Iterative Control is used to obtain high tracking performance on vibration testing equipments. It is important to find proper frequency response function for Iterative Control because it has information of real system...
详细信息
ISBN:
(纸本)9781479922802
Iterative Control is used to obtain high tracking performance on vibration testing equipments. It is important to find proper frequency response function for Iterative Control because it has information of real system. Signal processing to make proper frequency response function for Iterative Control has been investigated. Electrohydraulic actuated system was considered as theoretical model. Main performance parameters were found by considering the convergence of Iterative Control Algorithm. Signal processing to make proper frequency response function for Iterative Control was suggested on the basis of previous described works. The usefulness of suggested signal processing method was verified by testing the Iterative Control algorithm on 1 axle vibration testing equipment.
This paper describes the development of a Cooperative Adaptive Cruise Control (CACC) for the future urban transportation system at low-speed. The control algorithm was evaluated using two Cybecars as prototype vehicle...
详细信息
ISBN:
(纸本)9781479960781
This paper describes the development of a Cooperative Adaptive Cruise Control (CACC) for the future urban transportation system at low-speed. The control algorithm was evaluated using two Cybecars as prototype vehicles. A longitudinal response model for the vehicles was developed to design the CACC system. The control algorithm was implemented on a fuzzy logic-based controller that has been tuned to minimize a cost function in order to get a trade-off between a proper car-following gap error and the smoothness of the control signal. The controller was firstly tested in simulation using the developed model. Then, the CACC was implemented in two Cybecars to validate the controller performance in real scenarios.
In this paper, an adaptive fuzzy iterative learning control algorithm is proposed for controlling one of the Mechatronics systems. The proposed control scheme is based upon a proportional-derivative-integral (PID) ite...
详细信息
ISBN:
(纸本)9781479937325
In this paper, an adaptive fuzzy iterative learning control algorithm is proposed for controlling one of the Mechatronics systems. The proposed control scheme is based upon a proportional-derivative-integral (PID) iterative learning control (ILC), for which a fuzzy control is added to tune the parameters of the PID-type ILC. Moreover, an adaptation law is added to the fuzzy control in order to automatically select the proper fuzzy membership functions. The performance of proposed algorithm was assessed in computer numerical controlled (CNC) machine X-Y table to illustrate the validation and the effectiveness of the proposed procedure. The simulation results show that the proposed algorithm can reduce the trajectory error in a far less number of iterations.
It is widely known that Ethernet networks are susceptible to high-power electromagnetics (HPEM). Even with electromagnetic disturbance levels below the threshold, at which a hardware failure of components can be obser...
详细信息
ISBN:
(纸本)9781479955459
It is widely known that Ethernet networks are susceptible to high-power electromagnetics (HPEM). Even with electromagnetic disturbance levels below the threshold, at which a hardware failure of components can be observed, there are impacts on the data transmission between two computers. A typical effect on the application level is a decrease of the maximum data rate between two endpoints with a higher field strength until the transmission completely breaks down. To quantify the effect of electromagnetic disturbances it is necessary to distinguish between effects which are software-related due to control algorithms and applications behaviour on higher protocol layers, and hardware -related effects caused by physical interaction between the network components and the disturbance. This paper shows the results of a new measurement method compared to classical tests using a FTP data transmission.
Dynamic pallet routing optimal control is a crucial task for evolutionary manufacturing plants in order to guarantee efficient production plant performances. In this paper, a new approach based on hybrid Model Predict...
详细信息
ISBN:
(纸本)9781479974092
Dynamic pallet routing optimal control is a crucial task for evolutionary manufacturing plants in order to guarantee efficient production plant performances. In this paper, a new approach based on hybrid Model Predictive Control (MPC) is proposed to control a manufacturing multi-target, multi-pallet transport line. The mathematical representation of the plant is based on a Mixed Linear Dynamical (MLD) model, used by MPC to predict the plant behavior in terms of the future evolution of the state and control variables. The performance index to be minimized is linear and weights the distance of the pallets from their final target. The resulting Mixed Linear Integer Programming (MILP) problem is recursively solved to obtain the control law. Many simulation experiments have been carried out to evaluate the performances of the proposed approach in a realistic scenario. The achieved results confirm the good performances of the control algorithm and its ability to manage even pallet route conflicts and target dynamic re-scheduling.
New method for maximization of the energy transformation efficiency of wind energy systems is developed. The maximization is assumed to be equivalent to the maximization of the the energy transformation efficiency fro...
详细信息
ISBN:
(纸本)9781479974092
New method for maximization of the energy transformation efficiency of wind energy systems is developed. The maximization is assumed to be equivalent to the maximization of the the energy transformation efficiency from the wind energy to the blades rotational energy. Extremum seeking control is applied to wind energy systems in the face of aerodynamic uncertainties. In the existing methods, maximization is achieved by adding periodic external signals to the input signal. We develop a control algorithm that achieves the maximization of the energy transformation efficiency by utilizing the periodic fluctuation of the rotational speed of the blades with the tower shadow effect as an external periodic signal. A numerical simulation result is provided to show efficacy of the proposed approach.
