Engagement Control of Automated Clutch for Vehicle Launching Considering the Instantaneous Changes of Driver's Intention

2016 ◽  
Vol 139 (2) ◽  
Author(s):  
Liang Li ◽  
Zaobei Zhu ◽  
Yong Chen ◽  
Kai He ◽  
Xujian Li ◽  
...  
Keyword(s):  
Control Strategy ◽  
Control Method ◽  
Sliding Mode ◽  
Linear Quadratic Regulator ◽  
Vehicle Speed ◽  
Linear Quadratic ◽  
Clutch Engagement ◽  
Automated Manual Transmission ◽  
Driver’S Intention ◽  
Artificial Neural Network Ann

Engagement control of automated clutch is essential during launching process for a vehicle equipped with an automated manual transmission (AMT), and instantaneous changes in the driver's launching intention make it more complicated to control the clutch. This paper studies the identification of the driver's launching intentions, which may change anytime, and proposes a clutch engagement control method for vehicle launching. First, a launching-intention-aware machine (LIAM) based on artificial neural network (ANN) is designed for real-time tracking and identifying the driver's launching intentions. Second, the optimal engagement strategy for different launching intentions is deduced based on the linear quadratic regulator (LQR), which figures out a compromise between friction loss, vehicle shock, engine speed, clutch speed, and desired vehicle speed. Third, the relationship between transmitted torque and clutch position is obtained by experiments, and a sliding-mode controller (SMC) is designed for clutch engagement. Finally, the clutch engagement control strategy is validated by a joint simulation model and an experiment bench. The results show that the control strategy reflects the driver's launching intentions correctly and improves the performance of vehicle launching.

Coordination Control Strategy for Active and Reactive Power of DFIG Based on Exact Feedback Linearization under Grid Fault Condition

2011 ◽  
Vol 48-49 ◽  
pp. 335-344
Author(s):  
Meng Zeng Cheng ◽  
Zhen Lan Dou ◽  
Xu Cai
Keyword(s):  
Nonlinear Control ◽  
Power System ◽  
Control Strategy ◽  
Feedback Linearization ◽  
Transient Stability ◽  
Reactive Power ◽  
Control Method ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Nonlinear Control Method

In this paper, a control strategy for operation of rotor side converter (RSC) of Doubly Fed Induction Generators (DFIG) is developed by injecting reactive power into the grid in order to support the grid voltage during and after grid fault events. The novel nonlinear control method is based on differential geometry theory, and exact feedback linearization is applied for control system design of DFIG. Then the optimal control for the linearized system is obtained through introducing the linear quadratic regulator (LQR) design method. Simulation results on a single machine infinite bus power system show that the proposed nonlinear control method can inject reactive power to fault grid rapidly, reduce the oscillation of active power and improve the transient stability of power system.

Optimality of Synergetic Controllers

2006 ◽  
Author(s):  
Antonius Nusawardhana ◽  
Stanislaw H. Zak
Keyword(s):  
Sliding Mode Control ◽  
Control Strategy ◽  
Sliding Mode ◽  
Linear Quadratic Regulator ◽  
Variable Structure ◽  
Linear Quadratic ◽  
Linear Quadratic Optimal Control ◽  
Control Approach ◽  
Mode Control ◽  
Synergetic Control

Optimality properties of synergetic controllers are analyzed using the Euler-Lagrange conditions and the Hamilton-Jacobi-Bellman equation. First, a synergetic control strategy is compared with the variable structure sliding mode control. The synergetic control design methodology turns out to be closely related to the methods of variable structure sliding mode control. In fact, the method of sliding surface design from the sliding mode control are essential for designing similar manifolds in the synergetic control approach. It is shown that the synergetic control strategy can be derived using tools from the calculus of variations. The synergetic control laws have simple structure because they are derived from the associated first-order differential equation. It is also shown that the synergetic controller for a certain class of linear quadratic optimal control problems has the same structure as the one generated using the linear quadratic regulator (LQR) approach by solving the associated Riccati equation.

scholarly journals A Model Predictive Water-Level Difference Control Method for Automatic Control of Irrigation Canals

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 762 ◽  
Author(s):  
Kong ◽  
Lei ◽  
Wang ◽  
Long ◽  
Lu ◽  
...  
Keyword(s):  
Automatic Control ◽  
Water Level ◽  
Control Strategy ◽  
Control Method ◽  
Linear Quadratic Regulator ◽  
Automatic Regulation ◽  
Irrigation Canal ◽  
Linear Quadratic ◽  
Lqr Control ◽  
Level Difference

In this paper, automatic control of the water level in an irrigation canal by automatic regulation of intermediate gates was studied. Previous scholars have proposed a water level difference control strategy that works to keep relative deviations in all pools the same for a particular situation where the operator does not have full control over the canal inflow, with the centralized linear quadratic regulator (LQR) control method used. While in practice, the deviation tolerance of pools may differ in some canals which limits the applicability of the control strategy. In this work, a weight coefficient was added to the deviation and the algorithm was improved to keep the relative deviations to certain proportions. The model predictive control (MPC) method was then used with this improved control strategy and was compared to the LQR control method using the same control strategy. The results showed that the improved strategy can keep the water level deviations in all pools to certain proportions, as is our objective. Also, under this difference control strategy, the MPC method greatly improved the control performance compared to the LQR control method.

