Distributed Cooperative Optimal Control for Multiagent Systems on Directed Graphs: An Inverse Optimal Approach.

In this article, we explore human motion skills in the dual-arm manipulation tasks that include contact with equipment with the final aim to generate human-like humanoid motion. Human motion is analyzed using the optimization approaches starting with the assumption that human motion is optimal. A combination of commonly used optimization criteria in the joint space with the weight coefficients is considered: minimization of kinetic energy, minimization of joint velocities, minimization of the distance between the current and ergonomic positions, and maximization of manipulability. The contribution of each criterion for seven different dual-arm manipulation tasks to provide the most accurate imitation of the human motion is given via suggested inverse optimization approach calculating values of weight coefficients. The effects on actors’ body characteristics and the characteristics of the environment (involved equipment) on the choice of criterion functions are additionally analyzed. The optimal combination of weight coefficients calculated by the inverse optimization approach is used in our inverse kinematics algorithm to transfer human motion skills to the motion of the humanoid robots. The results show that the optimal combination of weight coefficients is able to generate human-like humanoid motions rather than individual one of the considered criterion functions. The recorded human motion and the motion of the humanoid robot ROMEO, obtained with the strategy used by human and defined by our inverse optimal control approach, for the tasks “opening/closing a drawer” are assessed visually and quantitatively.

A small-gain approach to inverse optimal adaptive control of nonlinear systems with unmodeled dynamics

This paper addresses the distributed consensus protocol design problem for multi-agent systems with general linear dynamics and directed communication graphs. Existing works usually design consensus protocols using the smallest real part of the nonzero eigenvalues of the Laplacian matrix associated with the communication graph, which however is global information. In this paper, based on only the agent dynamics and the relative states of neighboring agents, a distributed adaptive consensus protocol is designed to achieve leader-follower consensus for any communication graph containing a directed spanning tree with the leader as the root node. The proposed adaptive protocol is independent of any global information of the communication graph and thereby is fully distributed. Extensions to the case with multiple leaders are further studied.

International audience

This study uses inverse optimization to uncover the implicit objectives driving financial aid allocation decisions across U.S. higher education institutions. Analyzing data from 3,130 institutions in the 2021–22 IPEDS dataset, we estimate the strategic weight each institution places on four competing goals: access (coverage), equity (need-based targeting), prestige, and cost control. Private nonprofit universities prioritize prestige (54.8%), awarding an average of $23,155 per student; public universities emphasize broad coverage (59.7%) with more moderate awards; and for-profit institutions adopt mixed strategies, balancing access and need. By recovering these revealed institutional priorities from observed behavior, we provide the first large-scale quantitative evidence that financial aid is frequently used to enhance institutional reputation rather than expand access. These findings highlight the equity implications of strategic aid allocation and offer a methodological framework to evaluate whether institutional priorities align with access goals.

In this paper, the inverse optimal approach is employed to design distributed cooperative control protocols for identical linear systems that guarantee consensus and global optimality with respect to a positive (semi-) definite quadric performance index. Cooperative control and pinning control problems are considered, where the communication graphs are assumed to be directed and have fixe topology. Simple sufficient conditions are established, which indicate that the global optimality is achieved using local distributed protocols which are designed by the linear quadric regulator (LQR) based optimal control method. Examples are given to show the effectiveness of the proposed methods.

This paper considers the consensus control problem of heterogeneous linear multiagent systems. A distributed proportional-integral (PI) protocol is presented to ensure consensus of heterogeneous linear multiagent systems with directed communication graphs. Sufficient conditions for the choice of control parameters are derived. For the case that the agents are subject to the external time-varying but bounded disturbances, the proposed distributed PI protocol can assure uniformly ultimate boundedness of the consensus error. The effectiveness of the results is illustrated both theoretically and numerically.