This book thoroughly discusses computationally efficient (suboptimal) Model Predictive Control (MPC) techniques based on neural models. The subjects treated include: A few types of suboptimal MPC algorithms in which a...
详细信息
ISBN:
(数字)9783319042299
ISBN:
(纸本)9783319042282;9783319042299
This book thoroughly discusses computationally efficient (suboptimal) Model Predictive Control (MPC) techniques based on neural models. The subjects treated include: A few types of suboptimal MPC algorithms in which a linear approximation of the model or of the predicted trajectory is successively calculated on-line and used for prediction. Implementation details of the MPC algorithms for feed forward perceptron neural models, neural Hammerstein models, neural Wiener models and state-space neural models. The MPC algorithms based on neural multi-models (inspired by the idea of predictive control). The MPC algorithms with neural approximation with no on-line linearization. The MPC algorithms with guaranteed stability and robustness. Cooperation between the MPC algorithms and set-point optimization. Thanks to linearization (or neural approximation), the presented suboptimal algorithms do not require demanding on-line nonlinear optimization. The presented simulation results demonstrate high accuracy and computational efficiency of the algorithms. For a few representative nonlinear benchmark processes, such as chemical reactors and a distillation column, for which the classical MPC algorithms based on linear models do not work properly, the trajectories obtained in the suboptimal MPC algorithms are very similar to those given by the ``ideal'' MPC algorithm with on-line nonlinear optimization repeated at each sampling instant. At the same time, the suboptimal MPC algorithms are significantly less computationally demanding.
In recent years, the large development of light and flexible structures led to a wide interest about techniques for active vibration suppression. Indeed, these structures are typically characterized by low damping and...
详细信息
ISBN:
(纸本)9781479974092
In recent years, the large development of light and flexible structures led to a wide interest about techniques for active vibration suppression. Indeed, these structures are typically characterized by low damping and, consequently, by a significant amplification of vibrations, especially when the structure is forced close to its natural frequencies. System vibrations result in high stresses of the material, which may strongly reduce the structure lifetime. For this reason, all the techniques able to reduce vibrations and stresses are of great interest. Most of the researches focused on the vibration suppression, assuming that the fatigue reduction would be a direct consequence. Anyway, even if in many applications it can be regarded as true, there are some cases in which vibration reduction does not automatically imply an improvement in terms of fatigue life. For this reason, this paper proposes a new approach, able to take into account the fatigue phenomemon directly in the definition of the control algorithm. The proposed approach is firstly introduced from a theoretical point of view, describing the control algorithm and how it deals with the fatigue damaging. Then, the control logic is tested both numerically and experimentally on a plate instrumented with accelerometers, strain gauges and piezoelectric actuators. A comparison between the proposed solution and state of the art control techniques is proposed and critically analyzed to demonstrate how the fatigue life of the structure can be improved.
Biologically inspired control approaches have been attracted much attention as alternatives in recent time, for efficiently solving problems in controlling multi-DOF robotic systems, since most human beings or animals...
详细信息
ISBN:
(纸本)9781479967650
Biologically inspired control approaches have been attracted much attention as alternatives in recent time, for efficiently solving problems in controlling multi-DOF robotic systems, since most human beings or animals exhibit their behaviors in a natural way without explicit computation. Also, they show natural adaptive behaviors irrespective of unexpected external forces or changes of environment. This work is inspired from these novel features. Thus, a self-adapting robotic arm-hand control is proposed exploiting a control scheme based on central pattern generators (CPGs). Instead of a trajectory planning and inverse kinematics problem, this work endeavors to exploit robotic systems coupled with neural oscillators and virtual forces with joint velocity damping. We demonstrate self-adapting motions without the ill-posedness from extensive simulations that enable a robotic arm-hand to make adaptive changes from the given motion to a compliant motion. In addition, it is verified that reaching-to-grasping motion is possible by adopting only transit points sustaining motion repeatability under kinematic redundancy of joints.
This paper presents a control algorithm for an air multi-compressor system. The goal is to achieve adequate performance in terms of air pressure regulation by properly coordinating a set of compressors driven by fixed...
详细信息
ISBN:
(纸本)9781479940226
This paper presents a control algorithm for an air multi-compressor system. The goal is to achieve adequate performance in terms of air pressure regulation by properly coordinating a set of compressors driven by fixed speed motors. The coordination is required to impose an upper bound to the activation frequency of electric drives. A multi-compressor system is intended to be a viable alternative to compressor systems based on Variable Speed Drives (VSD) operated by inverters, which suffer of several technical and economic drawbacks. The control strategy is based on the evaluation of the timing associated to activations/deactivations of each compressor. Such evaluation is determined by the values of physical variables that determine the system behavior, including air flows, pressures and temperature. The periodic measurement of the actual pressure is performed to dynamically adjust the estimation of relevant time instants in case of variations of working conditions. The algorithm takes into account the dynamics of the air pressure, as well as timing constraints on the minimum period between two subsequent activations of each compressor. The effectiveness of the multi-compressor solution is evaluated by simulation.
暂无评论