Event-Triggered Consensus and Formation Control in Multi-Agent Coordination

The focus of this thesis is to study distributed event-triggered control for multi-agent systems (MASs) facing constraints in practical applications. We consider several problems in the field, ranging from event-triggered consensus with information quantization, event-triggered edge agreement under synchronized/unsynchronized clocks, event-triggered leader-follower consensus with Euler-Lagrange agent dynamics and cooperative event-triggered rigid formation control. The first topic is named as event-triggered consensus with quantized relative state measurements. In this topic, we develop two event-triggered controllers with quantized relative state measurements to achieve consensus for an undirected network where each agent is modelled by single integrator dynamics. Both uniform and logarithmic quantizers are considered, which, together with two different controllers, yield four cases of study in this topic. The quantized information is used to update the control input as well as to determine the next trigger event. We show that approximate consensus can be achieved by the proposed algorithms and Zeno behaviour can be completely excluded if constant offsets with some computable lower bounds are added to the trigger conditions. The second topic considers event-triggered edge agreement problems. Two cases, namely the synchronized clock case and the unsynchronized clock case, are studied. In the synchronized clock case, all agents are activated simultaneously to measure the relative state information over edge links under a global clock. Edge events are defined and their occurrences trigger the update of control inputs for the two agents sharing the link. We show that average consensus can be achieved with our proposed algorithm. In the unsynchronized clock case, each agent executes control algorithms under its own clock which is not synchronized with other agents' clocks. An edge event only triggers control input update for an individual agent. It is shown that all agents will reach consensus in a totally asynchronous manner. In the third topic, we propose three different distributed event-triggered control algorithms to achieve leader-follower consensus for a network of Euler-Lagrange agents. We firstly propose two model-independent algorithms for a subclass of Euler-Lagrange agents without the vector of gravitational potential forces. A variable-gain algorithm is employed when the sensing graph is undirected; algorithm parameters are selected in a fully distributed manner with much greater flexibility compared to all previous work concerning event-triggered consensus problems. When the sensing graph is directed, a constant-gain algorithm is employed. The control gains must be centrally designed to exceed several lower bounding inequalities which require limited knowledge of bounds on the matrices describing the agent dynamics, bounds on network topology information and bounds on the initial conditions. When the Euler-Lagrange agents have dynamics which include the vector of gravitational potential forces, an adaptive algorithm is proposed. This requires more information about the agent dynamics but allows for the estimation of uncertain agent parameters. The last topic discusses cooperative stabilization control of rigid formations via an event-triggered approach. We first design a centralized event-triggered formation control system, in which a central event controller determines the next triggering time and broadcasts the event signal to all the agents for control input update. We then build on this approach to propose a distributed event control strategy, in which each agent can use its local event trigger and local information to update the control input at its own event time. For both cases, the trigger condition, event function and trigger behaviour are discussed in detail, and the exponential convergence of the formation system is guaranteed

Event-Triggered Algorithms for Leader-Follower Consensus of Networked Euler-Lagrange Agents

This paper proposes three different distributed event-triggered control algorithms to achieve leader-follower consensus for a network of Euler-Lagrange agents. We firstly propose two model-independent algorithms for a subclass of Euler-Lagrange agents without the vector of gravitational potential forces. By model-independent, we mean that each agent can execute its algorithm with no knowledge of the agent self-dynamics. A variable-gain algorithm is employed when the sensing graph is undirected; algorithm parameters are selected in a fully distributed manner with much greater flexibility compared to all previous work concerning event-triggered consensus problems. When the sensing graph is directed, a constant-gain algorithm is employed. The control gains must be centrally designed to exceed several lower bounding inequalities which require limited knowledge of bounds on the matrices describing the agent dynamics, bounds on network topology information and bounds on the initial conditions. When the Euler-Lagrange agents have dynamics which include the vector of gravitational potential forces, an adaptive algorithm is proposed which requires more information about the agent dynamics but can estimate uncertain agent parameters. For each algorithm, a trigger function is proposed to govern the event update times. At each event, the controller is updated, which ensures that the control input is piecewise constant and saves energy resources. We analyse each controllers and trigger function and exclude Zeno behaviour. Extensive simulations show 1) the advantages of our proposed trigger function as compared to those in existing literature, and 2) the effectiveness of our proposed controllers.Comment: Extended manuscript of journal submission, containing omitted proofs and simulation

Application of C-SVM Classification Algorithm to the Lighting Visual Comfort of University Classrooms

Considering the quality of the classroom light-environment will directly affect students\u27 eye health and learning efficiency, it is a problem to be solved that how to evaluate the visual comfort levels of the classroom light-environment and save lighting energy on the premise of necessary visual comfort. Aiming at these problems above, this study restored the classroom scene through adjustable full-size light-environment simulation laboratory, in which 135 subjects participated in the visual comfort evaluation experiment of the indoor light-environment. After features (illuminance and correlated color temperature) and labels (comfort levels) preprocessed ,we trained and visualized the visual comfort classification models of desktop reading and blackboard reading using the algorithms of C-Support Vector Machine (C-SVM). Through the contour map and the scatter diagram, we get the classification boundary of different comfort levels and the relationship between visual comfort and lighting parameters, which has guiding significance to classroom lighting design and evaluation

Postoperative Delirium in Elderly Patients May Be Associated with Perioperative Blood Pressure Fluctuations

