Perfect cooperative pest control via nano-pesticide and natural predator: High predation selectivity and negligible toxicity toward predatory stinkbug

The improper use of synthetic pesticides has caused adverse effects on global ecosystems and human health. As a part of sustainable pest management strategy, natural predators, along with nano-pesticides, have made significant contributions to ecological agriculture. The cooperative application of both approaches may overcome their limitations, substantially reducing pesticide application while controlling insect pests efficiently. Herein, the current study introduced a cationic star polymer (SPc) to prepare two types of nano-pesticides, which were co-applied with predatory stinkbugs Picromerus lewisi to achieve perfect cooperative pest control. The SPc exhibited nearly no toxicity against predatory stinkbugs at the working concentration, but it led to the death of predatory stinkbugs at extremely high concentration with the lethal concentration 50 (LC50) value of 13.57 mg/mL through oral feeding method. RNA-seq analysis revealed that the oral feeding of SPc could induce obvious stress responses, leading to stronger phagocytosis, exocytosis, and energy synthesis to ultimately result in the death of predatory stinkbugs. Then, the broflanilide and chlorobenzuron were employed to prepare the self-assembled nano-pesticides via hydrogen bond and Van der Waals force, and the complexation with SPc broke the self-aggregated structures of pesticides and reduced their particle sizes down to nanoscale. The bioactivities of prepared nano-pesticides were significantly improved toward common cutworm Spodoptera litura with the corrected mortality increase by approximately 30%. Importantly, predatory stinkbugs exhibited a strong predation selectivity for alive common cutworms to reduce the exposure risk of nano-pesticides, and the nano-pesticides showed negligible toxicity against predators. Thus, the nano-pesticides and predatory stinkbugs could be applied simultaneously for efficient and sustainable pest management. The current study provides an excellent precedent for perfect cooperative pest control via nano-pesticide and natural predator.

Observer-based HOFA predictive cooperative control for networked multi-agent systems under time-variant communication constraints

This research focuses on a cooperative control problem for networked multi-agent systems (NMASs) under time-variant communication constraints (containing time-variant communication delays and time-variant data losses) in the forward and feedback channels. From the perspective of high-order fully actuated (HOFA) system theory, a HOFA system model is adopted to describe the NMAS, which is called the networked HOFA multi-agent system (NHOFAMAS). Because of complicated working scenarios over the network, the states of NMASs are immeasurable and the communication constraints are always present, such that an observer-based HOFA predictive control (OB-HOFAPC) method is designed to implement the cooperative control when existing the immeasurable states and time-variant communication constraints. In this method, a HOFA observer is established to estimate the immeasurable states for constructing a consensus control protocol. Then, an incremental prediction model (IPM) in a HOFA form is developed via a Diophantine equation to take the place of a reduced-order prediction model. Through this IPM, multi-step output ahead predictions are derived to optimize the cooperative control performance and compensate for time-variant communication constraints in real-time. The depth discussion gives a sufficient and necessary criterion to analyze the simultaneous consensus and stability for closed-loop NHOFAMASs. The capability and advantage of OB-HOFAPC method are illustrated via numerical simulation and experimental verification on a cooperative flying-around task of three air-bearing spacecraft simulators.

Consensus-based secondary control for DC microgrids with communication delays via a networked predictive control strategy

In today's cyber-physical microgrid systems, the consensus-based secondary control is generally utilized to settle the voltage deviation and rough current allocation issues at the primary control level. However, time delays follow inevitably the introduction of sparse communication networks, and most existing works adopt passive tolerance approaches. To actively alleviate the unavoidable delay effect in microgrids' communication networks, a networked predictive control (NPC) strategy is proposed for an islanded DC microgrid subject to time delays in this paper. Firstly, the predictive approaches for both voltage and current are developed based on the cyber-physical microgrid model. Unlike the practice of passively tolerating time delays, the NPC strategy is proposed to actively compensate for the effect of communication delays by estimating real-time voltage and current values using the previously obtained prediction models. Moreover, to prove the generality of the developed method, the microgrid systems' stability can be derived from the Schur stability of the closed-loop system, thus the DC microgrid can achieve voltage regulation and proportional current sharing simultaneously. Finally, the performance of our method against the time delay effect is validated by extensive experiments on an islanded 48-V DC microgrid system, in terms of its feasibility, delay tolerance ability, and robustness to load changes and communication faults. Experimental results demonstrate the effectiveness and superiority of the NPC strategy.

A cooperative control method for safer on-ramp merging process in heterogeneous traffic flow

The on-ramp area is a high-risk conflict zone where traffic accidents frequently occur. Connected and automated vehicles (CAVs) have the potential to enhance the safety of the merging process through appropriate cooperative control methods. This paper proposes a cooperative control method for safer on-ramp merging processes in heterogeneous traffic flow. Firstly, the gap selection process of ramp vehicles is described, thus all feasible virtual platoon results can be summarized. Next, the vehicle bond (VB) is used to describe the connection mode between vehicles within the virtual platoon. A two-layered gap selection function is proposed to ensure a safer merging process. The first layer aims to minimize the number of empty VBs, while the second layer considers fairness with respect to delay. To evaluate the control effectiveness, time exposed time-to-collision (TET), cumulative risk (CR), and conflict-potential mergence ratio (CPMR) are selected as the safety evaluation indicators. The simulation results show that the gap selection control moves the merging positions of ramp vehicles forward, resulting less risk of merging. It significantly enhances the safety of on-ramp merging without compromising traffic efficiency. At a flow rate of 650 veh/h for both the mainline and ramp, and a CAV penetration rate of 0.1-0.9, the gap selection control group achieves a decrease rate of about 0.3-0.6 for average TET and CR compared to the non-control group. In the pure CAV environment, the decrease rate can reach about 0.9. Sensitivity analysis indicates that the gap selection control is effective across varying flow rates and steady speeds. The optimal control effect is achieved when the length of the communication area ranges from 100 to 200 m.

