scholarly journals Variable Structure Control of Engine Idle Speed With Estimation of Unmeasurable Disturbances

2000 ◽  
Vol 122 (4) ◽  
pp. 599-603 ◽  
Author(s):  
A. Stotsky ◽  
B. Egardt ◽  
S. Eriksson
Keyword(s):  
Engine Speed ◽  
Main Tool ◽  
Variable Structure ◽  
Time Varying ◽  
Idle Speed ◽  
Structure Control ◽  
Lyapunov Function Method ◽  
Production Delay ◽  
The Stability ◽  
Disturbance Estimator

A new controller for throttle and spark advance to control the engine speed at idle under unknown time varying disturbances is proposed in this paper. By using measurements of the engine speed the disturbance estimator is designed to reconstruct a disturbance torque. The controller is formulated so that the throttle is used as much as possible as a main tool to produce a torque and spark advance is used to compensate intake to torque production delay. The stability of the system is proved via Lyapunov function method. [S0022-0434(00)01304-6]

Enhanced Grey Variable Structure Control Methodology of Parallel-Connected DC-AC Inverters for Ultra-Precision Machining

2015 ◽  
Vol 661 ◽  
pp. 29-35
Author(s):  
En Chih Chang ◽  
Hung Liang Cheng ◽  
Chien Hsuan Chang ◽  
Jin Wei Liu ◽  
Chih Hsien Chuang ◽  
...  
Keyword(s):  
Output Voltage ◽  
Variable Structure Control ◽  
Variable Structure ◽  
Precision Machining ◽  
Structure Control ◽  
Highly Nonlinear ◽  
Ultra Precision ◽  
The Stability ◽  
Control Methodology ◽  
Voltage Harmonics

This paper develops an enhanced grey variable structure controlled DC-AC inverter in parallel, and is suitable for the application of ultra-precision machining (UPM). The enhanced grey variable structure control methodology consists of a nonlinear sliding function (NSF) and a grey model, GM(2,1). The NSF has finite system-state convergence time, and thus the AC output voltage regulation and balanced current-sharing among the parallel modules can be achieved. However, once the loading of the UPM is a highly nonlinear condition, the chatter still exists in NSF. The chatter may cause heat losses and high voltage harmonics in parallel-connected DC-AC inverter output, and thus deteriorates the stability and reliability of the UPM. To eliminate the chatter, the control gains of the NSF can be adjusted by the use of the GM(2,1) under system uncertainty bounds are overestimated. With the enhanced methodology, the parallel-connected DC-AC inverter yields a high-quality AC output voltage with low voltage harmonics and fast dynamic response under highly nonlinear loading, thus achieving the stability and reliability of the UPM. Experimental results are performed to demonstrate the enhanced methodology.

scholarly journals Chattering-Free Single-Phase Robustness Sliding Mode Controller for Mismatched Uncertain Interconnected Systems with Unknown Time-Varying Delays

Energies ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 282 ◽  
Author(s):  
Cong-Trang Nguyen ◽  
Thanh Long Duong ◽  
Minh Quan Duong ◽  
Duc Tung Le
Keyword(s):  
Single Phase ◽  
Sliding Mode ◽  
Variable Structure Control ◽  
Variable Structure ◽  
Sliding Mode Controller ◽  
Time Varying ◽  
Structure Control ◽  
Time Varying Delay ◽  
Chattering Free ◽  
Varying Delay

Variable structure control with sliding mode can provide good control performance and excellent robustness. Unfortunately, the chattering phenomenon investigated due to discontinuous switching gain restricting their applications. In this paper, a chattering free improved variable structure control (IVSC) for a class of mismatched uncertain interconnected systems with an unknown time-varying delay is proposed. A sliding function is first established to eliminate the reaching phase in traditional variable structure control (TVSC). Next, a new reduced-order sliding mode estimator (ROSME) without time-varying delay is constructed to estimate all unmeasurable state variables of plants. Then, based on the Moore-Penrose inverse approach, a decentralized single-phase robustness sliding mode controller (DSPRSMC) is synthesized, which is independent of time delays. A DSPRSMC solves a complex interconnection problem with an unknown time-varying delay term and drives the system’s trajectories onto a switching surface from the initial time instance. Particularly, by applying the well-known Barbalat’s lemma, the chattering phenomenon in control input is alleviated. Moreover, a sufficient condition is established by using an appropriate Lyapunov theory and linear matrix inequality (LMI) method such that a sliding mode dynamics is asymptotically stable from the beginning time. Finally, a developed method is validated by numerical example with computer simulations.

