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 embedded built-in self-test (BIST) of electronic circuits and systems

Abstract: An embedded electronic system built-in self-test controller architecture that facilitates testing and debugging of electronic circuits and in-system configuration of programmable devices. The system BIST controller architecture includes an embedded system BIST controller, an embedded memory circuit, an embedded IEEE 1149.1 bus, and an external controller connector. The system BIST controller is coupled to the memory circuit and the IEEE 1149.1 bus, and coupleable to an external test controller via the external controller connector. The external test controller can communicate over the IEEE 1149.1 bus to program the memory and/or the system BIST controller circuitry, thereby enabling scan vectors to be debugged by the external test controller and then downloaded into the memory for subsequent application to a unit under test by the system BIST controller.

An Adaptive sliding surface slope adjustment in PD Sliding Mode Fuzzy Control for Robot Manipulator

Abstract: Robotic manipulators are multi-input multi-output (MIMO), nonlinear and most of dynamic parameters are uncertainty so design a high performance controller for these plants is very important. Today, strong mathematical tools used in new control methodologies to design adaptive nonlinear robust controller with acceptable performance. One of the best nonlinear robust controller which can be used in uncertainty nonlinear systems, are sliding mode controller but pure sliding mode controller has some disadvantages such as nonlinear dynamic uncertainties therefore to design model free sliding mode controller this research focuses on applied fuzzy logic controller in sliding mode controller. One of the most important challenging in pure sliding mode controller and sliding mode fuzzy controller is sliding surface slope coefficient therefore the second target in this research is design a supervisory controller to adjusting the sliding surface slope in sliding mode fuzzy controller.

Nonlinear state feedback controller for nonlinear systems: Stability analysis and design based on fuzzy plant model

Abstract: This paper presents the stability analysis of a fuzzy-model-based control system consisting of a nonlinear plant and a nonlinear state feedback controller and the design of the nonlinear gains of the controller. The nonlinear plant is represented by a fuzzy model having p rules. A nonlinear state feedback controller is designed to close the feedback loop. Under this design, the stability condition is reduced to p linear matrix inequalities. An application example on stabilizing a mass-spring-damper system will be given.

Multi-criteria analysis of wastewater treatment plant design and control scenarios under uncertainty

Abstract: Wastewater treatment plant control and monitoring can help to achieve good effluent quality, in a complex, highly non-linear process. The Benchmark Simulation Model no. 2 (BSM2) is a useful tool to competitively evaluate plant-wide control on a long-term basis. A method to conduct scenario analysis of process designs by means of Monte Carlo (MC) simulations and multi-criteria evaluation is presented. It is applied to the open loop version of BSM2 and to two closed loop versions, one with a simple oxygen controller and the other one with an ammonium controller regulating the set-point of the oxygen controller (cascade controller). The results show a much greater benefit of the cascade controller compared to the simple controller, both in environmental and economic terms. From an optimal process design point of view, the results show that the volume of the primary clarifier and the anoxic fraction of the reactor volume have an important impact on process performance. The uncertainty analysis of the optimal designs, also performed with MC simulations, highlights the improved and more stable effluent under closed loop control.