One of the primary causes of low light extraction efficiency (LEE) in conventional OLEDs is the trapping of light within the substrate layer. To overcome this limitation, various nanostructures have recently been investigated for integration into different OLED layers, aiming to convert the trapped loss modes into out-coupled light and thereby improve LEE. In this work, we propose a simple yet innovative nanorod array design composed of metal, insulator, and semiconductor-oxide layers, integrated on the bottom surface of the OLED structure. This configuration enhances light extraction through guided surface plasmon-coupled emission (SPCE). Using an inverse design-based optimization approach, the structural parameters of the nanorods were optimized to achieve wavelength-selective LEE enhancement. The periodic MIS nanorod array was optimized via the Particle Swarm Optimization (PSO) algorithm for different emission wavelengths, yielding improvements of 29%, 30%, and 51% at 440 nm, 550 nm, and 640 nm, respectively, compared with conventional OLEDs. In addition, the optimized arrays demonstrate high spectral luminous efficiency (SLE), reduced UV transmittance, and uniform emission directionality. These enhancements have significant potential to advance OLED-based display technologies.

A constructive approach for an optimal control applied to a class of nonlinear time delay systems

Global inverse optimality for a class of recurrent neural networks with multiple proportional delays

An Inverse Optimization Approach to Inducing Resource Conservation in Eco-Industrial Parks

IMRT, by virtue of the increased degrees of delivery freedom available, requires the utilization of advanced optimization approaches (so‐called inverse planning techniques). While such inverse planning optimization approaches make possible the solution of these otherwise intractably large problems, they impose unique challenges with regard to the treatment of multiple targets with different desired total delivered dose levels. In this session we will discuss and characterize these challenges and discuss various “workarounds” to these problems, along with their potential implications and ramifications.

This article investigates the optimal consensus problem for general linear multiagent systems (MASs) via a dynamic event-triggered approach. First, a modified interaction-related cost function is proposed. Second, a dynamic event-triggered approach is developed by constructing a new distributed dynamic triggering function and a new distributed event-triggered consensus protocol. Consequently, the modified interaction-related cost function can be minimized by applying the distributed control laws, which overcomes the difficulty in the optimal consensus problem that seeking the interaction-related cost function needs all agents' information. Then, some sufficient conditions are obtained to guarantee optimality. It is shown that the developed optimal consensus gain matrices are only related to the designed triggering parameters and the desirable modified interaction-related cost function, relaxing the constraint that the controller design requires the knowledge of system dynamics, initial states, and network scale. Meanwhile, the tradeoff between optimal consensus performance and event-triggered behavior is also considered. Finally, a simulation example is provided to verify the validity of the designed distributed event-triggered optimal controller.

This paper presents an event‐triggered distributed control protocol designed for scenarios involving Denial‐of‐Service (DoS) attacks within directed communication graphs. We address the consensus problem of uncertain systems by employing neural networks to approximate nonlinear components. Compared with traditional neural network observers, the proposed method incorporates damping terms to ensure the boundedness of neural network estimators. Initially, an auxiliary system was constructed to decouple the consensus problem under a directed communication graph framework. It is demonstrated that the uncertain nonlinear system can achieve consensus through the utilization of information exchanged among neighboring agents. Subsequently, to curtail the consumption of communication resources, we introduce an event‐triggered control protocol based on the aforementioned approach, incorporating an effective event‐triggering function. Building upon the proposed control protocol, we further develop a control strategy tailored for systems under DoS attacks. Furthermore, the event‐triggered mechanism without using global information in trigger condition not only curtails superfluous information exchange among agents but also precludes the occurrence of Zeno behavior (i.e., infinite triggering within a finite time interval). Finally, numerical simulations are carried out to validate the efficacy of the proposed control protocol.

1. In birds with bi‐parental care, handicapping is often assumed to decrease the amount of parental care of the handicapped partner. We discuss how handicapping could alter the shape of the handicapped bird's survival–effort curve (theoretical curve relating the survival of a parent to its effort) and show that the optimal response could yield a decrease, no response or even an increase in effort of the handicapped bird. 2. Male or female great tits Parus major (L.) were handicapped during the nestling period by clipping a number of feathers in order to study the effects on parental care and body condition. 3. Handicapped males significantly decreased their feeding rates, while handicapped females did not. Condition of handicapped females significantly deteriorated, while condition of handicapped males did not change during the experiment. Females with a handicapped partner fully compensated for their partner's decrease in work rate, while males with a handicapped partner did not show any compensation and even tended to decrease their feeding rates. 4. Using an inverse optimality approach, we reconstructed the theoretical curve relating the survival of a parent to its effort on the basis of the experimental effects. The handicapped male's survival–effort curve appeared to be slightly steeper than that of handicapped females. This suggests that handicapped males suffer more from an increase in effort than handicapped females.