SYNCHRONIZATION CONTROL OF NEURAL NETWORKS SUBJECT TO TIME-VARYING DELAYS AND INPUT NONLINEARITY

2006 ◽  
Vol 16 (12) ◽  
pp. 3643-3654 ◽  
Author(s):  
JUN-JUH YAN ◽  
TEH-LU LIAO ◽  
JUI-SHENG LIN ◽  
CHAO-JUNG CHENG
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Variable Structure ◽  
Hopfield Neural Network ◽  
Cellular Neural Network ◽  
Control Technique ◽  
Time Varying ◽  
Input Nonlinearity ◽  
Structure Control ◽  
Synchronization Problem

This paper investigates the synchronization problem for a particular class of neural networks subject to time-varying delays and input nonlinearity. Using the variable structure control technique, a memoryless decentralized control law is established which guarantees exponential synchronization even when input nonlinearity is present. The proposed controller is suitable for application in delayed cellular neural networks and Hopfield neural networks with no restriction on the derivative of the time-varying delays. A two-dimensional cellular neural network and a four-dimensional Hopfield neural network, both with time-varying delays, are presented as illustrative examples to demonstrate the effectiveness of the proposed synchronization scheme.

scholarly journals Fuzzy Adaptive Variable Structure Control of Second-Order Robotic Manipulators with Dead Zones

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Songyu Wang ◽  
Xianmin Hou
Keyword(s):  
Fuzzy Systems ◽  
Variable Structure ◽  
Second Order ◽  
Theoretical Derivation ◽  
Controlled System ◽  
Dead Zones ◽  
Structure Control ◽  
Adaptive Laws ◽  
The Stability ◽  
Fuzzy Adaptive

In this study, with respect to certain second-order robotic systems with dead zones, a fuzzy adaptive variable structure controller (VSC) is implemented. Some suitable adaptive fuzzy systems are used to estimate uncertain functions. Based on Lyapunov stability theorems, parameter adaptive laws are designed, and it is proven that all signals involved will remain bounded and the stability of the controlled system is also guaranteed. Our controller is effective for the system with or without sector nonlinearity. Finally, a simulation example is presented to illustrate the correctness of the theoretical derivation.

scholarly journals Neural-Fuzzy-Based Adaptive Sliding Mode Automatic Steering Control of Vision-based Unmanned Electric Vehicles

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Jinghua Guo ◽  
Keqiang Li ◽  
Jingjing Fan ◽  
Yugong Luo ◽  
Jingyao Wang
Keyword(s):  
Electric Vehicles ◽  
Sliding Mode ◽  
Variable Structure ◽  
Control Law ◽  
Time Varying ◽  
Steering Control ◽  
Structure Control ◽  
Adaptive Sliding Mode ◽  
Automatic Steering ◽  
Neural Fuzzy

AbstractThis paper presents a novel neural-fuzzy-based adaptive sliding mode automatic steering control strategy to improve the driving performance of vision-based unmanned electric vehicles with time-varying and uncertain parameters. Primarily, the kinematic and dynamic models which accurately express the steering behaviors of vehicles are constructed, and in which the relationship between the look-ahead time and vehicle velocity is revealed. Then, in order to overcome the external disturbances, parametric uncertainties and time-varying features of vehicles, a neural-fuzzy-based adaptive sliding mode automatic steering controller is proposed to supervise the lateral dynamic behavior of unmanned electric vehicles, which includes an equivalent control law and an adaptive variable structure control law. In this novel automatic steering control system of vehicles, a neural network system is utilized for approximating the switching control gain of variable structure control law, and a fuzzy inference system is presented to adjust the thickness of boundary layer in real-time. The stability of closed-loop neural-fuzzy-based adaptive sliding mode automatic steering control system is proven using the Lyapunov theory. Finally, the results illustrate that the presented control scheme has the excellent properties in term of error convergence and robustness.

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