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This letter concerns distributed spatial filtering over networked systems, i.e., transforming signal values given for nodes to those with a desired spatial frequency characteristic via a distributed computation. An existing filtering algorithm can achieve only low-pass filter characteristics, which limits its range of applications. To address this limitation, we extend the aforementioned filtering algorithm using an additional design parameter. We then present a characterization of all the realizable filter characteristics as a necessary and sufficient condition for achieving distributed spatial filtering. As a result, it is shown that the extended algorithm increases the range of the realizable filter characteristics. The proposed method is verified not only by simulation but also by denoising experiments for a real sensor network. The results show that the proposed method effectively reduces spatial noise and achieves higher performance than an average consensus algorithm and an average filter.

This paper proposes and develops a simulator of multiagent mass games in which agents achieve formations displaying given grayscale images via distributed control. One potential application of mass games is entertainment for ordinary users. However, it is difficult for nonexpert users to understand the existing control methods for mass games, and the implementation requires considerable time and effort. The proposed mass game simulator developed to overcome these difficulties is provided as a MATLAB application. With this simulator, we can import a reference image, simulate a mass game for the reference image, confirm the simulation result, and save the result through simple mouse and keyboard inputs without the need for expert knowledge or programming effort. In addition, the application of the proposed simulator to entertainment and digital signage is discussed and evaluated. In particular, in the latter application, by playing an animation of the simulation results obtained using the simulator on digital signage, we can construct a novel type of signage whose contents are shown by the motion of individual dots corresponding to agents. These results indicate that control of multiagent systems can be used for nonengineering applications, which have not been considered in most existing studies.

This paper investigates the control of multi-agent systems inspired by chemotaxis of microorganisms. Chemotaxis is a biological phenomenon wherein organisms in an environment are attracted to food but move away from toxins. The problem addressed here is a formation control problem, i.e., a design problem of distributed controllers wherein the relative positions of agents become the desired positions with the progression of time. To solve this problem, we introduce a performance index that quantifies the achieved degree of a desired formation, and decompose it into local indices that can be embedded in the distributed controllers. Based on this, we propose formation controllers inspired by chemotaxis of Escherichia coli (E. coli), where each agent moves with the aim of increasing the corresponding local performance index using the chemotaxis controller of E. coli. In addition, to improve the accuracy of the resulting formation, we present Paramecium caudatum (P. caudatum)-type formation controllers by replacing the chemotaxis controller of E. coli used above with that of P. caudatum. The effectiveness is demonstrated by a comparison with the E. coli-type formation controllers via numerical simulation. This result implies that various chemotaxis controllers can be used in our method and the performance of the resulting controllers can be improved by choosing an appropriate chemotaxis controller.

This study attempts to analyze and design multi-agent systems in the spatial frequency domain and demonstrates that the spatial frequency-based approach is useful for distributed spatial filtering in sensor networks. First, we take the consensus of multi-agent systems ( i.e., letting the states of all agents converge to an identical value) as an example and analyze it using the concept of spatial frequencies. We then show that consensus by typical controllers corresponds to lowpass filtering in the spatial frequency domain. This demonstrates that spatial frequencies can characterize the behavior of multi-agent systems. Second, we present a controller design method in the spatial frequency domain. The designed controllers provide the feedback system with a desired spatial frequency characteristic given in advance. We further derive a sufficient condition for the spatial frequency characteristic to ensure that the designed controllers are distributed. Finally, the effectiveness and applicability of our design method are demonstrated through an example of distributed denoising in a sensor network.

This paper presents networked controllers for the coordination of multi-robot systems, inspired by the chemotaxis of bacteria. Chemotaxis is a biological phenomenon wherein each organism senses the concentration of a chemical in its environment and moves to the highest (or lowest) concentration point. The problem studied herein is a coverage problem, specifically, the problem of finding networked controllers to deploy robots so that they are located uniformly on a given space. To solve this problem, we decompose a global performance index quantifying the achieved degree of coverage into local indices that can be calculated in a distributed manner over the network of robots. By combining this with a controller causing chemotaxis, we present a solution to the coverage problem wherein each robot performs either a forward movement or random rotation based on the local performance index at each time step. Moreover, we extend this solution to rendezvous at an unspecified point. Simulation and experimental results demonstrate that our solution achieves coverage and rendezvous only via the above two types of robot movements and can handle different tasks simply by changing the global performance index, through the appropriate use of the chemotaxis controller.

