Steady-State and Stochastic Performance of a Modified Discrete-Time Prototype Repetitive Controller

1990 ◽  
Vol 112 (1) ◽  
pp. 35-41 ◽  
Author(s):  
Kok Kia Chew ◽  
Masayoshi Tomizuka
Keyword(s):  
Steady State ◽  
Discrete Time ◽  
Internal Model ◽  
Repetitive Control ◽  
Signal Generator ◽  
Disk File ◽  
Stochastic Disturbances ◽  
Actuator System ◽  
Dual Objectives ◽  
Steady State Performance

Perfect regulation may be too stringent a condition in repetitive control. In this paper, the rigid stability requirement is relaxed by including an appropriately chosen filter in the repetitive signal generator. Lacking an internal model, perfect regulation is not assured in the modified system. The steady-state and stochastic performances of the resulting system are analyzed. These analyses reveal that under certain conditions the dual objectives of good steady-state and stochastic performances are conflicting. A high repetitive gain may give good steady-state performance, but the variance propagation of stochastic disturbances is large (extremely large for some choice of a parameter in the modified controller). The converse is true when the repetitive gain is small. The performance of the modified scheme is evaluated by applying it to a simulated disk-file actuator system.

scholarly journals Event-triggered Discrete-time Sliding Mode Control for High-order Systems via Reduced-order Model Approach

2020 ◽  
Vol 53 (2) ◽  
pp. 6207-6212
Author(s):  
Kiran Kumari ◽  
Bijnan Bandyopadhyay ◽  
Johann Reger ◽  
Abhisek K. Behera
Keyword(s):  
Sliding Mode Control ◽  
Discrete Time ◽  
Sliding Mode ◽  
High Order ◽  
Reduced Order Model ◽  
Order Model ◽  
Reduced Order ◽  
Mode Control ◽  
Event Triggered ◽  
Model Approach

Discrete-time Repetitive Control of LTI Systems Sampled at a Periodic Rate

1996 ◽  
Vol 29 (1) ◽  
pp. 1458-1463 ◽  
Author(s):  
Reed D. Hanson ◽  
Tsu-Chin Tsao
Keyword(s):  
Discrete Time ◽  
Repetitive Control

scholarly journals An internal model approach for motor behavior

2021 ◽  
Vol 15 (5) ◽  
pp. 356-371
Author(s):  
Cláudio M. F. Leite ◽  
Carlos E. Campos ◽  
Crislaine R. Couto ◽  
Herbert Ugrinowitsch
Keyword(s):  
Motor Skills ◽  
Internal Model ◽  
Motor Behavior ◽  
External World ◽  
Internal Models ◽  
Sensory Inputs ◽  
Theoretical Approaches ◽  
Internal Coherence ◽  
Motor Actions ◽  
Model Approach

Interacting with the environment requires a remarkable ability to control, learn, and adapt motor skills to ever-changing conditions. The intriguing complexity involved in the process of controlling, learning, and adapting motor skills has led to the development of many theoretical approaches to explain and investigate motor behavior. This paper will present a theoretical approach built upon the top-down mode of motor control that shows substantial internal coherence and has a large and growing body of empirical evidence: The Internal Models. The Internal Models are representations of the external world within the CNS, which learn to predict this external world, simulate behaviors based on sensory inputs, and transform these predictions into motor actions. We present the Internal Models’ background based on two main structures, Inverse and Forward models, explain how they work, and present some applicability.

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