We study distributed optimization problems over a directed network,where nodes aim to minimize the sum of local objective functions via directed communications with neighbors.Many algorithms are designed to solve it f...We study distributed optimization problems over a directed network,where nodes aim to minimize the sum of local objective functions via directed communications with neighbors.Many algorithms are designed to solve it for synchronized or randomly activated implementation,which may create deadlocks in practice.In sharp contrast,we propose a fully asynchronous push-pull gradient(APPG) algorithm,where each node updates without waiting for any other node by using possibly delayed information from neighbors.Then,we construct two novel augmented networks to analyze asynchrony and delays,and quantify its convergence rate from the worst-case point of view.Particularly,all nodes of APPG converge to the same optimal solution at a linear rate of O(λ^(k)) if local functions have Lipschitz-continuous gradients and their sum satisfies the Polyak-?ojasiewicz condition(convexity is not required),where λ ∈(0,1) is explicitly given and the virtual counter k increases by one when any node updates.Finally,the advantage of APPG over the synchronous counterpart and its linear speedup efficiency are numerically validated via a logistic regression problem.展开更多
This paper investigates a consensus design problem for continuous-time first-order multiagent systems with uniform constant communication delay.Provided that the agent dynamic is unstable and the diagraph is undirecte...This paper investigates a consensus design problem for continuous-time first-order multiagent systems with uniform constant communication delay.Provided that the agent dynamic is unstable and the diagraph is undirected,sufficient conditions are derived to guarantee consensus.The key technique is the adoption of historical input information in the protocol.Especially,when agent's own historical input information is used in the protocol design,the consensus condition is constructed in terms of agent dynamic,communication delay,and the eigenratio of the network topology.Simulation result is presented to validate the effectiveness of the theoretical result.展开更多
This paper addresses the source seeking problems for an autonomous underwater vehicle（AUV） with the estimated gradients. The AUV is embedded with multiple sensors, which are only able to detect the signal strengths ...This paper addresses the source seeking problems for an autonomous underwater vehicle（AUV） with the estimated gradients. The AUV is embedded with multiple sensors, which are only able to detect the signal strengths of the source with unknown distribution. To resolve this challenge,a sensor configuration is explicitly designed as a semicircle to estimate gradients of the signal field.Then, a controller is obtained via the estimated gradients to drive the AUV to approach the source.Moreover, an upper bound for the localization error is provided in terms of the radius of the semicircle and the signal distribution. Finally, the authors include a simulation example by applying the strategy to a Remote Environmental Monitoring Unit S（REMUS） for seeking the deepest point of a region of seabed in the South China Sea.展开更多
Quantized feedback control is fundamental to system synthesis with limited communication capacity.In sharp contrast to the existing literature on quantized control which requires an explicit dynamical model,the author...Quantized feedback control is fundamental to system synthesis with limited communication capacity.In sharp contrast to the existing literature on quantized control which requires an explicit dynamical model,the authors study the quadratic stabilization and performance control problems with logarithmically quantized feedback in a direct data-driven framework,where the system state matrix is not exactly known and instead,belongs to an ambiguity set that is directly constructed from a finite number of noisy system data.To this end,the authors firstly establish sufficient and necessary conditions via linear matrix inequalities for the existence of a common quantized controller that achieves our control objectives over the ambiguity set.Then,the authors provide necessary conditions on the data for the solvability of the LMIs,and determine the coarsest quantization density via semi-definite programming.The theoretical results are validated through numerical examples.展开更多
基金Supported by National Natural Science Foundation of China(62033006,62203254)。
文摘We study distributed optimization problems over a directed network,where nodes aim to minimize the sum of local objective functions via directed communications with neighbors.Many algorithms are designed to solve it for synchronized or randomly activated implementation,which may create deadlocks in practice.In sharp contrast,we propose a fully asynchronous push-pull gradient(APPG) algorithm,where each node updates without waiting for any other node by using possibly delayed information from neighbors.Then,we construct two novel augmented networks to analyze asynchrony and delays,and quantify its convergence rate from the worst-case point of view.Particularly,all nodes of APPG converge to the same optimal solution at a linear rate of O(λ^(k)) if local functions have Lipschitz-continuous gradients and their sum satisfies the Polyak-?ojasiewicz condition(convexity is not required),where λ ∈(0,1) is explicitly given and the virtual counter k increases by one when any node updates.Finally,the advantage of APPG over the synchronous counterpart and its linear speedup efficiency are numerically validated via a logistic regression problem.
基金supported by the Taishan Scholar Construction Engineering by Shandong Government,the National Natural Science Foundation of China under Grant Nos.61120106011 and 61203029
文摘This paper investigates a consensus design problem for continuous-time first-order multiagent systems with uniform constant communication delay.Provided that the agent dynamic is unstable and the diagraph is undirected,sufficient conditions are derived to guarantee consensus.The key technique is the adoption of historical input information in the protocol.Especially,when agent's own historical input information is used in the protocol design,the consensus condition is constructed in terms of agent dynamic,communication delay,and the eigenratio of the network topology.Simulation result is presented to validate the effectiveness of the theoretical result.
基金supported by the National Key Research and Development Program of China under Grant No.2016YFC0300801the National Natural Science Foundation of China under Grants Nos.41576101 and 41427806
文摘This paper addresses the source seeking problems for an autonomous underwater vehicle（AUV） with the estimated gradients. The AUV is embedded with multiple sensors, which are only able to detect the signal strengths of the source with unknown distribution. To resolve this challenge,a sensor configuration is explicitly designed as a semicircle to estimate gradients of the signal field.Then, a controller is obtained via the estimated gradients to drive the AUV to approach the source.Moreover, an upper bound for the localization error is provided in terms of the radius of the semicircle and the signal distribution. Finally, the authors include a simulation example by applying the strategy to a Remote Environmental Monitoring Unit S（REMUS） for seeking the deepest point of a region of seabed in the South China Sea.
基金supported by National Key R&D Program of China under Grant No.2022ZD0116700National Natural Science Foundation of China under Grant Nos.62033006 and 62325305
文摘Quantized feedback control is fundamental to system synthesis with limited communication capacity.In sharp contrast to the existing literature on quantized control which requires an explicit dynamical model,the authors study the quadratic stabilization and performance control problems with logarithmically quantized feedback in a direct data-driven framework,where the system state matrix is not exactly known and instead,belongs to an ambiguity set that is directly constructed from a finite number of noisy system data.To this end,the authors firstly establish sufficient and necessary conditions via linear matrix inequalities for the existence of a common quantized controller that achieves our control objectives over the ambiguity set.Then,the authors provide necessary conditions on the data for the solvability of the LMIs,and determine the coarsest quantization density via semi-definite programming.The theoretical results are validated through numerical examples.
