| 1. |
- Liu, Lizheng, et al.
(författare)
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A FPGA-based Hardware Accelerator for Bayesian Confidence Propagation Neural Network
- 2020
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Ingår i: 2020 IEEE Nordic Circuits and Systems Conference, NORCAS 2020 - Proceedings. - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- The Bayesian Confidence Propagation Neural Network (BCPNN) has been applied in higher level of cognitive intelligence (e.g. working memory, associative memory). However, in the spike-based version of this learning rule the pre-, postsynaptic and coincident activity is traced in three low-passfiltering stages, the calculation processes of weight update are very computationally intensive. In this paper, a hardware architecture of the updating process for lazy update mode is proposed for updating 8 local synaptic state variables. The parallelism by decomposing the calculation steps of formulas based on the inherent data dependencies is optimized. The FPGA-based hardware accelerator of BCPNN is designed and implemented. The experimental results show the updating process on FPGA can be accomplished within 110 ns with a clock frequency of 200 MHz, the updating speed is greatly enhanced compared with the CPU test. The trade-off between performance, accuracy and resources on dedicated hardware is evaluated, and the impact of the module reuse on resource consumption and computing performance is evaluated.
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| 2. |
- Zhang, Silun
(författare)
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Intrinsic Formation and Macroscopic Intervention in Multi-agent Systems
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In this dissertation, we study two problems within the field of the multi-agent systems theory. One is the formation control for multiple reducedattitudes, which are extensively utilized in many pointing applications and under-actuated scenarios for attitude maneuvers. In contrast to most existing methodologies on the formation control, the proposed method does notneed to contain any formation errors in the protocol. Instead, the constructedformation is attributed to geometric properties of the configuration space andthe designed connection topology. We refer to this type of formation controlas intrinsic formation control. Besides, the control protocols proposed in thiswork are designed directly in space S^2 , avoiding to use any attitude parameterizations. Moreover, along the studies, some elementary tools for reducedattitudes control are developed.Another problem is a moment-based methodology to modeling and ana-lyzing collective behavior of a group of agents. The theory is applicable fora wide range of applications, such as multi-agent systems with interactionsas well as with leaders and/or control input, and the use of this frameworkcan considerably reduce the computational burden for controlling and ana-lyzing such systems. We therefore propose to develop and use this theory forthe multi-agent applications such as crowd dynamics, opinion dynamics andother macroscopic problems.Particularly, in paper A a continuous control law is provided for a reduced attitude system, by which a regular tetrahedron formation can achieveasymptotic stability under a quite large family of gain functions in the con-trol. Then, with a further restriction on the control gain, almost global stability of the tetrahedron formation is also obtained. In this work, we introducea novel coordinates transformation that represents the relative reduced atti-tudes between the agents. The proposed method is an intrinsic formationcontrol that does not need to involve any information of the desired formation beforehand. Another virtue of the method proposed is that only relativeattitude measurement is required.Paper B further concerns the formation control of all regular polyhedralconfigurations (also called Platonic solids) for reduced attitudes. Accord-ing to the symmetries possessed by regular polyhedra, a unified frameworkis proposed for their formations. Via using the coordinates transformationpreviously proposed, it is shown that stability of the desired formations canbe provided by stabilizing a constrained nonlinear system. Then, a method-ology to investigate the stability of this type of constrained systems is alsopresented.In paper C, we introduce an approach for modeling collective behaviorof a group of agents using moments. We represent the swarming via their dis-tribution and derive a method to estimate the dynamics of the moments. We use this to predict the evolution of the distribution of agents by first computing the moment trajectories and then use this to reconstruct the distributionof the agents. In the latter an inverse problem is solved in order to reconstructa nominal distribution and to recover the macro-scale properties of the groupof agents. The proposed method is applicable for several types of multi-agent systems, including leader-follower systems.Paper D considers the problem of tracking and encircling a moving target by agents in the 3-dimensional space. In this work, we show that similardesign techniques proposed for reduced attitudes formations can also be applied to the formation control for point mass systems. Therein, a group ofagents are driven to some desired formation on a spherical surface and simultaneously the center of this spherical formation is kept coinciding withthe target to be tracked. By properly designing communication topology, theagents constitute a cyclic formation along the equator of an encircling sphere.In Paper E, a methodology based on differential geometry techniquesis proposed to investigate exponential stability of a formation for reducedattitudes. By such a method, there is no need in finding any relative coordinates, which is typically needed but shown to be difficult when the formationproblem is evolving in a non-Euclidean space. In the paper, the desired formation is treated as an embedding submanifold in (S^2)^N and by using therotation symmetries owned by the attitude dynamics its stability is directlyexamined. Moreover, such a method turns out to be coordinates free, namely,exponential stability of a formation can be completely determined by just investigating any one equilibrium which can result in the formation under anylocal chart of (S^2 )^N . This greatly simplifies the stability analysis for theformation problems.
