A self-tuning PID control for a class of nonlinear systems based on the Lyapunov approach

Chang, Wei‐Der; Hwang, Rey-Chue; Hsieh, Jer‐Guang

doi:10.1016/s0959-1524(01)00041-5

Cited by 153 publications

(63 citation statements)

References 10 publications

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“…In general, the main difficulty is to swing up the pendulum from the downward vertical position and to keep the cart stable. Numerous control techniques have been employed to stabilize the inverted pendulum such as proportional-integral-derivative (PID) controllers where the control gains are adjustable and updated online with a stable adaptation mechanism [13] .…”

Section: Introductionmentioning

confidence: 99%

Second-order sliding mode approaches for the control of a class of underactuated systems

Mahjoub

Mnif

Derbel

2015

Int. J. Autom. Comput.

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Abstract:In this paper, first-order and second-order sliding mode controllers for underactuated manipulators are proposed. Sliding mode control (SMC) is considered as an effective tool in different studies for control systems. However, the associated chattering phenomenon degrades the system performance. To overcome this phenomenon and track a desired trajectory, a twisting, a supertwisting and a modified super-twisting algorithms are presented respectively. The stability analysis is performed using a Lyapunov function for the proposed controllers. Further, the four different controllers are compared with each other. As an illustration, an example of an inverted pendulum is considered. Simulation results are given to demonstrate the effectiveness of the proposed approaches.

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Section: Introductionmentioning

confidence: 99%

Second-order sliding mode approaches for the control of a class of underactuated systems

Mahjoub

Mnif

Derbel

2015

Int. J. Autom. Comput.

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“…Formulation of the proposed controller Consider the FOPID controller given in (4). In the following first we develop a method for discretizing the derivative term of this controller based on the prewarped Tustin method and then we extend the results to the integrative term.…”

Section: Discrete-time Fractional-order Pid Controllermentioning

confidence: 99%

“…Currently, various continuous and discrete-time versions of this type of controller are available, which can be applied to the processes modeled by linear differential or linear difference equations, respectively [1][2][3]. Successful applications of PID controllers to control nonlinear processes can also be found in the literature [4].…”

Section: Introductionmentioning

confidence: 99%

Discrete-time fractional-order PID controller: Definition, tuning, digital realization and some applications

Merrikh-Bayat

Mirebrahimi

Khalili

2014

Int. J. Control Autom. Syst.

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In some of the complicated control problems we have to use the controllers that apply nonlocal operators to the error signal to generate the control. Currently, the most famous controller with nonlocal operators is the fractional-order PID (FOPID). Commonly, after tuning the parameters of FO-PID controller, its transfer function is discretized (for realization purposes) using the so-called generating function. This discretization is the origin of some errors and unexpected results in feedback systems. It may even happen that the controller obtained by discretizing a FOPID controller works worse than a directly-tuned discrete-time classical PID controller. Moreover, FOPID controllers cannot directly be applied to the processes modeled by, e.g., the ARMA or ARMAX model. The aim of this paper is to propose a discrete-time version of the FOPID controller and discuss on its properties and applications. Similar to the FOPID controller, the proposed structure applies nonlocal operators (with adjustable memory length) to the error signal. Two methods for tuning the parameters of the proposed controller are developed and it is shown that the proposed controller has the capacity of solving complicated control problems.

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“…Fuzzy control theory has become an important branch in control area and has been used in practice [15][16][17]. The implementation of a fuzzy logic controller undoubtedly requires some efforts in obtaining the fuzzy rules [18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Smart hanger dynamic modeling and fuzzy controller design

Fung

Wong

Ma³

et al. 2011

Int. J. Control Autom. Syst.

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The controlled smart hanger is an indispensable component in the automatic system for garment inspection. Fuzzy logic is chosen for the smart hanger manipulator since it can describe the human behavior remarkably well. In this paper, the dynamic model of the manipulator governing the contact force with garment fabric is first developed. An adaptive fuzzy logic PID control scheme is successfully formulated for the contact force control. Simulation results indicate that the fuzzy PID controller can yield a faster response without overshoot and a smaller error performance as compared to the traditional method based on PID. The stability of the fuzzy PID controller is also demonstrated by computer simulations.

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A self-tuning PID control for a class of nonlinear systems based on the Lyapunov approach

Cited by 153 publications

References 10 publications

Second-order sliding mode approaches for the control of a class of underactuated systems

Second-order sliding mode approaches for the control of a class of underactuated systems

Discrete-time fractional-order PID controller: Definition, tuning, digital realization and some applications

Smart hanger dynamic modeling and fuzzy controller design

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