Fuzzy moving sliding mode control with application to robotic manipulators

Ha, Q.P.; Rye, David; Durrant‐Whyte, Hugh

doi:10.1016/s0005-1098(98)00169-1

Cited by 152 publications

(88 citation statements)

References 9 publications

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“…In [12] a way to tune a fuzzy SMC (FSMC) was derived by rotating and shifting the sliding surface and achieved faster reaching times and improved tracking error to a class of nonlinear systems compared with a conventional SMC.…”

Section: Dynamic Smc Tuningmentioning

confidence: 99%

Exponential Mapping Function for Nonlinear Control

Castro¹,

Paglione²,

Ribeiro³

2015

SIC

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Industrial control engineers, who are often faced with the problem of dealing with projects involving unknown or poorly modelled systems, usually have at their disposal a limited number of options to develop, implement, and maintain controllers, namely PID and, lately, fuzzy-based controllers. The large use of the PID controller comes from the widespread knowledge of its theory and easy tuning methods and its prompt availability in control equipment and supervisory systems. Nevertheless, depending on the manufacturer's discretion, at least five gains have to be set. Fuzzy controllers for a SISO system usually demand between fifteen and twenty parameters. That's also a problem for the maintenance personnel. The proposed SISO controller needs two heuristically defined gains to be set, based on knowledge about the free response of the plant and expected disturbances. Its simplicity allows its implementation on devices with memory and processor constraints.

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Section: Dynamic Smc Tuningmentioning

confidence: 99%

Exponential Mapping Function for Nonlinear Control

Castro¹,

Paglione²,

Ribeiro³

2015

SIC

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“…The fuzzy control, based on fuzzy sets theory, fuzzy language variation, and fuzzy logical reasoning, is a relatively mathematical method that can directly express the human empirical reasoning, judicial thinking process. Its control performance is comparatively well because the establishment of the control system is resulted from control principle by the language variable conditional statements [12][13][14] .…”

Section: A System Structure Of Fuzzy Pid Controlmentioning

confidence: 99%

Fuzzy PID Control Simulation Research on Rotational Speed Regulation for Diesel Engines

Zhang¹,

Xiao²,

Jin³

2015

Proceedings of the 2015 International Conference on Mechatronics, Electronic, Industrial and Control Engineering

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Abstract-The online self-adjustment of parameters of diesel engines mechanical speed controller is achieved by a designed fuzzy PID controller, through establishing a mathematic model of diesel engine mechanical centrifugal speed controller and the application of the advantages of the conventional PID control and fuzzy control. The fuzzy PID diesel engine mechanical speed control system is simulated by Simulink of MATLAB. The digital electronic governor depends on controlling software to realize the function of regulation and control. It can automatically regulate the accelerograph of the diesel engine, gives the engine the right amount fuel oil, and lets the diesel engine work at the fixed rotational speed when the load is being changed. It also has solved the mechanical governor problems such as poor accuracy and large time consumption to achieve stable state, and it is versatile and possesses extensional ability. The simulation results suggest fine dynamic performance, strong robustness, and better adaptability, compared to the conventional PID control algorithm of fuzzy self-adjustment PID algorithm. The performance of diesel engine speed control system is thusly largely advanced.

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“…In this case, experimental results indicate that the performance can be degraded by the presence of noise. Fuzzy moving sliding mode [12] and impedance [13] controllers have similarly been developed for robot excavators. Budny [14] considers control of an excavator bucket in straight lines by applying Danfoss PVG 32 loadindependent hydraulic valves.…”

Section: Excavator Controlmentioning

confidence: 99%

Proportional-Integral-Plus (PIP) Gain Scheduling Control of an Intelligent Excavator

Gu¹,

Taylor²,

Seward³

2004

Proceedings of the 21st International Symposium on Automation and Robotics in Construction

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This paper considers the design and implementation of an electro-hydraulic control system for a robotic excavator, namely the Lancaster University Computerised and Intelligent Excavator (LUCIE). The excavator is being developed to autonomously dig trenches without human intervention. Here, a gain scheduling design, based on Proportional-Integral-Plus (PIP) control methods, is utilised to regulate the highly nonlinear joint dynamics. Simulation and initial field tests both demonstrate the feasibility of the proposed technique, with the excavator arm directed along specified trajectories in a smooth, fast and accurate manner.

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Fuzzy moving sliding mode control with application to robotic manipulators

Cited by 152 publications

References 9 publications

Exponential Mapping Function for Nonlinear Control

Exponential Mapping Function for Nonlinear Control

Fuzzy PID Control Simulation Research on Rotational Speed Regulation for Diesel Engines

Proportional-Integral-Plus (PIP) Gain Scheduling Control of an Intelligent Excavator

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