Sensitivity Of Control System Research Articles

A Highly Accurate Model-Free Motion Control System with a Mamdani Fuzzy Feedback Controller combined with a TSK Fuzzy Feed-forward Controller

In this paper, a new intelligent robot motion control architecture --- a highly accurate model-free fuzzy motion control- is proposed in order to achieve improved robot motion accuracy and dynamic performance. Its architecture combines a Mamdani fuzzy proportional (P) and a conventional integral (I) plus derivative (D) controller for the feedback part of the system, and a Takagi-Sugeno-Kang fuzzy controller for the feed-forward, nonlinear part. The fuzzy P + ID controller improves the performance of the nonlinear system, and the TSK fuzzy controller uses a TSK fuzzy inference system based on extended subtractive- clustering method which integrates information on joint angular displacement, velocity and acceleration for torque identification. The advantage of this kind of model-free control is that it uses the information directly from the input/output of the nonlinear system, without any complex robot model computation, in order to decrease the control system's sensitivity to any dynamical uncertainty. Furthermore, parametric search for clustering parameters in extended subtractive clustering secures the high accuracy of the system identification. Consequently, this proposed model-free fuzzy motion control benefits from the advantages of two kinds of fuzzy system. It not only incorporates flexible design, good performance and simple conception but also ensures precise motion control and great robustness. Comparisons with other intelligent models and results from numerical studies on a 4-bar planar parallel mechanism show the effectiveness and competitiveness of the proposed control.

Voltage Controller for a Synchronous Generator with Exciter

In this paper, the excitation controller for a synchronous generator (SG) with an exciter is presented, based on novel stabilization feedback actions comprising the SG rotor current and rotor voltage measurements. The novel stabilizing feedback actions are used to compensate the dynamic lag introduced by the exciter machine, and to improve the overall excitation system's dynamic performance without employing differential control actions. Namely, by avoiding differential control actions, an improved level of performance can be achieved without compromising the control system's sensitivity in relation to the measurement noise. Also, compared with the existing solutions based on a different set of stabilizing feedback signals, the controlling structure proposed in this paper enables a more stable and faster dynamic response, which is illustrated in the paper by means of the system frequency response analysis. The performance of the proposed solution is verified through the set of simulation and experimental runs presented in the paper. While the controller design is based on a simplified generator model, the simulations are carried out using the full order generator and exciter models. The experimental tests were carried out on a 300 MW thermal power plant aggregate with an AC exciter.

An analytical and experimental study of a control system's sensitivity to structural modifications

Two aspects of the sensitivity of a control system to minor structural modifications are discussed. The first is the sensitivity of the performance of the control system, which is usually associated with the robustness of the system. The second is the sensitivity of the optimum design of the control system, which is important in the assessment of the need for combined control/structural design. The two aspects of sensitivity are demonstrated for a flexible laboratory structure controlled by several rate-feedback colocated force-actuator velocity-sensor pairs. Both the performance and the optimum design of the control system are shown to be quite sensitive to structural modifications. Analytical predictions of sensitivity are validated experimentally.