Postoperative delirium (PD) is a common complication of surgery in elderly patients, but its pathophysiological mechanism remains unclear. In order to clarify the role of intraoperative hypotension and fluctuation of blood pressure in the development of PD, we conducted a follow-up study in elderly patients with intraoperative hypotension and fluctuation of blood pressure. A total of 237 patients underwent hip surgery between July 2018 and September 2019, and 158 patients who were eligible for inclusion were enrolled in the study. One day before the operation, the mentality of patients was evaluated by Mini-mental State Examination (MMSE), and the sex, age, height, and weight of the patients were recorded. Radial artery puncture was performed in all patients before anesthesia, intraoperative SBP, MAP and DBP were recorded, and the surgical events of the patients was recorded. The markers associated with PD (TNF-α, IL-6 and S-100β) were determined before and after surgery. Perioperative delirium (PD) was assessed by the prevailing standard of assessment, Confusion of Consciousness Assessment (CAM). Cognitive assessment was evaluated using the Mini-mental State Examination (MMSE). In addition, the timing and type of delirium were recorded. There were 158 patients which were accorded with the inclusion criteria came into the study. The results of our data showed that delirium occurred in 41 patients (25.9%) during the first week after surgery. In the comparison between the PD group and the non-PD group, it was found that the patients with postoperative delirium were older, lower body mass index and higher MMSE score before operation. Intraoperative blood pressure is low, usually more than 30% lower than preoperative blood pressure. The levels of TNF- α, IL-6 and Smur100 β were higher after operation. The increased incidence of postoperative delirium may be related to intraoperative hypotension and intraoperative blood pressure fluctuation. The pathophysiological mechanism may be that hypotension causes low cerebral perfusion, which in turn causes local inflammation in the brain. In addition, postoperative delirium is also more likely to occur in older patients with lower body mass index

Evaluation of Light Specific Gravity Ropivacaine Combined with Sufentanil in Hip Arthroplasty at An Advanced Age

Objective: To observe the effect of light specific gravity ropivacaine combined with sufentanil in elderly patients undergoing hip replacement. Methods :89 elderly patients with hip arthroplasty from July 2019 to September 2020 were randomly divided into experimental group and control group. The experimental group was anesthetized with light specific gravity ropivacaine combined with sufentanil. The control group was anesthetized with equal specific gravity ropivacaine to compare the effect of anesthesia and the incidence of adverse reactions. Results: there was no significant difference in sensory recovery time and motor recovery time between the experimental group and the control group (P>0.05), and the incidence of adverse reactions between the two groups was low. The sensory block time in the experimental group was shorter than that in the control group (PP>0.05). Conclusion: ropivacaine combined with sufentanil subarachnoid anesthesia is more effective in elderly patients undergoing hip arthroplasty, and the safety of the anesthesia scheme is higher, which will not lead to serious adverse reactions during operation. Moreover, the application of the anesthesia scheme can effectively improve the analgesic effect during and after operation, and the clinical application value is high

Average Communication Rate for Networked Event-Triggered Stochastic Control Systems

Quantifying the average communication rate (ACR) of a networked event-triggered stochastic control system (NET-SCS) with deterministic thresholds is a challenging problem due to the non-stationary nature of the system's stochastic processes. For such a system, a closed-loop effect emerges due to the interdependence between the system variable and the trigger of communication. This effect, commonly referred to as \textit{side information} by related work, distorts the stochastic distribution of the system variables and makes the ACR computation non-trivial. Previous work in this area used to over-simplify the computation by ignoring the side information and misusing a Gaussian distribution, which leads to approximated results. This paper proposes both analytical and numerical approaches to predict the exact ACR for a NET-SCS using a recursive model. Furthermore, we use theoretical analysis and a numerical study to qualitatively evaluate the deviation gap of the conventional approach that ignores the side information. The accuracy of our proposed method, alongside its comparison with the simplified results of the conventional approach, is validated by experimental studies. Our work is promising to benefit the efficient resource planning of networked control systems with limited communication resources by providing accurate ACR computation

Generalized controllers for rigid formation stabilization with application to event-based controller design

This paper discusses generalized controllers for rigid formation shape stabilization. We provide unified analysis to show convergence using different controllers reported in the literature, and further prove an exponential stability of the formation system when using the general form of shape controllers. We also show that different agents can use different controllers for controlling different distances to achieve a desired rigid formation, which enables the implementation of heterogeneous agents in practice for formation shape control. We further propose an event-triggered rigid formation control scheme based on the generalized controllers. The triggering condition, event function and convergence analysis are discusse

Safe Feedback Motion Planning in Unknown Environments:An Instantaneous Local Control Barrier Function Approach

Mobile robots are desired with resilience to safely interact with prior-unknown environments and finally accomplish given tasks. This paper utilizes instantaneous local sensory data to stimulate the safe feedback motion planning (SFMP) strategy with adaptability to diverse prior-unknown environments without building a global map. This is achieved by the numerical optimization with the constraints, referred to as instantaneous local control barrier functions (IL-CBFs) and goal-driven control Lyapunov functions (GD-CLFs), learned from perceptional signals. In particular, the IL-CBFs reflecting potential collisions and GD-CLFs encoding incrementally discovered subgoals are first online learned from local perceptual data. Then, the learned IL-CBFs are united with GD-CLFs in the context of quadratic programming (QP) to generate the safe feedback motion planning strategy. Rather importantly, an optimization over the admissible control space of IL-CBFs is conducted to enhance the solution feasibility of QP. The SFMP strategy is developed with theoretically guaranteed collision avoidance and convergence to destinations. Numerical simulations are conducted to reveal the effectiveness of the proposed SFMP strategy that drives mobile robots to safely reach the destination incrementally in diverse prior-unknown environments.</p