This paper studies scalable control of power systems, i.e., control with the constraint that controllers of all generators are the same. This control framework is useful to reduce the cost of constructing large-scale power systems because we can obtain controllers of all generators merely by designing one controller. The problem addressed here is to find the same controllers stabilizing an equilibrium point of the resulting feedback system and improving the performance in terms of the time response. As a solution to this problem, we present controllers to uniformly increase the damping forces of generators. We then show that an equilibrium point of the resulting feedback system is stable under certain conditions. In addition, we present a design method of the controller gain for improving the performance of the resulting feedback system in terms of the time response.

In this paper, we concern swing down control of the Acrobot which is a 2-link planar robot with a single actuator driving the second joint, whose control objective is to stabilize the Acrobot to the downward equilibrium point with the two links in the downward position for all initial states of the Acrobot with the exception of a set of Lebesgue measure zero. To achieve this control objective, we design a nonlinear controller by using nonnegative linear feedback of the sine function of the angle of the second joint in addition to the negative linear feedback of its angular velocity. By analyzing globally the solution of the closed-loop system consisting of the Acrobot and the presented controller and focusing on the equilibrium points of the closed-loop system and their stability, we prove that the control objective is achieved provided that some conditions on two control gains are satisfied. We design the two control gains such that the real parts of the dominant poles of the linearized model of the closed-loop system around the downward equilibrium point are minimized. We provide simulation results for two Acrobots to show the effectiveness of the presented controller.

This paper presents a theoretical analysis of the small-signal stability of a power system in which a synchronous generator and a photovoltaic (PV) generator supply power to an infinite bus. The problem considered here is to investigate the existence of the equilibrium points of the system and their stability. In terms of this problem, by focusing on the condition to be satisfied by the equilibrium points and appropriately using the intermediate value theorem, we derive a sufficient condition on the magnitude of the PV current for the existence of the equilibrium points. The condition is given as inequalities with respect to the system parameters. These inequalities show that, if the power system from which the PV generator is removed has equilibrium points, then equilibrium points exist also in the original system as long as the PV current is small. Moreover, we analyze the stability of the equilibrium points and show that the equilibrium points found under our existence condition are asymptotically stable. These results imply that, when the PV current is below a certain level, the existence of the asymptotically stable equilibrium points is preserved even though the PV generator is introduced.

This paper presents an algorithm estimating the regions of attraction of power systems based on the Lyapunov function approach where a sublevel set of a Lyapunov function for a target system is used as the estimate. In particular, we focus here on the algorithm based on sum of squares (SOS) programming, which has been recently proposed, and aim to develop a simpler algorithm for the practical use. For this aim, we present an algorithm overcoming the difficulty of the SOS programming problem addressed in the existing study, i.e., the bilinear constraints, in a simpler way. In the proposed algorithm, two SOS programming problems are iteratively solved, and the number of the problems solved at each iteration is reduced to half of that in the existing algorithm. In addition, we theoretically analyze the proposed algorithm, and show the convergence under certain conditions. The performance of our algorithm is demonstrated by numerical examples.

This paper presents a framework of real-time pricing by data fusion of power consumption, i.e., estimating the total power consumption of consumers by sharing the information on local power consumption that each power source has. The problem addressed here is to find power estimators embedded in power sources (or embedded in access points provided in advance) and a power price controller such that the total power consumption tracks a given reference input. As a solution to this problem, we present power estimators with a consensus protocol and a proportional–integral type power price controller. We then show that our solution achieves the reference tracking of the total power consumption in a distributed manner.

This paper analyzes the transient stability of power systems with uncertain parameters. More precisely, we suppose that the inertia constants and damping coefficients of generators are uncertain, and consider the problem of checking the stability of an equilibrium state for all possible values of the uncertain parameters, and estimating the intersection of the region of attraction for those parameter values. By using a polytope representation for the uncertain parameters, we present a method to solve the problem. In the presented method, we solve a sum of squares (SOS) programming problem based on the polytope representation. It is proven that if this SOS programming problem is feasible, then our method provides a solution to the analysis problem of the transient stability.

