Zero overshoot and fast transient response using a fuzzy logic controller

In some industrial process control systems it is desirable not to allow an overshoot beyond the setpoint or a threshold, this could be a safety constraint or the requirement of the system. This paper outlines our work in designing a fuzzy PID controller to achieve a step-response with zero overshoot while improving the output transient response. Our designed fuzzy PID controller is applied to stable, marginally stable and unstable systems and their step responses are compared with a tuned conventional PID controller. A comparative case study shows that the proposed fuzzy controller is highly effective and outperforms the PID controller in achieving a zero overshoot response and enhancing the output transient response

Institutional reforms in irrigation sector of Punjab, Pakistan: Proceedings of Workshop held at Faisalabad Serena on 10-11 February 2000

Institution building / Irrigated farming / Irrigation management / Participatory management / Farmer participation / Farmers' associations / Pakistan / Punjab / Hakra

Institutional reforms in irrigation sector of Punjab, Pakistan: Proceedings of Workshop held at Faisalabad Serena on 10-11 February 2000

Institution building / Irrigated farming / Irrigation management / Participatory management / Farmer participation / Farmers' associations / Pakistan / Punjab / Hakra

Unremitting chronic skin lesions: A case of delayed diagnosis of glucagonoma

A grant from the One-University Open Access Fund at the University of Kansas was used to defray the author's publication fees in this Open Access journal. The Open Access Fund, administered by librarians from the KU, KU Law, and KUMC libraries, is made possible by contributions from the offices of KU Provost, KU Vice Chancellor for Research & Graduate Studies, and KUMC Vice Chancellor for Research. For more information about the Open Access Fund, please see http://library.kumc.edu/authors-fund.xml.A 54-year-old Caucasian male with history of hypertension, hyperlipidemia, insulin-dependent diabetes mellitus, and chronic skin rash of 4 years presented to the emergency department with worsening rash and weight loss. Physical examination revealed diffuse erythematous rash, skin ulceration, bullae with associated paresthesia in the lower extremities, trunk, bilateral upper extremities, and palms and soles. A computed tomography (CT) scan with contrast showed a large, heterogenously enhancing pancreatic mass measuring 9.4 × 3.8 cm with surrounding low-attenuation soft tissue thickening. Blood tests showed hemoglobin A1C of 10.0%. Glucagon level was elevated to 2,178 (normal < 80 pg/dl). Endoscopic ultrasound (EUS)-guided fine needle aspiration (FNA) from the pancreatic mass was suggestive of pancreatic endocrine tumor. The tumor cells were positive for synaptophysin, chromogranin, CD56, and pan-cytokeratin with focal positivity for glucagon, suggestive of glucagonoma. The patient underwent distal pancreatectomy along with splenectomy and cholecystectomy. The glucagon level normalized to 25 pg/dl within a week of tumor resection, and during his 6-week outpatient follow up, skin rash had completely resolved

Design of a wireless intelligent fuzzy controller network

Since the first application of fuzzy logic in the field of control engineering, fuzzy logic control has been successfully employed in controlling a wide variety of applications, such as commercial appliances, industrial automation, robots, traffic control, cement kilns and automotive engineering. The human knowledge on controlling complex and non-linear processes can be incorporated into a controller in the form of linguistic expressions. Despite these achievements, however, there is still a lack of an empirical or analytical design study which adequately addresses a systematic auto-tuning method. Indeed, tuning is one of the most crucial parts in the overall design of fuzzy logic controllers and it has become an active research field. Various techniques have been utilised to develop algorithms to fine-tune the controller parameters from a trial and error method to very advanced optimisation techniques. The structure of fuzzy logic controllers is not straightforward as is the case in PID controllers. In addition, there is also a set of parameters that can be adjusted, and it is not always easy to find the relationship between the parameters and the controller performance measures. Moreover, in general, controllers have a wide range of setpoints; changing from one value to another requiring the controller parameters to be re-tuned in order to maintain a satisfactory performance over the entire range of setpoints. This thesis deals with the design and implementation of a new intelligent algorithm for fuzzy logic controllers in a wireless network structure. The algorithm enables the controllers to learn about their plants and systematically tune their gains. The algorithm also provides the capability of retaining the knowledge acquired during the tuning process. Furthermore, this knowledge is shared on the network through a wireless communication link with other controllers. Based on the relationships between controller gains and the closed-loop characteristics, an auto-tuning algorithm is developed. Simulation experiments using standard second order systems demonstrate the effectiveness of the algorithm with respect to auto-tuning, tracking setpoints and rejecting external disturbances. Furthermore, a zero overshoot response is produced with improvements in the transient and the steady state responses. The wireless network structure is implemented using LabVIEW by composing a network of several fuzzy controllers. The results demonstrate that the controllers are able to retain and share the knowledge