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| 3. |
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| 4. |
- Guo, Chaoqun, et al.
(författare)
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Fixed-time safe tracking control of uncertain high-order nonlinear pure-feedback systems via unified transformation functions
- 2023
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Ingår i: Kybernetika (Praha). - : Institute of Information Theory and Automation. - 0023-5954 .- 1805-949X. ; 59:3, s. 342-364
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, a fixed-time safe control problem is investigated for an uncertain high-order nonlinear pure-feedback system with state constraints. A new nonlinear transformation function is firstly proposed to handle both the constrained and unconstrained cases in a unified way. Further, a radial basis function neural network is constructed to approximate the unknown dynamics in the system and a fixed-time dynamic surface control (FDSC) technique is developed to facilitate the fixed-time control design for the uncertain high-order pure-feedback system. Combined with the proposed unified transformation function and the FDSC technique, an adaptive fixed-time control strategy is proposed to guarantee the fixed-time tracking. The novel original results of the paper allow to design the independent unified flexible fixed-time control strategy taking into account the actual possible constraints, either present or missing. Numerical examples are presented to demonstrate the proposed fixed-time tracking control strategy.
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| 5. |
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| 6. |
- Lu, Y., et al.
(författare)
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Fuzzy hegselmann-krause opinion dynamics with opinion leaders
- 2019
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Ingår i: 2019 Chinese Control Conference (CCC). ; , s. 6019-6024
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Konferensbidrag (refereegranskat)abstract
- In this paper, from the perspective of opinion dynamics theory, we investigate the intrinsic interaction principles of a group of autonomous agents and develop a fuzzy opinion dynamics model with leaders. First, this paper divides group agents into three subgroups: opinion followers, positive opinion leaders, and negative opinion leaders according to the opinion's update manner and influence. Then, we consider the uncertainty of the agents' opinion gaps and apply the Fuzzy Inference Machine to the effects of the leaders' opinions on a certain follower's opinion. The innovation of this paper is that the weight is distributed from 0 to 1 in accordance with the closeness among the opinion leaders and followers, which is closer to real life. Finally, the simulation results show that the proposed model can effectively explain the opinion interaction and evolution and conforms with the existing theoretical results in the field of opinion dynamics.
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| 7. |
- Xu, Jianqiang, et al.
(författare)
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Design of Smart Unstaffed Retail Shop Based on IoT and Artificial Intelligence
- 2020
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Ingår i: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 8, s. 147728-147737
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Tidskriftsartikel (refereegranskat)abstract
- Unstaffed retail shops have emerged recently and been noticeably changing our shopping styles. In terms of these shops, the design of vending machine is critical to user shopping experience. The conventional design typically uses weighing sensors incapable of sensing what the customer is taking. In the present study, a smart unstaffed retail shop scheme is proposed based on artificial intelligence and the internet of things, as an attempt to enhance the user shopping experience remarkably. To analyze multiple target features of commodities, the SSD (300x300) algorithm is employed; the recognition accuracy is further enhanced by adding sub-prediction structure. Using the data set of 18, 000 images in different practical scenarios containing 20 different type of stock keeping units, the comparison experimental results reveal that the proposed SSD (300x300) model outperforms than the original SSD (300x300) in goods detection, the mean average precision of the developed method reaches 96.1% on the test dataset, revealing that the system can make up for the deficiency of conventional unmanned container. The practical test shows that the system can meet the requirements of new retail, which greatly increases the customer flow and transaction volume.
