scholarly journals Expert Skill-Based Gain Tuning in Discrete-Time Adaptive Control for Robots

2004 ◽  
Vol 16 (1) ◽  
pp. 54-60 ◽  
Author(s):  
Haruhisa Kawasaki ◽  
◽  
Geng Li
Keyword(s):  
Adaptive Control ◽  
Discrete Time ◽  
Sampling Period ◽  
High Gain ◽  
Second Step ◽  
Trial And Error ◽  
Time System ◽  
Robot Controller ◽  
Tuning Method ◽  
Continuous Time System

This paper presents a gain tuning method based on the sampling period in discrete-time adaptive control for robots. Gain matrices of model-based adaptive control in a continuous-time system are allowed a high gain positive definite. The maximum of the gains depends on the sampling period, however, and gain tuning is very time-consuming. It is thus desirable to give a gain tuning rule in discrete-time adaptive control. The proposed gain tuning consists of two steps. The first is gain tuning at the basic sampling period by a skilful specialist by trial and error. The second step, executed if the sampling period changes, is a new gain calculation based on a new sampling period. The simulation and experiments with 1-dof and 3-dof robots demonstrate that the robot controller is stable at the large variance of sampling period changes and more accurate than a fixed gain controller.

On Zeros of Discrete-Time Models for Collocated Mass-Damper-Spring Systems

2004 ◽  
Vol 126 (1) ◽  
pp. 205-210 ◽  
Author(s):  
Mitsuaki Ishitobi ◽  
Shan Liang
Keyword(s):  
Discrete Time ◽  
Continuous Time ◽  
Sampling Period ◽  
Sufficient Condition ◽  
Time System ◽  
Time Model ◽  
Discrete Time Model ◽  
Mass Damper ◽  
Approximate Expressions ◽  
Continuous Time System

When a continuous-time system is discretized using the zero-order hold, there is no simple relation which shows how the zeros of the continuous-time system are transformed by sampling. In this paper, for a discrete-time model of a collocated mass-damper-spring system, the asymptotic behavior of the zeros is analyzed with respect to the sampling period and the linear approximate expressions are given. In addition, the linear approximate expressions lead to a sufficient condition for all the zeros of the discrete-time model to lie inside the unit circle for sufficiently small sampling periods. The sufficient condition is satisfied when a damping matrix is positive definite. Moreover, an example is shown to illustrate the validity of the linear approximations. Finally, a comment for a noncollocated system is presented.

Stability of real-time hybrid simulation involving time-varying delay and direct integration algorithms

2021 ◽  
pp. 107754632110016
Author(s):  
Liang Huang ◽  
Cheng Chen ◽  
Shenjiang Huang ◽  
Jingfeng Wang
Keyword(s):  
Real Time ◽  
Discrete Time ◽  
Continuous Time ◽  
Hybrid Simulation ◽  
Time Varying ◽  
Discrete Time System ◽  
Time System ◽  
Integration Algorithms ◽  
The Stability ◽  
Continuous Time System

Stability presents a critical issue for real-time hybrid simulation. Actuator delay might destabilize the real-time test without proper compensation. Previous research often assumed real-time hybrid simulation as a continuous-time system; however, it is more appropriately treated as a discrete-time system because of application of digital devices and integration algorithms. By using the Lyapunov–Krasovskii theory, this study explores the convoluted effect of integration algorithms and actuator delay on the stability of real-time hybrid simulation. Both theoretical and numerical analysis results demonstrate that (1) the direct integration algorithm is preferably used for real-time hybrid simulation because of its computational efficiency; (2) the stability analysis of real-time hybrid simulation highly depends on actuator delay models, and the actuator model that accounts for time-varying characteristic will lead to more conservative stability; and (3) the integration step is constrained by the algorithm and structural frequencies. Moreover, when the step is small, the stability of the discrete-time system will approach that of the corresponding continuous-time system. The study establishes a bridge between continuous- and discrete-time systems for stability analysis of real-time hybrid simulation.

scholarly journals Extreme stability and almost periodicity in continuous and discrete neuronal models with finite delays

2002 ◽  
Vol 44 (2) ◽  
pp. 261-282 ◽  
Author(s):  
S. Mohamad ◽  
K. Gopalsamy
Keyword(s):  
Discrete Time ◽  
Continuous Time ◽  
Model Neuron ◽  
Sufficient Conditions ◽  
External Stimulus ◽  
Input Stimulus ◽  
Time System ◽  
Time Model ◽  
Discrete Time Model ◽  
Continuous Time System

We consider the dynamical characteristics of a continuous-time isolated Hopfield-type neuron subjected to an almost periodic external stimulus. The model neuron is assumed to be dissipative having finite time delays in the process of encoding the external input stimulus and recalling the encoded pattern associated with the external stimulus. By using non-autonomous Halanay-type inequalities we obtain sufficient conditions for the hetero-associative stable encoding of temporally non-uniform stimuli. A brief study of a discrete-time model derived from the continuous-time system is given. It is shown that the discrete-time model preserves the stability conditions of the continuous-time system.

Discrete-time approximationsfor continuous-time Markoviancontrol systems

1984 ◽  
Vol 16 (1) ◽  
pp. 15-16
Author(s):  
A. Hordijk ◽  
F. A. Van Der Duyn Schouten
Keyword(s):  
Decision Theory ◽  
Discrete Time ◽  
Continuous Time ◽  
Time System ◽  
Time Approximation ◽  
Discrete Time Systems ◽  
Discrete Time Approximation ◽  
And Control ◽  
Time Systems ◽  
Continuous Time System

The method of discrete-time approximation is widespread in control and decision theory. However, little attention has been paid to the conditions on parameters and control under which the discrete-time systems come close to the continuous-time system.

Optimal Mini Segway Control Using Non-Minimum Phase Sample and Hold Input

2019 ◽  
Author(s):  
Yingxu Wang ◽  
Guoming G. Zhu
Keyword(s):  
Discrete Time ◽  
Continuous Time ◽  
System Performance ◽  
Low Cost ◽  
Sampling Period ◽  
High Gain ◽  
Minimum Phase ◽  
Discrete Time System ◽  
Loop Control ◽  
Sample And Hold

Abstract Our early work shows the reduction of feasible sampling period when sample and hold inputs (SHI) are used to convert a continuous-time non-minimum phase (NMP) system to a discrete-time minimum phase (MP) system, comparing to conventional zero-order hold. Consequently, high-gain discrete-time controllers can be designed and used to improve continuous-time NMP system performance since the resulting discrete-time system is MP. This paper demonstrates the performance improvements of a mini Segway robot through experiments utilizing a dual-loop control architecture. An inner-loop continuous-time controller stabilizes the mini Segway robot and the outer-loop discrete-time controller, designed based on the discrete-time MP system, is used to improve the overall system performance. Experimental results show that the mini Segway cart oscillation magnitudes are significantly reduced and its stability is also improved. This study also confirms the feasibility of implementing the SHI into a low cost microcontroller such as Arduino. That is, the additional computational load of SHIs is minimal.

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