In this paper we propose a hybrid system that integrates reinforcement learning and flocking control in order to create an adaptive and intelligent multi-robot system. First, we present a flocking control algorithm th...
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In this paper we propose a hybrid system that integrates reinforcement learning and flocking control in order to create an adaptive and intelligent multi-robot system. First, we present a flocking control algorithm that allows multiple mobile robots to move together while avoiding obstacles. Second, we propose a distributed cooperative learning algorithm that can quickly enable the mobile robot network to avoid predator/enemy while maintaining the network connectivity and topology. The convergence of the cooperative learning algorithm is discussed. As a result, the hybrid system of flocking control and cooperative reinforcement learning results in an efficient integration of high level behaviors (discrete states and actions) and low level behaviors (continuous states and actions) for multi-robot cooperation. The simulations are performed to demonstrate the effectiveness of the proposed system.
Real objects in general are fractional-order (FO) systems, although in some types of systems the order is very close to integer order (IO). Since major advances have been made in the theory and practice of the identif...
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Real objects in general are fractional-order (FO) systems, although in some types of systems the order is very close to integer order (IO). Since major advances have been made in the theory and practice of the identification of FO controlled objects and in the design of FO controllers, it is possible to consider also the real order of the dynamical systems and consider more quality criterion while designing the FO controllers with more degrees of freedom compared to their IO counterparts. In this paper, we present an application of the retuning method to design and apply new FO controller for the existing laboratory feedback control system with no modifications in the internal architecture of the original feedback control system. Along with the mathematical description, presented are also simulation results.
Inter-area oscillations in power networks are typically poorly controllable by means of local decentralized control. Recent research efforts have been aimed at developing wide-area control strategies that involve comm...
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ISBN:
(纸本)9781479901777
Inter-area oscillations in power networks are typically poorly controllable by means of local decentralized control. Recent research efforts have been aimed at developing wide-area control strategies that involve communication of remote signals. In conventional wide-area control strategies the control structure is fixed a priori typically based on modal criteria. In contrast, here we employ the recently introduced paradigm of sparsity-promoting optimal control to simultaneously identify the control structure and optimize the closed-loop performance. To induce a sparse control architecture, we regularize the standard quadratic performance index with an l_1-penalty on the feedback matrix. The quadratic objective functions are inspired by the classic slow coherency theory and are aimed at imitating homogeneous networks without interarea oscillations. We use a compelling example to demonstrate that the proposed combination of the sparsity-promoting optimal control design with the slow coherency objective functions performs almost as well as the optimal centralized controllers.
The framework is designed to provide a simple and powerful way of Web application component development. Components of the framework can nest, and the framework is designed to be easy to reuse as a component, thus pro...
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In this paper design and control of planar cable-driven parallel robots are studied in an experimental prospective. Since in this class of manipulators, cable tensionability conditions must be met, feedback control of...
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In this paper design and control of planar cable-driven parallel robots are studied in an experimental prospective. Since in this class of manipulators, cable tensionability conditions must be met, feedback control of such robots becomes more challenging than for conventional robots. To meet these conditions, internal force control structure is introduced and used in addition to a PID control scheme to ensure that all cables remain in tension. A robust PID controller is proposed for partial knowledge of the robot, to keep the tracking errors bounded. Finally, the effectiveness of the proposed control algorithm is examined through experiments on K.N. Toosi planar cable-driven robot and it is shown that the proposed control structure is able to provide suitable performance in practice.
Scalar field mapping has many applications including environmental monitoring, search and rescue, etc. In such applications there is a need to achieve a certain level of confidence regarding the estimates at each loca...
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ISBN:
(纸本)9781479915132
Scalar field mapping has many applications including environmental monitoring, search and rescue, etc. In such applications there is a need to achieve a certain level of confidence regarding the estimates at each location. In this paper, a cooperative and active sensing framework is developed to enable scalar field mapping using multiple mobile sensor nodes. The cooperative and active controller is designed via the real-time feedback of the sensing performance to steer the mobile sensors to new locations in order to improve the sensing quality. During the movement of the mobile sensors, the measurements from each sensor node and its neighbors are taken and fused with the corresponding confidences using distributed consensus filters. As a result an online map of the scalar field is built with a certain level of confidence of the estimates. We conducted computer simulations to validate and evaluate our proposed algorithms
We study in this paper the consensus problem for multi-agent systems with agents characterized by high-order linear systems with time delays in both the communication network and inputs. Provided that the open-loop dy...
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ISBN:
(纸本)9781479901777
We study in this paper the consensus problem for multi-agent systems with agents characterized by high-order linear systems with time delays in both the communication network and inputs. Provided that the open-loop dynamics of the agents is not exponentially unstable, but may be polynomially unstable, and the communication topology contains a directed spanning tree, a truncated predictor feedback approach is established to solve the consensus problem. It is shown that, if the delays are constant and exactly known, the consensus problem can be solved by state feedback protocols for arbitrarily large bounded delays. If it is further assumed that the open-loop dynamics of the agents only contains zero eigenvalues, the delays are allowed to be time-varying and unknown. Numerical examples are worked out to illustrate the effectiveness of the proposed approaches.
This paper deals with exponential stability of some classes of integral delay systems with a prescribed decay rate. By carefully exploring the literature on this topic, a delay decomposition approach is established to...
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ISBN:
(纸本)9781479901777
This paper deals with exponential stability of some classes of integral delay systems with a prescribed decay rate. By carefully exploring the literature on this topic, a delay decomposition approach is established to reduce the conservatism in the existing sufficient conditions by constructing new Lyapunov-Krasovskii functionals. It is proven that the proposed sufficient conditions are always less conservative than the existing ones. Numerical examples illustrate the effectiveness of the proposed approaches.
We analyze real-life implementations of measurement-device-independent quantum-key-distribution (MDI-QKD): a general system model, a finite-decoy protocol and a finite-key analysis. Our work is relevant to not only QK...
Brain computer interface (BCI) is a widely used system to assist the disabled and paralyzed people by creating a new communication channel. Among the various methods used in BCI area, motor imagery (MI) is the most po...
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