On The Stability of Control Systems Having Clegg Integrators

1999 ◽  
pp. 107-115 ◽  
Author(s):  
Hanzhong Hu ◽  
Yuan Zheng ◽  
Christopher V. Hollot ◽  
Yossi Chait
Keyword(s):  
Control Systems ◽  
The Stability

TO THE STABILITY OF TANK VEHICLES IN THE BRAKE MODE

2019 ◽  
pp. 27-32
Author(s):  
Denys Popelysh ◽  
Yurii Seluk ◽  
Sergyi Tomchuk
Keyword(s):  
Mathematical Model ◽  
Control Systems ◽  
Distribution Systems ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Center Of Mass ◽  
Dynamic Processes ◽  
Course Stability ◽  
The Stability ◽  
Tank Vehicles

This article discusses the question of the possibility of improving the roll stability of partially filled tank vehicles while braking. We consider the dangers associated with partially filled tank vehicles. We give examples of the severe consequences of road traffic accidents that have occurred with tank vehicles carrying dangerous goods. We conducted an analysis of the dynamic processes of fluid flow in the tank and their influence on the basic parameters of the stability of vehicle. When transporting a partially filled tank due to the comparability of the mass of the empty tank with the mass of the fluid being transported, the dynamic qualities of the vehicle change so that they differ significantly from the dynamic characteristics of other vehicles. Due to large displacements of the center of mass of cargo in the tank there are additional loads that act vehicle and significantly reduce the course stability and the drivability. We consider the dynamics of liquid sloshing in moving containers, and give examples of building a mechanical model of an oscillating fluid in a tank and a mathematical model of a vehicle with a tank. We also considered the method of improving the vehicle’s stability, which is based on the prediction of the moment of action and the nature of the dynamic processes of liquid cargo and the implementation of preventive actions by executive mechanisms. Modern automated control systems (anti-lock brake system, anti-slip control systems, stabilization systems, braking forces distribution systems, floor level systems, etc.) use a certain list of elements for collecting necessary parameters and actuators for their work. This gives the ability to influence the course stability properties without interfering with the design of the vehicle only by making changes to the software of these systems. Keywords: tank vehicle, roll stability, mathematical model, vehicle control systems.

scholarly journals The Application of an Impedance-Passivity Controller in Haptic Stability Analysis

2021 ◽  
Vol 11 (4) ◽  
pp. 1618
Author(s):  
Ping-Nan Chen ◽  
Yung-Te Chen ◽  
Hsin Hsiu ◽  
Ruei-Jia Chen
Keyword(s):  
Control Systems ◽  
Force Feedback ◽  
Training System ◽  
Considerable Time ◽  
Virtual Training ◽  
Control Gain ◽  
Negative Damping ◽  
The Stability ◽  
Time Required ◽  
Stable Control

This paper proposes a passivity theorem on the basis of energy concepts to study the stability of force feedback in a virtual haptic system. An impedance-passivity controller (IPC) was designed from the two-port network perspective to improve the chief drawback of haptic systems, namely the considerable time required to reach stability if the equipment consumes energy slowly. The proposed IPC can be used to achieve stability through model parameter selection and to obtain control gain. In particular, haptic performance can be improved for extreme cases of high stiffness and negative damping. Furthermore, a virtual training system for one-degree-of-freedom sticking was developed to validate the experimental platform of our IPC. To ensure consistency in the experiment, we designed a specialized mechanical robot to replace human operation. Finally, compared with basic passivity control systems, our IPC could achieve stable control rapidly.

scholarly journals Iterative stability analysis for general polynomial control systems

2021 ◽  
Author(s):  
Bo Xiao ◽  
Hak-Keung Lam ◽  
Zhixiong Zhong
Keyword(s):  
Stability Analysis ◽  
Lyapunov Function ◽  
Control Systems ◽  
Polynomial System ◽  
Stability Conditions ◽  
General Polynomial ◽  
Main Challenge ◽  
Detailed Simulation ◽  
Feasible Solutions ◽  
The Stability

AbstractThe main challenge of the stability analysis for general polynomial control systems is that non-convex terms exist in the stability conditions, which hinders solving the stability conditions numerically. Most approaches in the literature impose constraints on the Lyapunov function candidates or the non-convex related terms to circumvent this problem. Motivated by this difficulty, in this paper, we confront the non-convex problem directly and present an iterative stability analysis to address the long-standing problem in general polynomial control systems. Different from the existing methods, no constraints are imposed on the polynomial Lyapunov function candidates. Therefore, the limitations on the Lyapunov function candidate and non-convex terms are eliminated from the proposed analysis, which makes the proposed method more general than the state-of-the-art. In the proposed approach, the stability for the general polynomial model is analyzed and the original non-convex stability conditions are developed. To solve the non-convex stability conditions through the sum-of-squares programming, the iterative stability analysis is presented. The feasible solutions are verified by the original non-convex stability conditions to guarantee the asymptotic stability of the general polynomial system. The detailed simulation example is provided to verify the effectiveness of the proposed approach. The simulation results show that the proposed approach is more capable to find feasible solutions for the general polynomial control systems when compared with the existing ones.

