This paper presents a recently developed Hybrid Multi-Swarm Particle Swarm Optimization (HMPSO) algorithm for multi-objective optimalreactive power control (ORPC) for minimizing real power loss and improving voltage s...
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ISBN:
(纸本)9781509012770
This paper presents a recently developed Hybrid Multi-Swarm Particle Swarm Optimization (HMPSO) algorithm for multi-objective optimalreactive power control (ORPC) for minimizing real power loss and improving voltage stability. Optimal reactive power control in electrical power system is a single objective or a multi-objective, non-linear, constrained optimization problem that can be solved by applying any optimization technique. HMPSO is a recently developedevolutionary computing based optimization algorithm, in which the existing swarm is divided into several sub-swarms. For each sub-swarm, PSO algorithm is implemented as the search engine. In addition to this, differential evolution (DE) algorithm is applied to improve the personal best of each particle. To find the Pareto optimal set for the ORPC problem, the weighted sum method has been used. Consequently, to extract the best compromise solution out of the Pareto-optimal set, fuzzy based mechanism has been used. Effectiveness of the HMPSO algorithm for solving ORPC problem has been establishedby applying it on the ieee 30-bus system.
Robot manipulation has been an interesting topic for researchers over decades. While researches are going on, different problems occurred. One of the most important problems is energy consumption. Because operation ti...
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Robot manipulation has been an interesting topic for researchers over decades. While researches are going on, different problems occurred. One of the most important problems is energy consumption. Because operation time of mobile robots is fully related with energy consumption. In this study two main problems are taken into consideration, first one is minimization of energy consumption and second one is obstacle avoidance. For this purpose, a simple robot manipulator with two degrees of freedom is chosen. The objective function is selected as a function of applied torque values at the joints, minimization of objective function, results in minimization of motor currents. The algorithm checks if there is a contact between the obstacles and the manipulator, while the algorithm is searching for the trajectory polynomial that requires minimum energy consumption. Finally, the algorithm finds the trajectory polynomial that contains no contact between the manipulator and the obstacles, also minimizes energy consumption.
Today India trends towards the Research Development as the Research leads to make the country developed. In all the several Disciplines in Research Power system shows the great embark in development. DVR is used for c...
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In order to deal with constrained characteristics in the closed-loop industrial processes, a constrained applied predictive control(CAPC) method based on closed-loop subspace identification is proposed. The state-spac...
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ISBN:
(纸本)9781509028146
In order to deal with constrained characteristics in the closed-loop industrial processes, a constrained applied predictive control(CAPC) method based on closed-loop subspace identification is proposed. The state-space model is obtained through the closed-loop subspace identification algorithm, which is regarded as the system model. Then, the model is used to design the model predictive controller which involves the solution of a quadratic program solving constraints. The paper presents a comparison of performance given by proposed control method when applied to a 2-CSTR system with an open-loop subspace CAPC method, the superiority of the proposed method is illustrated through the simulation results.
Dynamic analysis technique extracts malicious behavior by monitoring the execution of malware. But due to the differences between analysis environment and real environment, Malware can easily hide its malicious behavi...
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Dynamic analysis technique extracts malicious behavior by monitoring the execution of malware. But due to the differences between analysis environment and real environment, Malware can easily hide its malicious behavior in suspicious environment. This paper proposed a method in detecting environment-sensitive malware based on taint analysis, which monitored the use of environment-sensitive features, and detected malicious behavior by executing along hidden path. Our approach firstly extracted sensitive system calls and special instructions to mark tainted features, then achieved environment-sensitive controlled jump based on taint propagation analysis while code was running, and at last forced execution along different paths according to the extraction of path jump constraint conditions. We designed and implemented a prototype that can be automatically applied on malware analysis. The evaluation of the prototype by comparing with static and dynamic tools showed it can recognize the environment-sensitive features comprehensively, and can effectively increase the ability in malware detection with high efficiency.
This paper focuses on optimal tuning of PI controller in motor vector controlsystem by using hybrid system composed of GA (Genetic Algorithm) and BA (Bacterial Foraging). Generally, vector control of motor has three ...
