Time-optimal sliding mode control of robot manipulator

Kalaykov, Ivan; Iliev, Boyko

doi:10.1109/iecon.2000.973161

Cited by 7 publications

(3 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…2. In theory, this TOC takes on the switching curve as its sliding surface when the initial state is driven to that curve with an extreme value of the control signal [11] [18]. Therefore, this TOC method has the following advantages over a linear controller: 1) the state arrives at the steady state in minimal and finite time [19]; and 2) superior disturbance rejection robustness against dynamic uncertainties [20].…”

Section: Introductionmentioning

confidence: 99%

High-precision tracking differentiator via generalized discrete-time optimal control

et al. 2019

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

High-precision tracking differentiator via generalized discrete-time optimal control

et al. 2019

View full text Add to dashboard Cite

“…Many control methods have been proposed to control the flexible manipulators employing PD control [3], adaptive control [4,5], computed torque method [6], robust control [7], sliding mode control [26] etc.…”

Section: Introductionmentioning

confidence: 99%

Particle swarm optimized hybrid fuzzy precompensated trajectory control of rigid-flexible manipulator

Alavandar

Jain

Nigam

2009

KES

View full text Add to dashboard Cite

Light-weight flexible arms will most likely constitute the next generation robots due to their large payload carrying capacities at high speeds and less power demand. Control problem of robots with flexible members is more complex compared to rigid robots due to vibrations during the motion. This paper presents the optimization technique inspired by social behavior of bird flocking to optimize hybrid Fuzzy Precompensated Proportional -Derivative (PD) controller in trajectory control of two link rigid-flexible manipulator. Numerical simulation using the dynamic model of two link rigid-flexible manipulator shows the effectiveness of the approach in trajectory tracking problems and the use of fuzzy precompensation has superior performance in terms of improvement in transient and steady state response, robustness to variations in loading conditions and ease to use in practice. Comparative evaluation with respect to genetic algorithm based optimization is presented to validate the controller design. The results presented emphasize that a satisfactory tracking precision could be achieved using hybrid Fuzzy Precompensated Proportional -Derivative controller with particle swarm optimization.

show abstract

“…Therefore, improving the control performance under disturbances becomes a major issue .The control aim of motion control for flexible manipulator is to ensure the end position track the given trajectory accurately under the action of control torque of each joint. Many control methods have been proposed to control the flexible manipulators employing PD control, 3 adaptive control, 4,5 computed torque method, 6 robust control, 7 sliding mode control 21 etc.…”

Section: Introductionmentioning

confidence: 99%

Bacterial Foraging Optimized Hybrid Fuzzy Precompensated PD Control of Two Link Rigid-Flexible Manipulator

Alavandar¹,

Jain²,

Nigam³

2009

IJCIS

View full text Add to dashboard Cite

Light-weight flexible arms will most likely constitute the next generation robots due to their large payload carrying capacities at high speeds and less power demand. Control problem of robots with flexible members is more complex compared to rigid robots due to vibrations during the motion. This paper presents the social foraging behavior of Escherichia coli bacteria to optimize hybrid Fuzzy Precompensated Proportional -Derivative (PD) controller in trajectory control of two link rigid-flexible manipulator. Numerical simulation using the dynamic model of the two link rigid-flexible manipulator shows the effectiveness of the approach in trajectory tracking problems and the use of fuzzy precompensation has superior performance in terms of improvement in transient and steady state response, robustness to variations in loading conditions and ease to use in practice. Comparative evaluation with respect to genetic algorithm based optimization is presented to validate the controller design. The results presented emphasize that a satisfactory tracking precision could be achieved using hybrid Fuzzy Precompensated PD controller with bacterial foraging based optimization.

show abstract

Time-optimal sliding mode control of robot manipulator

Cited by 7 publications

References 2 publications

High-precision tracking differentiator via generalized discrete-time optimal control

High-precision tracking differentiator via generalized discrete-time optimal control

Particle swarm optimized hybrid fuzzy precompensated trajectory control of rigid-flexible manipulator

Bacterial Foraging Optimized Hybrid Fuzzy Precompensated PD Control of Two Link Rigid-Flexible Manipulator

Contact Info

Product

Resources

About