针对高冗余蛇形机械臂在三维空间中的路径规划问题,结合快速搜索随机树算法(Rapidly-exploring Random Tree,RRT),提出角度约束快速搜索随机树算法(Angle Constraint Rapidly-exploring Random Tree,AC-RRT)。首先根据空间中障碍物分布...针对高冗余蛇形机械臂在三维空间中的路径规划问题,结合快速搜索随机树算法(Rapidly-exploring Random Tree,RRT),提出角度约束快速搜索随机树算法(Angle Constraint Rapidly-exploring Random Tree,AC-RRT)。首先根据空间中障碍物分布关系提出一种步长与目标偏置概率的确定方法,提高算法的自适应能力;其次根据蛇形机械臂机械结构提出一种随机树延伸的角度约束模型,使规划路径更加符合机械臂的空间运动特性;最后引入一种目标点贪婪查询方法,缩短路径搜索时间、减少冗余节点。通过Matlab仿真并对比与RRT和RRT-connect算法之间的性能差异,使用V-REP软件结合机械臂模型对算法模拟仿真,验证算法的可行性。结果表明AC-RRT算法路径规划用时更短、路径代价更小、路径轨迹更符合机械臂的运动特性。展开更多
Based on the ant colony system （ACS） algorithm and fuzzy logic control, a new design method for optimal fuzzy PID controller was proposed. In this method, the ACS algorithm was used to optimize the input/output scal...Based on the ant colony system （ACS） algorithm and fuzzy logic control, a new design method for optimal fuzzy PID controller was proposed. In this method, the ACS algorithm was used to optimize the input/output scaling factors of fuzzy PID controller to generate the optimal fuzzy control rules and optimal real-time control action on a given controlled object. The designed controller, called the Fuzzy-ACS PID controller, was used to control the CIP-Ⅰ intelligent leg. The simulation experiments demonstrate that this controller has good control performance. Compared with other three optimal PID controllers designed respectively by using the differential evolution algorithm, the real-coded genetic algorithm, and the simulated annealing, it was verified that the Fuzzy-ACS PID controller has better control performance. Furthermore, the simulation results also verify that the proposed ACS algorithm has quick convergence speed, small solution variation, good dynamic convergence behavior, and high computation efficiency in searching for the optimal input/output scaling factors.展开更多
In this paper, a new Modified Bacterial Foraging Algorithm (MBFA) method is developed to incorporate FACTS devices in optimal power flow (OPF) problem. This method can provide an enhanced economic solution with the us...In this paper, a new Modified Bacterial Foraging Algorithm (MBFA) method is developed to incorporate FACTS devices in optimal power flow (OPF) problem. This method can provide an enhanced economic solution with the use of controllable FACTS devices. Two types of FACTS devices, thyristor controlled series compensators (TCSC) and Static VAR Compensator (SVC) are considered in this method. The basic bacterial foraging algorithm (BFA) is an evolutionary optimization technique inspired by the foraging behavior of the E. coli bacteria. The strategy of the OPF problem is decomposed in two sub-problems, the first sub-problem related to active power planning to minimize the fuel cost function, and the second sub-problem designed to make corrections to the voltage deviation and reactive power violation based in an efficient reactive power planning of multi Static VAR Compensator (SVC). The specified power flow control constraints due to the use of FACTS devices are included in the OPF problem. The proposed method decomposes the solution of such modified OPF problem into two sub problems’ iteration. The first sub problem is a power flow control problem and the second sub problem is a modified Bacterial foraging algorithm (MBFA) OPF problem. The two sub problems are solved iteratively until convergence. Case studies are presented to show the effectiveness of the proposed method.展开更多
为了进一步提高LDPC码的性能,利用外在信息度(EMD)能准确表示环外节点的情况,构造了优化的LDPC码。同时,对构造过程中出现连通性较差的短环,采用破环(Cyc le Removal)操作来改善二部图局部的连通性。实验结果证明:在码长、码率和度分布...为了进一步提高LDPC码的性能,利用外在信息度(EMD)能准确表示环外节点的情况,构造了优化的LDPC码。同时,对构造过程中出现连通性较差的短环,采用破环(Cyc le Removal)操作来改善二部图局部的连通性。实验结果证明:在码长、码率和度分布相同的情况下,它较好的提高了码的性能。展开更多
文摘针对高冗余蛇形机械臂在三维空间中的路径规划问题,结合快速搜索随机树算法(Rapidly-exploring Random Tree,RRT),提出角度约束快速搜索随机树算法(Angle Constraint Rapidly-exploring Random Tree,AC-RRT)。首先根据空间中障碍物分布关系提出一种步长与目标偏置概率的确定方法,提高算法的自适应能力;其次根据蛇形机械臂机械结构提出一种随机树延伸的角度约束模型,使规划路径更加符合机械臂的空间运动特性;最后引入一种目标点贪婪查询方法,缩短路径搜索时间、减少冗余节点。通过Matlab仿真并对比与RRT和RRT-connect算法之间的性能差异,使用V-REP软件结合机械臂模型对算法模拟仿真,验证算法的可行性。结果表明AC-RRT算法路径规划用时更短、路径代价更小、路径轨迹更符合机械臂的运动特性。
基金Project(50275150) supported by the National Natural Science Foundation of ChinaProject(20040533035) supported by the National Research Foundation for the Doctoral Program of Higher Education of ChinaProject(05JJ40128) supported by the Natural Science Foundation of Hunan Province, China
文摘Based on the ant colony system （ACS） algorithm and fuzzy logic control, a new design method for optimal fuzzy PID controller was proposed. In this method, the ACS algorithm was used to optimize the input/output scaling factors of fuzzy PID controller to generate the optimal fuzzy control rules and optimal real-time control action on a given controlled object. The designed controller, called the Fuzzy-ACS PID controller, was used to control the CIP-Ⅰ intelligent leg. The simulation experiments demonstrate that this controller has good control performance. Compared with other three optimal PID controllers designed respectively by using the differential evolution algorithm, the real-coded genetic algorithm, and the simulated annealing, it was verified that the Fuzzy-ACS PID controller has better control performance. Furthermore, the simulation results also verify that the proposed ACS algorithm has quick convergence speed, small solution variation, good dynamic convergence behavior, and high computation efficiency in searching for the optimal input/output scaling factors.
文摘In this paper, a new Modified Bacterial Foraging Algorithm (MBFA) method is developed to incorporate FACTS devices in optimal power flow (OPF) problem. This method can provide an enhanced economic solution with the use of controllable FACTS devices. Two types of FACTS devices, thyristor controlled series compensators (TCSC) and Static VAR Compensator (SVC) are considered in this method. The basic bacterial foraging algorithm (BFA) is an evolutionary optimization technique inspired by the foraging behavior of the E. coli bacteria. The strategy of the OPF problem is decomposed in two sub-problems, the first sub-problem related to active power planning to minimize the fuel cost function, and the second sub-problem designed to make corrections to the voltage deviation and reactive power violation based in an efficient reactive power planning of multi Static VAR Compensator (SVC). The specified power flow control constraints due to the use of FACTS devices are included in the OPF problem. The proposed method decomposes the solution of such modified OPF problem into two sub problems’ iteration. The first sub problem is a power flow control problem and the second sub problem is a modified Bacterial foraging algorithm (MBFA) OPF problem. The two sub problems are solved iteratively until convergence. Case studies are presented to show the effectiveness of the proposed method.
