Learning control in robotic systems

Gu, Yan; Loh, N.K.

doi:10.1007/bf00238694

Cited by 18 publications

(10 citation statements)

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“…During the past ten years, learning control with applications to dynamic systems, such as robot manipulation and flight guidance, has become an increasingly important research topic. A set of learning control schemes and better control processes have also been investigated and proposed [4,5,9,24,25,36,65].In this chapter, some basic concepts including definition, reasons and history of learning control followed by machine learning and its application in control will be first introduced. Then the schemes of learning control, which involve pattern recognition-based learning control, iterative learning control, repetitive learning control, NN-based learning control and rule-based learning control, etc., will be discussed.…”

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Learning Control System

Cai¹

1997

Intelligent Control: Principles, Techniques and Applications

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Learning control is one of the earliest research areas of intelligent control. The concepts of learning and learning control were introduced about a quarter of century ago [17,18,64,68]. During the past ten years, learning control with applications to dynamic systems, such as robot manipulation and flight guidance, has become an increasingly important research topic. A set of learning control schemes and better control processes have also been investigated and proposed [4,5,9,24,25,36,65].In this chapter, some basic concepts including definition, reasons and history of learning control followed by machine learning and its application in control will be first introduced. Then the schemes of learning control, which involve pattern recognition-based learning control, iterative learning control, repetitive learning control, NN-based learning control and rule-based learning control, etc., will be discussed. After that, some issues for learning control, which deal with design principles, control rules, stability analysis and convergence analysis of learning control, will be analyzed. Finally, an example of learning control systems, the self-learning fuzzy neurocontrol for arc welding process, will be presented. Intelligent Control: Principles, Techniques and Applications Downloaded from www.worldscientific.com by UNIVERSITY OF BIRMINGHAM on 06/25/16. For personal use only.Learning Control System 303 material that can be influenced by the natural selection. If the change comes out in a type of behavior and provided this behavior is harmless, then this change would be continued generation after generation. This change of behavioral type from one generation to its next generation is called racial learning or system growth learning, and the behavior change or behavior learning that happens in a specific individual is called individual growth learning. C. Shannon defined learning with more limitation in 1953. Definition 8.2 (Shannon). Suppose: (1) an organism or a machine is in a kind of environment; (2) There exists a "successful" measure or "adaptive" measure to the environment; (3) This measure is a relative local measure with respect to time, i.e., people can test this successful measure in a time shorter than the life time of the organism. If this local successful measure is improved with the time for the environment considered, then it is said that, for the selected successful measure, the organism or machine is in learning for adapting this kind of environment.Osgood presented learning from the point of view of psychology in 1953. Definition 8.3. In repetitive circumstances with same features, the organism individual continuously changes its own behaviors and enhances its selection in competitive reaction depending upon its own adaptability. This kind of selective variation formed by the individual experience is the so-called learning.Tsypkin gave learning and self-learning a more general definition as follows [68]. Definition 8.4. Learning can be understood as a process that repeats various input signals, corrects s...

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Learning Control System

Cai¹

1997

Intelligent Control: Principles, Techniques and Applications

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“…Further, there is a restriction on the number of inputs and outputs. Gu and Loh (1987) presented a multi-step learning control scheme for robotic systems. The updating law of the control input signal is intuitively chosen as the weighted summation of the errors of previous operations.…”

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Two-dimensional model and algorithm analysis for a class of iterative learning control systems

Zhang¹,

Carroll

Xie

1990

International Journal of Control

127

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“…The PID formulation for ILC was addressed in [8] without consideration toward time delay elements. However, it will be shown here even in the linear time invariant case that such a formulation does not yield stable results.…”

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“…In the next section, the results of [ i ' l are summarized. In Section Ill, the PID learning control of [8] is similiarly developed. Section IV contains this papers suggested formulation.…”

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confidence: 99%

Stability and convergence issues in iterative learning control. II

Hideg

Proceedings of the 1996 IEEE International Symposium on Intelligent Control

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Repeated accurate path tracking has many control applications. Manufacturing or cycled endurance testing are examples. Repetitions permit adjustments of control signals between cycles with trajectory error information. Iterative learning control (ILC) systems are designed for this situation. Time delays can adversely affect stability especially in interative schemes. Calculation time by digital systems or by sampling techniques can cause delays. Sensor dynamics or sensor location can also cause delays. This paper proposes a stability condition for ILC where the plant exhibits a time delay.

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Learning control in robotic systems

Cited by 18 publications

References 6 publications

Learning Control System

Learning Control System

Two-dimensional model and algorithm analysis for a class of iterative learning control systems

Stability and convergence issues in iterative learning control. II

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