1,720,994 research outputs found
Fuzzy PID controller simulation for a quarter-car semi-active suspension system using Magnetorheological damper
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Fuzzy logic with firefly algortihm for semi-active suspension system using magneto-rheological damper
No full textImplementation of PID controller tuning using differential evolution and genetic algorithms
Full text linkLink to publisher's homepage at http://www.ijicic.orgThis paper presents the implementation of PID controller tuning using two modern heuristic techniques which are differential evolution (DE) and genetic algorithm (GA). The optimal PID control parameters are applied for a high order system, system with time delay and non-minimum phase system. The performance of these techniques is evaluated by setting their objective functions as mean square error (MSE) and integral absolute error (IAE). The reliability between DE and GA in consistently maintaining minimum MSE is studied. The performance of the PID control systems tuned using GA and DE methods are also compared with Ziegler-Nichols method
Implementation of active control on flexibly mounted pipe exposed to vortex induced vibration using rotating rod
No full textPID controller tuning using evolutionary algorithms
Full text linkLink to publisher's homepage at http://www.wseas.orgThis paper presents the implementation of PID controller tuning using two sets of evolutionary techniques which are differential evolution (DE) and genetic algorithm (GA). The optimal PID control parameters are applied for a high order system, system with time delay and non-minimum phase system. The performance of the two techniques is evaluated by setting its objective function with mean square error (MSE) and integral absolute error (IAE). Both techniques will compete to achieve the globally minimum value of its objective functions. Meanwhile, reliability between DE and GA in consistently maintaining minimum MSE is also been studied. This paper also compares the performance of the tuned PID controller using GA and DE methods with Ziegler-Nichols method
Optimal placement of actuator for vibration suppression based on intelligent PID controller
Full text linkMany attempts have been proposed by the previous researchers due to reduce the undesired vibration by considering several control strategies. The simplest way in reducing the vibration is to build more rigid structure so that less vibration will be produced. Nevertheless, this strategy is usually not applicable since the structures are need high power consumption and limitation in operation speed. Furthermore, it becomes a growing trend among the industries to use light weight of mechanical structure known as flexible plate. However, the critical problem faced by the industries is vibration on the structure that can lead to structural damage. Hence, this research presents the optimal placement of actuator and sensor on the experimental rig for vibration cancelation of the flexible plate structure based on intelligent PID controller. The PID controller tuned by artificial bee colony (ABC) algorithm was used to control the undesired vibration on the structure. The robustness of developed controller was validated by varying the position of actuator on the experimental rig. It was indicated that point A2 leads to the good attenuation level by achieving highest attenuation value at the first mode of vibration with 28.83 dB which is equivalent to 21.62 % attenuation, after the introduction of vibration control
Active Vibration Control of Flexible Beam using Differential Evolution Optimisation
No full textThis paper presents the development of an active
vibration control using direct adaptive controller to suppress the
vibration of a flexible beam system. The controller is realized based
on linear parametric form. Differential evolution optimisation
algorithm is used to optimize the controller using single objective
function by minimizing the mean square error of the observed
vibration signal. Furthermore, an alternative approach is developed to
systematically search for the best controller model structure together
with it parameter values. The performance of the control scheme is
presented and analysed in both time and frequency domain.
Simulation results demonstrate that the proposed scheme is able to
suppress the unwanted vibration effectively
Self-tuning PID controller for active suspension system with hydraulic actuator
No full textThis paper investigated the performance of PID controller for active suspension system. A half car model has been simulated by using an analytical model within Matlab SIMULINK environment. Three different road disturbances, namely, the bump and hole, sine and random input have been applied to disturb the suspension system. Based on these three road disturbances, the performances of passive and active suspension system were investigated. Moreover, for active suspension system, hydraulic actuator was included in the simulation and PID controller was introduced. Three tuning methods namely heuristic tuning, Ziegler-Nichols (ZN) tuning, and iterative learning algorithm (ILA) were used to obtain the optimum value of the PID controller parameters. A comparative study was carried out between active and passive suspension systems, and these three methods of tuning the PID controller. The active suspension system has been proven to perform better than the passive suspension system provided the PID controller parameters are tuned properly. Also, in this investigation, the comparative assessment indicated that the PID controller tuned by the iterative learning algorithm for active suspension system with hydraulic actuator has performed better than the other two tuning algorithms
Active vibration control of a flexible beam using system identification and controller tuning by evolutionary algorithm
Full text linkLink to publisher’s homepage at http://jvc.sagepub.comThis paper presents a new approach of proportional-integral-derivative (PID) controller tuning via an evolutionary algorithm that optimally suppresses the vibration of a flexible beam system using a piezoelectric actuator. The system's dynamic model is identified based on autoregression with exogenous input (ARX) structure using recursive least square. The input-output data were obtained experimentally. This ARX model represents the physical system and is used for the controller optimization process. Evolutionary algorithms such as differential evolution (DE) and genetic algorithms (GA) were applied to optimize and tune the controller parameters offline based on a defined performance index, i.e. mean square error of the vibration signals. The optimum PID parameters were validated experimentally. The performance of PID tuned by DE and GA are compared with conventional PID tuning (using Ziegler Nichols method). Experimental study showed that PID tuned by DE and GA offer a better transient response than the conventional tuning method
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