Open-loop controller

About: Open-loop controller is a research topic. Over the lifetime, 16148 publications have been published within this topic receiving 224014 citations. The topic is also known as: non-feedback controller & open-loop control law.

Method and apparatus for tuning control system parameters

Abstract: A method and apparatus for tuning control loop parameters in a motion control system, is provided. In one embodiment, tuning of the proportional and integral gains of a servocontroller's velocity loop compensator is provided, as well as tuning of the cutoff frequencies of the servocontroller's low pass filters. In this embodiment, random noise excitation is added to the velocity command during a plurality of movement types for a machine tool axis. During each movement type, frequency response measurements are taken. Then, a composite frequency response can be selected by concatenating portions of the various frequency response measurements, so as to simulate a worst case scenario for the machine tool axis. From this composite response, an open loop response can be calculated and displayed, as well as bandwidth, phase margin, and gain margin values. The user can then enter the compensator parameters which were used when this data was taken, as well as proposed parameters. The system can automatically predict, or simulate, the effects of the proposed parameters on bandwidth, gain margin, and phase margin, based upon the composite data. Accordingly, the user need not actually try out the proposed parameters on the machine. Moreover, the simulated responses for the proposed parameters are based upon actual frequency response data taken during actual operating conditions of the system, and, accordingly, the inaccuracies of using mathematical assumptions are avoided.

Tuning of Field-Oriented Induction Motor Controllers for High-Performance Applications

Abstract: A tuning procedure for high-performance (e.g., axis feed type) applications of feedforward field-oriented controllers is developed and demonstrated. The theoretical basis of the procedure is explained via a novel form of dq vector diagram. This diagram displays both steady and transient states simultaneously. This format also provides substantial insight into the expected behavior of mistuned controllers, especially for analyzing transient torque performance. The procedure is unambiguous to implement, and it requires no additional sensors beyond those required for the feedforward controller.

Design of Automatic Steering Controller for Trajectory Tracking of Unmanned Vehicles Using Genetic Algorithms

Abstract: In this paper, an efficient strategy is proposed to design the automatic steering controller for trajectory tracking of unmanned vehicles, which is robust with respect to the inherent nonlinearities and uncertainties of vehicles. The proposed automatic steering controller consists of a feedback part and a feedforward part. First, a fuzzy controller is proposed as the feedback part, and the parameters of membership functions and rules are optimized by genetic algorithms (GAs) to guarantee high performance. Then, a feedforward controller is designed to assist the controller when the vehicle is engaged in a curved section of trajectory, which utilizes preview information regarding upcoming curvature of reference trajectory to calculate a preview steering angle so that it offsets the disturbance of curvature. Both simulation and experimental results show that the proposed strategy can robustly track the reference trajectories under various conditions with high accuracy.

Speed control of Brushless DC motor using bat algorithm optimized Adaptive Neuro-Fuzzy Inference System

Abstract: Bat algorithm optimized online ANFIS based speed controller presented for Brushless DC motor.The speed response of Brushless DC motor is analyzed for different operating conditions.The proposed controller eliminates the uncertainty problem due to load disturbance and set speed variations.The proposed controller enhances the time domain specifications and performance indices in all operating conditions. In this paper, speed control of Brushless DC motor using Bat algorithm optimized online Adaptive Neuro-Fuzzy Inference System is presented. Learning parameters of the online ANFIS controller, i.e., Learning Rate (?), Forgetting Factor (λ) and Steepest Descent Momentum Constant (α) are optimized for different operating conditions of Brushless DC motor using Genetic Algorithm, Particle Swarm Optimization, and Bat algorithm. In addition, tuning of the gains of the Proportional Integral Derivative (PID), Fuzzy PID, and Adaptive Fuzzy Logic Controller is optimized using Genetic Algorithm, Particle Swarm Optimization and Bat Algorithm. Time domain specification of the speed response such as rise time, peak overshoot, undershoot, recovery time, settling time and steady state error is obtained and compared for the considered controllers. Also, performance indices such as Root Mean Squared Error, Integral of Absolute Error, Integral of Time Multiplied Absolute Error and Integral of Squared Error are evaluated and compared for the above controllers. In order to validate the effectiveness of the proposed controller, simulation is performed under constant load condition, varying load condition and varying set speed conditions of the Brushless DC motor. The real time experimental verification of the proposed controller is verified using an advanced DSP processor. The simulation and experimental results confirm that bat algorithm optimized online ANFIS controller outperforms the other controllers under all considered operating conditions.

Stand alone induction generator with terminal impedance controller and no turbine controls

Abstract: Induction generators with hydraulic turbines are often used for cogeneration The same turbine generator configuration can be used for stand-alone generation if an impedance controller is connected to the generator terminals; this configuration requires no hydraulic controls on the turbine The authors propose an electronic impedance controller to control the voltage and the frequency of a stand-alone induction generator The controller concept and its control range are discussed Particular attention is given to the harmonic distortion caused by the controller and measures to reduce these distortions The controller design is discussed, and data from an experimental generator set are provided to verify the proposed concept >