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| 8. |
- Zhang, Han
(författare)
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Optimizing Networked Systems and Inverse Optimal Control
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis is concerned with the problems of optimizing networked systems, including designing a distributed energy optimal consensus controller for homogeneous networked linear systems, maximizing the algebraic connectivity of a network by projected saddle point dynamics. In addition, the inverse optimal control problems for discrete-time finite time-horizon Linear Quadratic Regulators (LQRs) are considered. The goal is to infer the Q matrix in the quadratic cost function using the observations (possibly noisy) either on the optimal state trajectories, optimal control input or the system output.In Paper A, an optimal energy cost controller design for identical networked linear systems asymptotic consensus is considered. It is assumed that the topology of the network is given and the controller can only depend on relative information of the agents. Since finding the control gain for such a controller is hard, we focus on finding an optimal controller among a classical family of controllers which is based on the Algebraic Riccati Equation (ARE) and guarantees asymptotic consensus. We find that the energy cost is bounded by an interval and hence we minimize the upper bound. Further, the minimization for the upper bound boils down to optimizing the control gain and the edge weights of the graph separately. A suboptimal control gain is obtained by choosing Q=0 in the ARE. Negative edge weights are allowed, meaning that "competitions" between the agents are allowed. The edge weight optimization problem is formulated as a Semi-Definite Programming (SDP) problem. We show that the lowest control energy cost is reached when the graph is complete and with equal edge weights. Furthermore, two sufficient conditions for the existence of negative optimal edge weights realization are given. In addition, we provide a distributed way of solving the SDP problem when the graph topology is regular.In Paper B, a projected primal-dual gradient flow of augmented Lagrangian is presented to solve convex optimization problems that are not necessarily strictly convex. The optimization variables are restricted by a convex set with computable projection operation on its tangent cone as well as equality constraints. We show that the projected dynamical system converges to one of the saddle points and hence finding an optimal solution. Moreover, the problem of distributedly maximizing the algebraic connectivity of an undirected network by optimizing the "port gains" of each nodes is considered. The original SDP problem is relaxed into a nonlinear programming (NP) problem that will be solved by the aforementioned projected dynamical system. Numerical examples show the convergence of the aforementioned algorithm to one of the optimal solutions. The effect of the relaxation is illustrated empirically with numerical examples. A methodology is presented so that the number of iterations needed to converge is reduced. Complexity per iteration of the algorithm is illustrated with numerical examples.In Paper C and D, the inverse optimal control problems over finite-time horizon for discrete-time LQRs are considered. The well-posedness of the inverse optimal control problem is first justified. In the noiseless case, when these observations of the optimal state trajectories or the optimal control input are exact, we analyze the identifiability of the problem and provide sufficient conditions for uniqueness of the solution. In the noisy case, when the observations are corrupted by additive zero-mean noise, we formulate the problem as an optimization problem and prove that the solution to this problem is statistically consistent. The following two scenarios are further considered: 1) the distributions of the initial state and the observation noise are unknown, yet the exact observations on the initial states and the noisy observations on the system output are available; 2) the exact observations on the initial states are not available, yet the observation noises are known to be white Gaussian and the distribution of the initial state is also Gaussian (with unknown mean and covariance). For the first scenario, we show statistical consistency for the estimation. For the second scenario, we fit the problem into the framework of maximum-likelihood and Expectation Maximization (EM) algorithm is used to solve this problem. The performance of the proposed method is illustrated through numerical examples.
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| 9. |
- Cao, Yuexin, et al.
(författare)
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Minimal Control Placement of Turing's Model Using Symmetries
- 2023
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Ingår i: 2023 62nd IEEE Conference on Decision and Control, CDC 2023. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1456-1461
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Konferensbidrag (refereegranskat)abstract
- In this paper, the minimal control placement prob-lem for Turing's reaction-diffusion model is studied. Turing's model describes the process of morphogens diffusing and reacting with each other and is considered as one of the most fundamental models to explain pattern formation in a devel-oping embryo. Controlling pattern formation artificially has gained increasing attention in the field of development biology, which motivates us to investigate this problem mathematically. In this work, the two-dimensional Turing's reaction-diffusion model is discretized into square grids. The minimal control placement problem for the diffusion system is investigated first. The symmetric control sets are defined based on the symmetry of the network structure. A necessary condition is provided to guarantee controllability. Under certain circumstances, we prove that this condition is also sufficient. Then we show that the necessary condition can also be applied to the reaction-diffusion system by means of suitable extension of the symmetric control sets. Under similar circumstances, a sufficient condition is given to place the minimal control for the reaction-diffusion system.
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| 10. |
- Cao, Yuexin, et al.
(författare)
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Network Controllability of Turing Reaction and Diffusion Model
- 2022
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Ingår i: 2022 41St Chinese Control Conference (Ccc). - : IEEE. ; , s. 259-264
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Konferensbidrag (refereegranskat)abstract
- In this paper, the controllability problem of the reaction-diffusion (RD) model, or Turing model is studied. Turing model provides a valuable framework for self-organized system and has been widely used to explain to pattern formation in the real life. With the rapidly development of the biology technology, biologists are trying to control the pattern formation artificially and has achieved some progress. However, the influence that exerted on the pattern formation by the external factors, such as light and temperature, remains to be solved. In this work, The RD model is obtained following the assumptions in Turing's original paper and spatially discretized into square grids. The nodes in the outermost layer are considered as candidates for control. Controllability of the RD system with all such nodes as control is first shown. Then controllability of the RD system with minimal number of control nodes is studied. Our results show that nearly 87.5% control nodes can be saved while the system is still controllable. Numerical simulations are provided to demonstrate the effects of controlling the reaction and diffusion of the morphogens.
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