This paper analyzes the transient stability of power systems with uncertain parameters. More precisely, we suppose that the inertia constants and damping coefficients of generators are uncertain, and consider the problem of checking the stability of an equilibrium state for all possible values of these uncertain parameters, and estimating the intersection of the region of attraction for those parameter values. By using a polytopic representation for the uncertain parameters and a concept from the field of robust control, we present a method for solving this problem. In the presented method, we solve a sum of squares programming problem with constraints imposed on systems where the values of the uncertain parameters correspond to the vertices of a polytope. We prove that, if the sum of squares programming problem is feasible, our method solves the analysis problem of robust transient stability. A numerical example demonstrates that our method correctly analyzes transient stability despite the parameter uncertainties, whereas an existing method gives an incorrect analysis result owing to the uncertainties.

For multi-link planar robots moving in the vertical plane with a last active joint, this paper studies how to design angular momentum based stabilizing controllers with a large region of attraction for the upright equilibrium point (UEP) of the robots, where all the links are upright. First, for an $n$ -link planar robot, the presented stabilizing control in this paper contains a term compensating the gravitational term related to the last joint and a linear feedback of $2n$ variables, which are the angular momentum of the robot about the first joint, its first-time derivative, its second-time derivative, and the other $(2n-3$ ) variables to be designed such that the Jacobian matrix of these $2n$ variables is nonsingular at the UEP. Second, as an application, regarding the three-link case, this paper proves that the Jacobian matrix is nonsingular at the UEP regardless of all the mechanical parameters if the three variables to be designed are chosen to be one of the nine combinations of any two joint angles from three joint angles and any one joint angular velocity from three joint angular velocities of the robot. Finally, the simulation results of a three-link robot are presented to show that the regions of attraction of the obtained nine controllers are bigger than that of the conventional linear state-feedback controller with the state variables being the angles and angular velocities of the robot. The new results obtained in this paper include the existing results for the two-link case as a special case.

For the Acrobot (a two-link planar robot moving in the vertical plane with a single actuator at the second joint), this paper studies how to design angular momentum based stabilizing controllers with a large region of attraction for its upright equilibrium point, where all the links are upright. First, in addition to the angular momentum of the Acrobot about the first joint, its first-time derivative, and its second-time derivative, this paper shows how to design a variable from the non-singularity of the Jacobian matrix of these four variables. This paper presents a necessary and sufficient condition such that the Jacobian matrix is nonsingular regardless of all the mechanical parameters, and proposes two parameterizations of the variable to be designed and two types of stabilizing controllers using these four variables. Finally, the simulation results are presented to show that the regions of attraction of the proposed controllers are much bigger than those of the linear state-feedback controllers having the same poles of the linearized system of the closed-loop system.

This paper analyzes the stability of a power system in which a synchronous generator and a photovoltaic (PV) generator supply the power to an infinite bus. The infinite bus corresponds to a large system to which the two generators are connected. The problem considered here is to investigate the existence of the equilibrium points of the system and their stability. For the problem, we derive a sufficient condition on the magnitude of the PV current for the existence of the equilibrium points. In addition, we analyze the stability of the equilibrium points, and show that the equilibrium points found under the derived condition are stable. These results clarify the impact of the penetration of the PV generator on the existence of the stable equilibrium points of the system.

This paper investigates the relation between graph signal processing and consensus of multi-agent systems. The graph signal processing is a technique to process graph signals, that is, signals whose values are on the vertices of graphs and whose structures are specified by the edges. By considering the combination of the states of agents and the graph describing the network structure between them as a graph signal, we show that the multi-agent consensus corresponds to low-pass filtering of the graph signal. This reveals a connection between the two distinct areas, i.e., the graph signal processing and the control of multi-agent systems. In addition, we provide a design method of consensus controllers based on the graph signal processing. In the proposed method, the controllers of agents are designed so that the spatial frequency of the states of the agents becomes a desired one. This enables us to construct controllers of multi-agent systems in the spatial frequency domain.