and stereoselective synthesis of fully‐substituted and configuration‐defined alkyl vinyl ethers (AVEs) using simple chemical feedstocks. The distinctive ...approach involves the chemo‐ and regioselective functionalization of the CF2 unit in gem‐difluorinated cyclopropanes with O−H and C−H nucleophiles in a specific order. The resulting highly functionalized cyclopropanyl ethers then undergo a stereoselective ring‐opening process to produce fully‐substituted and configuration‐defined AVEs. These AVEs are rarely accessible through conventional methods and are easily transformable. Mechanistic experiments indicate that the success of this method relies on the use of dual‐functional copper catalysis, which is involved in both the functionalization of the CF2 unit and the subsequent ring‐opening process.
The synthesis of highly‐substituted alkyl vinyl ethers in a well‐defined configuration is challenging. Now, a modular, chemo‐, regio‐, and stereoselective synthesis of fully‐substituted and configuration‐defined alkyl vinyl ethers (AVEs) enabled by dual‐functional Cu catalysis is reported. It also represents a novel ring‐opening pattern involving the cleavage of the C1−C3 bond in gem‐difluorinated cyclopropanes.
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