On the stability of a class of nonlinear control systems

2015 ◽  
Vol 80 (3) ◽  
pp. 1245-1256 ◽  
Author(s):  
M. H. Noori Skandari
Keyword(s):  
Nonlinear Control ◽  
Control Systems ◽  
Nonlinear Control Systems ◽  
The Stability

scholarly journals Control/Network Codesign Basics for IP-Based Shared Networks

2011 ◽  
Vol 2011 ◽  
pp. 1-23 ◽  
Author(s):  
Miguel Díaz-Cacho Medina ◽  
Emma Delgado Romero ◽  
Antonio Barreiro Blas
Keyword(s):  
Control Systems ◽  
Networked Control Systems ◽  
Transmission Rate ◽  
Design Parameters ◽  
Control Network ◽  
Transport Protocol ◽  
Test Platform ◽  
Shared Networks ◽  
The Stability ◽  
And Control

Network and control relationship is an essential aspect in the design of networked control systems (NCSs). The design parameters are mainly centered in the transmission rate and in the packet structure, and some studies have been made to determine how transmission rate affects the network delay and consequently the stability of the control. In Internet, these analysis are mathematically complex due to the large number of different potential scenarios. Using empirical methods, this work deduces that the transmission scheduling problem of an NCS can be solved by designing an appropriate transport protocol, taken into account high and periodic sampling rates. The transport protocol features are determined by simulation, using a new test platform based on the NS2 network simulation suite, to develop control/network codesign solutions. Conclusions of this paper are that the transport features are packet-loss-based flow control, best effort, and fairness, supplemented by a packet priority scheme.

scholarly journals A Mechanical Feedback Classification of Linear Mechanical Control Systems

2021 ◽  
Vol 11 (22) ◽  
pp. 10669
Author(s):  
Marcin Nowicki ◽  
Witold Respondek
Keyword(s):  
Control System ◽  
Control Systems ◽  
Lagrangian Systems ◽  
Stabilization Problem ◽  
Mechanical Control ◽  
Stability And Stabilization ◽  
The Stability ◽  
Mechanical Change ◽  
Feedback Classification

We give a classification of linear nondissipative mechanical control system under mechanical change of coordinates and feedback. First, we consider a controllable case that is somehow a mechanical counterpart of Brunovský classification, then we extend the result to all linear nondissipative mechanical systems (not necessarily controllable) which leads to a mechanical canonical decomposition. The classification of Lagrangian systems is given afterwards. Next, we show an application of the classification results to the stability and stabilization problem and illustrate them with several examples. All presented results in this paper are expressed in terms of objects on the configuration space Rn only, while the state-space of a mechanical control system is Rn×Rn consisting of configurations and velocities.

scholarly journals Hydraulic Tests and Interpretation of Test Data for Reno Mattresses in Open Channel Flow

2021 ◽  
Vol 930 (1) ◽  
pp. 012025
Author(s):  
P D Pietro ◽  
M Lelli ◽  
A Rahman ◽  
Serkandi
Keyword(s):  
Soil Erosion ◽  
Control Systems ◽  
Soil Layer ◽  
Erosion Control ◽  
Wire Mesh ◽  
Unit Weight ◽  
Research Results ◽  
Colorado State University ◽  
Soil Erosion Control ◽  
The Stability

Abstract The efficacy of erosion control systems depends on preventing soil loss underneath and maintaining its integrity under the effects of the water flow. The paper presents the research results at the Colorado State University on the performance of double twisted wire mesh products, known as Reno Mattresses, used as soil erosion control systems. Mattresses were subjected to various flow conditions on a 10 m long flume placed on a soil layer. The performance against erosion was evaluated by assessing the effect of the stone motion inside the mattress combined with the condition of incipient soil erosion underneath, in relationship to the mattress thickness, the filling stone properties, and under variable hydraulic flow regimes. At the same time, confirming the stability obtained using the conventional tractive force design approach, the research results allowed to introduce a new performance limit based on incipient soil erosion underneath the revetment. Based on the research results, the authors propose to express the shear resistance of mattresses used as soil erosion control systems as a function of the filling stones’ size, uniformity, unit weight, mattress thickness, and the presence of vertical strengthening elements.

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