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.

A self-tuning controller for the control of multi-machine power systems

Abstract: An adaptive synchronous machine controller that minimizes a cost function incorporating system input, output, and set-point variations, and its application to a multimachine power system are described. The control is based on a criterion of automatically shifting the closed loop poles of the system towards the origin in the z-domain without violating the control constraints. It possesses the property of robustness and ease of reference signal tracking. The ability of the proposed controller to damp multimode oscillations is investigated. Studies show that the proposed controller cooperates with the conventional power-system stabilizers on the system in damping the oscillations. >

Design Artificial Nonlinear Controller Based on Computed Torque like Controller with Tunable Gain

Abstract: One of the most active research areas in the field of robotics is robot arms control, because these systems are multi-input multi-output (MIMO), nonlinear, time variant and uncertainty. An artificial non linear robust controller design is major subject in this work. At present, robot manipulators are used in unknown and unstructured situation and caused to provide complicated systems, consequently nonlinear classical controllers are used in artificial intelligence control methodologies to design nonlinear robust controller with satisfactory performance (e.g. minimum error, good trajectory, disturbance rejection). Computed torque controller (CTC) is the best nonlinear robust controllers which can be used in uncertainty nonlinear. Computed torque controller works very well when all nonlinear dynamic parameters are known. This research is focused on the applied non- classical method (e.g. Fuzzy Logic) in robust classical method (e.g. computed torque controller) in the presence of uncertainties and external disturbance to reduce the limitations. Applying the Mamdani's error based fuzzy logic controller with minimum rules is the first goal that causes the elimination of the mathematical nonlinear dynamic CTC. Second target focuses on the elimination of oscillation with regard to the variety of uncertainty and external disturbance in computed torque like controller by optimization the tunable gain. Therefore computed torque like controller with tunable gain (GTCTLC) will be presented in this paper.

Maiden application of hybrid pattern search-biogeography based optimisation technique in automatic generation control of a multi-area system incorporating interline power flow controller

Abstract: This study exhibits the automatic generation control (AGC) of an unequal three-area thermal system having single reheat turbine, generation rate constraint, and governor dead band, in all areas. A three-degree-of-freedom proportional-integral-derivative (3DOF-PID) controller is used as secondary controller in all the areas and its dynamic performance is compared with that of classical PI, ID, and PID controllers. The controller parameters are simultaneously optimised using biogeography-based optimisation (BBO) technique, where 3DOF-PID controller outperforms the other. A hybrid pattern search BBO (hPS-BBO) technique is applied for the first time in AGC, to simultaneously optimise 3DOF-PID controller parameters. Comparison of dynamic responses corresponding to BBO and hPS-BBO optimised 3DOF-PID controller gives better performance of the latter. This is also validated with random disturbance. The considered system is checked for optimal location of interline power flow controller (IPFC) using BBO optimised 3DOF-PID controller. Observations reveal that IPFC placed between Line1 and Line3 is the optimal location. A comparatively better response is observed with hPS-BBO optimised 3DOF-PID controller parameters, having IPFC placed in its optimal location. Sensitivity analysis of the hPS-BBO optimised 3DOF-PID controller parameters is tested and found satisfactory for variations in system loading and inertia constant H .

A Neural Network Inverse Model for a Shape Memory Alloy Wire Actuator

Abstract: Tracking control of shape memory alloy (SMA) actuators is essential in many applications such as vibration controls. Due to the hysteresis, an inherent nonlinear phenomenon associated with SMAs, open-loop control design has proven inadequate for tracking control of these actuators. Aimed at eliminating the position sensor to reduce cost of an SMA actuator system, in this paper, a neural network open loop controller is proposed for tracking control of an SMA actuator. A test stand, including a titanium-nickel (TiNi, or Nitinol) SMA wire actuator, a position sensor, bias springs, and a programmable current amplifier, is used to generate training data and to verify the neural networks open loop controller. A digital data acquisition and real-time control system was used to record experimental data and to implement the control strategy. Based on the training data obtained from the test stand, two neural networks are used to respectively model the forward and inverse hysteresis relations between the applied voltage and the displacement of the SMA wire actuator. To control the SMA actuator without using a position sensor, the neural network inverse model is used as a feedforward controller. The experimental results demonstrate the effectiveness of the neural network open loop controller for tracking control of the SMA wire actuator.