A force-sensing surgical drill for real-time force feedback in robotic mastoidectomy

PURPOSE

Robotic assistance in otologic surgery can reduce the task load of operating surgeons during the removal of bone around the critical structures in the lateral skull base. However, safe deployment into the anatomical passageways necessitates the development of advanced sensing capabilities to actively limit the interaction forces between the surgical tools and critical anatomy.

METHODS

We introduce a surgical drill equipped with a force sensor that is capable of measuring accurate tool-tissue interaction forces to enable force control and feedback to surgeons. The design, calibration and validation of the force-sensing surgical drill mounted on a cooperatively controlled surgical robot are described in this work.

RESULTS

The force measurements on the tip of the surgical drill are validated with raw-egg drilling experiments, where a force sensor mounted below the egg serves as ground truth. The average root mean square error for points and path drilling experiments is 41.7 (± 12.2) mN and 48.3 (± 13.7) mN, respectively.

CONCLUSION

The force-sensing prototype measures forces with sub-millinewton resolution and the results demonstrate that the calibrated force-sensing drill generates accurate force measurements with minimal error compared to the measured drill forces. The development of such sensing capabilities is crucial for the safe use of robotic systems in a clinical context.

Scalable time-constrained planning of multi-robot systems

This paper presents a scalable procedure for time-constrained planning of a class of uncertain nonlinear multi-robot systems. In particular, we consider N robotic agents operating in a workspace which contains regions of interest (RoI), in which atomic propositions for each robot are assigned. The main goal is to design decentralized and robust control laws so that each robot meets an individual high-level specification given as a metric interval temporal logic (MITL), while using only local information based on a limited sensing radius. Furthermore, the robots need to fulfill certain desired transient constraints such as collision avoidance between them. The controllers, which guarantee the transition between regions, consist of two terms: a nominal control input, which is computed online and is the solution of a decentralized finite-horizon optimal control problem (DFHOCP); and an additive state feedback law which is computed offline and guarantees that the real trajectories of the system will belong to a hyper-tube centered along the nominal trajectory. The controllers serve as actions for the individual weighted transition system (WTS) of each robot, and the time duration required for the transition between regions is modeled by a weight. The DFHOCP is solved at every sampling time by each robot and then necessary information is exchanged between neighboring robots. The proposed approach is scalable since it does not require a product computation among the WTS of the robots. The proposed framework is experimentally tested and the results show that the proposed framework is promising for solving real-life robotic as well as industrial applications.

Reliable cooperative control and plug-and-play operation for networked heterogeneous systems under cyber-physical attacks

This paper considers a reliable cooperative control and plug-and-play operation problem in networked heterogeneous systems (NHSs), and focuses on the scenario subjected to physical attack-induced actuator failures/uncertainties and Denial-of-Service (DoS) attacks on communication channels between physical nodes. To solve it, a new self-feedback control with an adaptive integral sliding-mode compensator is developed. The new one configures each heterogeneous system under the malicious actuator failures/uncertainties to be passivity-short (PS). The PS index quantifies the impact of each attacked heterogeneous dynamics on their networked operations. Furthermore, based on cloud networks, a novel network-level distributed control is proposed. It improves robustness of the systems against DoS with no frequency and duration constraints. And then, a technical condition is presented with the aid of the impact equivalence principle. Under the condition, the self-feedback and network-level controls designed separately but performed together ensure the leader-follower consensus and plug-and-play operation of the attacked NHSs. Finally, the effectiveness of the proposed method is verified by flight control systems.

Observer-based consensus of networked thrust-propelled vehicles with directed graphs

In this paper, we investigate the consensus problem for networked underactuated thrust-propelled vehicles (TPVs) interacting on directed graphs. We propose distributed observer-based consensus protocols, which avoid the reliance on the measurements of translational velocities and accelerations. Using the input-output analysis, we present necessary and sufficient conditions to ensure that the observer-based protocols can achieve consensus for both the cases without and with constant communication delays, provided that the communication graph contains a directed spanning tree. Simulation examples are finally provided to illustrate the effectiveness of the control schemes.

Distributed-observer-based cooperative control for synchronization of linear discrete-time multi-agent systems

This paper considers output synchronization of discrete-time multi-agent systems with directed communication topologies. The directed communication graph contains a spanning tree and the exosystem as its root. Distributed observer-based consensus protocols are proposed, based on the relative outputs of neighboring agents. A multi-step algorithm is presented to construct the observer-based protocols. In light of the discrete-time algebraic Riccati equation and internal model principle, synchronization problem is completed. At last, numerical simulation is provided to verify the effectiveness of the theoretical results.