Fixed-time synchronization(FTS)of delayed memristor-based neural networks(MNNs)with discontinuous activations is studied in this *** continuous and discontinuous activations are considered *** the mixed delays which a...
详细信息
Fixed-time synchronization(FTS)of delayed memristor-based neural networks(MNNs)with discontinuous activations is studied in this *** continuous and discontinuous activations are considered *** the mixed delays which are closer to reality are taken into the ***,two kinds of control schemes are proposed,including feedback and adaptive control *** on some lemmas,mathematical inequalities and the designed controllers,a few synchronization criteria are ***,the upper bound of settling time(ST)which is independent of the initial values is ***,the feasibility of our theory is attested by simulation examples.
Complicated nonlinear intensity differences, nonlinear local geometric distortions, noises and rotation transformation are main challenges in multimodal image matching. In order to solve these problems, we propose a m...
详细信息
Retinal image registration is vital for diagnostic therapeutic applications within the field of ophthalmology. Existing public datasets, focusing on adult retinal pathologies with high-quality images, have limited num...
详细信息
Due to the demand for energy efficiency in electro-hydraulic systems, the separate meter in and separate meter out(SMISMO) control system attracts vast attention. In this paper, the SMISMO control system was configure...
详细信息
Due to the demand for energy efficiency in electro-hydraulic systems, the separate meter in and separate meter out(SMISMO) control system attracts vast attention. In this paper, the SMISMO control system was configured with two servo valves to control the meter in and meter out *** designing two of the proposed indirect adaptive robust dynamic surface controllers(IARDSC)for the working-side and off-side system and setting the coupled items as estimated parameters, the SMISMO control system was decoupled into two subsystems completely. Here, indirect adaptive robust control(IARC) was employed to address the internal parameter uncertainties and external *** surface control(DSC) was utilized in the backstepping design procedure of IARC to deal with the inherent ‘explosion of terms' problem. As thus, the proposed IARDSC could simplify the design procedure, decrease the computational cost, and achieve an improved control performance in practical use. Finally, experimental results validated the effectiveness of proposed IARDSC and showed that the proposed SMISMO control system could provide a possibility to save more energy.
The problem of generating optimal paths for curvature-constrained unmanned aerial vehicles (UAVs) performing surveillance of multiple ground targets is addressed in this paper. UAVs are modeled as Dubins vehicles so...
详细信息
The problem of generating optimal paths for curvature-constrained unmanned aerial vehicles (UAVs) performing surveillance of multiple ground targets is addressed in this paper. UAVs are modeled as Dubins vehicles so that the constraints of UAVs' minimal turning radius can be taken into account. In view of the effective surveillance range of the sensors equipped on UAVs, the problem is formulated as a Dubins traveling salesman problem with neighborhood (DTSPN). Considering its prohibitively high computational complexity, the Dubins paths in the sense of terminal heading relaxation are introduced to simplify the calculation of the Dubins distance, and a boundary-based encoding scheme is proposed to determine the visiting point of every target neighborhood. Then, an evolutionary algorithm is used to derive the optimal Dubins tour. To further enhance the quality of the solutions, a local search strategy based on approximate gradient is employed to improve the visiting points of target neighborhoods. Finally, by a minor modification to the individual encoding, the algorithm is easily extended to deal with other two more sophisticated DTSPN variants (multi-UAV scenario and multiple groups of targets scenario). The performance of the algorithm is demonstrated through comparative experiments with other two state-of-the-art DTSPN algorithms identified in literature. Numerical simulations exhibit that the algorithm proposed in this paper can find high-quality solutions to the DTSPN with lower computational cost and produce significantly improved performance over the other algorithms.
The multi-robot coverage motion planning(MCMP) problem in which every reachable area must be covered is common in multi-robot systems. To deal with the MCMP problem, we propose an efficient, complete, and off-line alg...
详细信息
The multi-robot coverage motion planning(MCMP) problem in which every reachable area must be covered is common in multi-robot systems. To deal with the MCMP problem, we propose an efficient, complete, and off-line algorithm, named the "auction-based spanning tree coverage(A-STC)" algorithm. First, the configuration space is divided into mega cells whose size is twice the minimum coverage range of a robot. Based on connection relationships among mega cells, a graph structure can be obtained. A robot that circumnavigates a spanning tree of the graph can generate a coverage trajectory. Then, the proposed algorithm adopts an auction mechanism to construct one spanning tree for each robot. In this mechanism, an auctioneer robot chooses a suitable vertex of the graph as an auction item from neighboring vertexes of its spanning tree by heuristic rules. A bidder robot submits a proper bid to the auctioneer according to the auction vertexes' relationships with the spanning tree of the robot and the estimated length of its trajectory. The estimated length is calculated based on vertexes and edges in the spanning tree. The bidder with the highest bid is selected as a winner to reduce the makespan of the coverage task. After auction processes, acceptable coverage trajectories can be planned rapidly. Computational experiments validate the effectiveness of the proposed MCMP algorithm and the method for estimating trajectory lengths. The proposed algorithm is also compared with the state-of-the-art algorithms. The comparative results show that the A-STC algorithm has apparent advantages in terms of the running time and the makespan for large crowded configuration spaces.
A model-based offline policy iteration(PI) algorithm and a model-free online Q-learning algorithm are proposed for solving fully cooperative linear quadratic dynamic games. The PI-based adaptive Q-learning method can ...
详细信息
A model-based offline policy iteration(PI) algorithm and a model-free online Q-learning algorithm are proposed for solving fully cooperative linear quadratic dynamic games. The PI-based adaptive Q-learning method can learn the feedback Nash equilibrium online using the state samples generated by behavior policies, without sending inquiries to the system model. Unlike the existing Q-learning methods, this novel Q-learning algorithm executes both policy evaluation and policy improvement in an adaptive *** prove the convergence of the offline PI algorithm by proving its equivalence to Newton's method while solving the game algebraic Riccati equation(GARE). Furthermore, we prove that the proposed Q-learning method will converge to the Nash equilibrium under a small learning rate if the method satisfies certain persistence of excitation conditions, which can be easily met by suitable behavior policies. Our simulation results demonstrate the good performance of the proposed online adaptive Q-learning algorithm.
This paper is devoted to further investigating the cloud control systems(CCSs). The benefits and challenges of CCSs are provided. Both new research results of ours and some typical work made by other researchers are p...
详细信息
This paper is devoted to further investigating the cloud control systems(CCSs). The benefits and challenges of CCSs are provided. Both new research results of ours and some typical work made by other researchers are presented. It is believed that the CCSs can have huge and promising effects due to their potential advantages.
The integrated sensing and communication (ISAC) system can simultaneously provide communication and radar sensing, effectively improving spectrum utilization. However, existing research mainly focuses on the mono-stat...
详细信息
We extend the traditional nonnegative reward testing with negative *** this new testing framework,may preorder and must preorder are the inverse of each *** surprisingly,it turns out that the real reward must testing ...
详细信息
We extend the traditional nonnegative reward testing with negative *** this new testing framework,may preorder and must preorder are the inverse of each *** surprisingly,it turns out that the real reward must testing is no more powerful than the nonnegative reward testing,at least for finite processes. In order to prove that result,we exploit an important property of failure simulation about the inclusion of the testing outcomes between two related processes.
暂无评论