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ISBN:
(纸本)9783319272474;9783319272450
This paper focuses on optimal tuning of PI controller in motor vector controlsystem by using hybrid system composed of GA (Genetic Algorithm) and BA (Bacterial Foraging). Generally, vector control of motor has three PI controllers to control speed and current. In this case, engineer has to tune 6-parameters simultaneously on site. Therefore, it is difficult to tune in high speed motor controlsystem. Also, they cannot sometimes obtain optimal parameters of PI controller using only manually or traditional approaches or conventional artificial intelligence such as GA (Genetic Algorithm), FZ (Fuzzy), NN (Neural Network), and etc. because of local solution and low speed computing characteristics. To obtain optimal gain for vector control and good computing characteristics in high speed, this paper deals with applying hybrid system by GA and BA.
Since traditional methods of training have been insufficient for the rehabilitation, diversities of robots are being introduced to assist patients, doctors, and trainers. In this research, a novel 7-DOF exoskeleton ro...
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ISBN:
(纸本)9781467389594
Since traditional methods of training have been insufficient for the rehabilitation, diversities of robots are being introduced to assist patients, doctors, and trainers. In this research, a novel 7-DOF exoskeleton robot for upper limb rehabilitation is proposed. 6 DOF arc actuated by micro motor which is equipped at the each DOF of the robot. controlled method is proposed for the robot to actuate the motor to assist users in movement. Simulation and experiment are performed to evaluate the accuracy of the robot.
Temporal reasoning is one of the cognitive capabilities humans involve in communicating with others and everything appears related because of temporal reference. Therefore, in this paper a geometric dynamic temporal r...
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ISBN:
(纸本)9781509038466
Temporal reasoning is one of the cognitive capabilities humans involve in communicating with others and everything appears related because of temporal reference. Therefore, in this paper a geometric dynamic temporal reasoning algorithm is proposed to solve the temporal reasoning problem, especially in autonomous planning and scheduling. This method is based on the representation of actions in a two dimensional coordination system. The main advantage of this method over others is that it uses tags to mark new constraints added into the constraint network, which leads the algorithm to deal with pending constraints rather than all constraints. This characteristic makes the algorithm suitable for temporal reasoning, where variables and constraints are always added dynamically. This algorithm can be used not only in intelligent planning, but also computational intelligence, real-time systems, and etc. The results show the efficiency of our algorithm from four cases simulating the planning and scheduling process.
In this paper, we propose an intelligent nursing bed system which is controlled by a hybrid brain-computer interface (BCI) involving steady-state visual evoked potential (SSVEP) and P300. Specifically, the hybrid BCI ...
ISBN:
(纸本)9781457702204
In this paper, we propose an intelligent nursing bed system which is controlled by a hybrid brain-computer interface (BCI) involving steady-state visual evoked potential (SSVEP) and P300. Specifically, the hybrid BCI includes an asynchronous brain switch based on SSVEP and P300, and a P300-based BCI. The brain switch is used to turn on/off the controlsystem of the electric nursing bed through idle/control state detection, whereas the P300-based BCI is for operating the nursing bed. At the beginning, the user may focus on one group of flashing buttons in the graphic user interface (GUI) of the brain switch, which can simultaneously evoke SSVEP and P300, to switch on the controlsystem. Here, the combination of SSVEP and P300 is used for improving the performance of the brain switch. Next, the user can control the nursing bed using the P300-based BCI. The GUI of the P300-based BCI includes 10 flashing buttons, which correspond to 10 functional operations, namely, left-side up, left-side down, back up, back down, bedpan open, bedpan close, legs up, legs down, right-side up, and right-side down. For instance, he/she can focus on the flashing button "back up" in the GUI of the P300-based BCI to activate the corresponding control such that the nursing bed is adjusted up. Eight healthy subjects participated in our experiment, and obtained an average accuracy of 93.75% and an average false positive rate (FPR) of 0.15 event/min. The effectiveness of our system was thus demonstrated.
This paper investigates the relative position control problem for a two-agent spacecraft formation. The modified nonlinear dynamic based on C-W equation is adopted to describe relative position between the leader and ...
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ISBN:
(纸本)9781467398725
This paper investigates the relative position control problem for a two-agent spacecraft formation. The modified nonlinear dynamic based on C-W equation is adopted to describe relative position between the leader and follower. Considering the system uncertainty and external disturbance, adaptive sliding mode control laws based on linear and terminal sliding surface are proposed respectively. In addition, a switching mechanism is employed to make a selection between the general and terminal surfaces so as to avoid singularity. The convergence of closed-loop system is proved by Lyapunov stability theory. Numerical simulations illustrates the validity of the control law proposed.
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