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.

Modular remote controller

Abstract: Provided is a modular remote controller assembled by the connection of modules chosen based on desired functions, wherein each of the modules is constructed for one function of the remote controller. The modular remote controller includes: a main remote controller which generates a remote control signal for remote controlling an electronic apparatus in response to one of an internal control signal, which is internally generated in response to a key input, and an external control signal; and at least one remote controller extension module which is detachably coupled to the main remote controller and generates the external control signal.

A novel interval type-2 fractional order fuzzy PID controller: Design, performance evaluation, and its optimal time domain tuning

Abstract: In this paper, a novel concept of an interval type-2 fractional order fuzzy PID (IT2FO-FPID) controller, which requires fractional order integrator and fractional order differentiator, is proposed. The incorporation of Takagi-Sugeno-Kang (TSK) type interval type-2 fuzzy logic controller (IT2FLC) with fractional controller of PID-type is investigated for time response measure due to both unit step response and unit load disturbance. The resulting IT2FO-FPID controller is examined on different delayed linear and nonlinear benchmark plants followed by robustness analysis. In order to design this controller, fractional order integrator-differentiator operators are considered as design variables including input-output scaling factors. A new hybridized algorithm named as artificial bee colony-genetic algorithm (ABC-GA) is used to optimize the parameters of the controller while minimizing weighted sum of integral of time absolute error (ITAE) and integral of square of control output (ISCO). To assess the comparative performance of the IT2FO-FPID, authors compared it against existing controllers, i.e., interval type-2 fuzzy PID (IT2-FPID), type-1 fractional order fuzzy PID (T1FO-FPID), type-1 fuzzy PID (T1-FPID), and conventional PID controllers. Furthermore, to show the effectiveness of the proposed controller, the perturbed processes along with the larger dead time are tested. Moreover, the proposed controllers are also implemented on multi input multi output (MIMO), coupled, and highly complex nonlinear two-link robot manipulator system in presence of un-modeled dynamics. Finally, the simulation results explicitly indicate that the performance of the proposed IT2FO-FPID controller is superior to its conventional counterparts in most of the cases.

Pattern-recognizing self-tuning controller

Abstract: A pattern-recognizing, self-tuning controller is provided for controlling a process wherein measured characteristics including at least one peak of an error signal, derived from the differences occurring over time between the values of a process controlled variable and a desired set-point level for that variable, are used for identifying the behavior pattern of the error signal so that an operating parameter of the controller can be changed as required to minimize process recovery time whenever the process is subsequently disturbed or an abrupt change is made to the set-point level at some later time. The preferred embodiment of the device is in the form of a proportional-integral-derivative (PID) controller in which the PID coefficients are calculated in accordance with prescribed relationships that are based on damping, overshoot and time period characteristics of the error signal. Provisions are also made for including a user-specified noise threshold in order to reduce substantially the possibility of detecting a noise peak as a true peak of the error signal. A pre-adapt mode is also included, in which the controller automatically determines the initial values of the PID coefficients, the noise threshold, and the approximate time scale of the process, before on-line adaptive control of the process is given to the controller.

A Novel Piezoelectric Strain Sensor for Simultaneous Damping and Tracking Control of a High-Speed Nanopositioner

Abstract: This paper presents a novel piezoelectric strain sensor for damping and accurate tracking control of a high-speed nanopositioning stage. Piezoelectric sensors have the benefit of simple interface circuitry, low cost, high sensitivity, and high bandwidth. Although piezoelectric sensors have been successfully used as vibration sensors in smart structures, complications arise when they are used in a feedback loop for tracking. As piezoelectric strain sensors exhibit a capacitive source impedance, a high-pass filter is created, typically with a cut-off frequency of 1 to 10 Hz. This filter can cause significant errors and destabilize a tracking control system. Here, we overcome this problem by using a low-frequency bypass technique to replace the low-frequency component of the strain measurement with an estimate based on the open-loop system. Once the low-frequency filter is accounted for, any standard control system can be applied. In this paper, an analog integral resonant controller together with an integral tracking controller are implemented on a flexure-guided nanopositioner. The resulting closed-loop bandwidth is experimentally demonstrated to be 1.86 kHz. The nanopositioner is installed in an Atomic Force Microscope to obtain open- and closed-loop images at line rates of 40 and 78 Hz. Images recorded in closed loop show a significant improvement due to the elimination of nonlinearity.

Adaptive controller having optimal filtering

Abstract: A self-adaptive controller for use in a control process for providing ordered changes in a manipulated process variable in response to measured changes in a controlled process variable having means for using measured and predicted values of the controlled variable to obtain an estimated value of the controlled variable which estimated value is used via a self-adaptive controller to determine the change in manipulated variable. The controller is described with reference to a paper manufacturing process for controlling the basis weight and moisture content of a continuous web of paper.