An automatic gear-shifting strategy for manual transmissions

2007 ◽  
Vol 221 (5) ◽  
pp. 757-768 ◽  
Author(s):  
B Mashadi ◽  
A Kazemkhani ◽  
R Baghaei Lakeh
Keyword(s):  
Fuzzy Inference ◽  
Control Method ◽  
Fuzzy Controller ◽  
Step Function ◽  
Maximum Speed ◽  
Vehicle Speed ◽  
Deceleration Phase ◽  
Shifting Strategy ◽  
Automated Manual Transmission ◽  
Driver’S Intention

Based on two different criteria, namely the engine working conditions and the driver's intention, the governing parameters in decision making for gear shifting of an automated manual transmission are discussed. The gear-shifting strategy was designed by taking into consideration the effects of these parameters, with the application of a fuzzy control method. The controller structure is formed in two layers. In the first layer, two fuzzy inference modules are used to determine the necessary outputs. In the second layer a fuzzy inference module makes the decision of shifting by upshift, downshift, or maintain commands. The behaviour of the fuzzy controller is examined by making use of ADVISOR software. It is shown that at different driving conditions the controllers make correct decisions for gear shifting accounting for the dynamic requirements of the vehicle. It is also shown that the controller based on both the engine state and the driver's intention eliminates unnecessary shiftings that are present when the intention is overlooked. A microtrip is designed in which a required speed in the form of a step function is demanded for the vehicle on level or sloping roads. Both strategies for the vehicle to reach the maximum speed starting from rest allow the gear shift to be made consecutively. Considerable differences are observed between the two strategies in the deceleration phase. The engine-state strategy is less sensitive to downshift, taking even unnecessary upshift decisions. The state intention strategy, however, interprets the driver's intention correctly for decreasing speed and utilizes engine brake torque to reduce the vehicle speed in a shorter time.

A novel multi-parameter coordinated shift control strategy for an automated manual transmission based on fuzzy inference

2016 ◽  
Vol 231 (5) ◽  
pp. 684-699 ◽  
Author(s):  
Lipeng Zhang ◽  
Xiaohong Zhang ◽  
Zongqi Han ◽  
Junyun Chen ◽  
Jingchao Liu
Keyword(s):  
Control Strategy ◽  
Dynamic Performance ◽  
Automatic Transmission ◽  
Rate Of Change ◽  
Manual Transmission ◽  
Vehicle Speed ◽  
Shift Control ◽  
Automated Manual Transmission ◽  
Shift Strategy ◽  
Driver’S Intention

For a vehicle equipped with an automatic transmission, the shift control strategy should reflect the driver’s intention in the dynamic performance and the economy performance of the vehicle. However, the driver’s intention is difficult to identify and involve in the shift strategy because of the complexity of driving environments, the diversity of powertrain parameters and the randomness of the driver’s behaviour. Therefore, in this paper, by considering a vehicle equipped with an automated manual transmission as the study object, a novel multi-parameter coordinated shift control strategy is proposed on the basis of identification of the driver’s intention. First, in order to predict the intention of the driver more effectively, the relative opening degree of the accelerator is defined on the basis of the dynamic analysis. Then, the characteristics of the driver’s expected acceleration, which involve the influence of the driving environment, are proposed. They can be classified into five categories, namely stop, deceleration, keep, acceleration and urgent acceleration. Next, a fuzzy control system is designed to identify the driver’s acceleration characteristics in real time. This considers the vehicle speed, the rate of change in the opening degree of the accelerator and the relative opening degree of the accelerator as the inputs and the quantitative intention of the driver as the output. Finally, the novel multi-parameter coordinated shift control strategy is formulated on the basis of the vehicle speed, the opening degree of the accelerator and the quantitative intention of the driver. The designed shift strategy is compared with conventional methods using simulations and is verified by road tests. The results show that the shift control strategy can make the vehicle shift much more effective.

Speed regulation control of tractors’ new dual-flow transmission system based on slip rate resistance classification

2021 ◽  
pp. 095440702110105
Author(s):  
Guang Xia ◽  
Yan Xia ◽  
Xiwen Tang ◽  
Linfeng Zhao ◽  
Baoqun Sun
Keyword(s):  
Control Strategy ◽  
Control Algorithm ◽  
Production Efficiency ◽  
Sliding Mode ◽  
Slip Rate ◽  
Speed Control ◽  
Working Environment ◽  
Vehicle Speed ◽  
Speed Change ◽  
Simulation Results

Fluctuations in operation resistance during the operating process lead to reduced efficiency in tractor production. To address this problem, the project team independently developed and designed a new type of hydraulic mechanical continuously variable transmission (HMCVT). Based on introducing the mechanical structure and transmission principle of the HMCVT system, the priority of slip rate control and vehicle speed control is determined by classifying the slip rate. In the process of vehicle speed control, the driving mode of HMCVT system suitable for the current resistance state is determined by classifying the operation resistance. The speed change rule under HMT and HST modes is formulated with the goal of the highest production efficiency, and the displacement ratio adjustment surfaces under HMT and HST modes are determined. A sliding mode control algorithm based on feedforward compensation is proposed to address the problem that the oil pressure fluctuation has influences on the adjustment accuracy of hydraulic pump displacement. The simulation results of Simulink show that this algorithm can not only accurately follow the expected signal changes, but has better tracking stability than traditional PID control algorithm. The HMCVT system and speed control strategy models were built, and simulation results show that the speed control strategy can restrict the slip rate of driving wheels within the allowable range when load or road conditions change. When the tractor speed is lower than the lower limit of the high-efficiency speed range, the speed change law formulated in this paper can improve the tractor speed faster than the traditional rule, and effectively ensure the production efficiency. The research results are of great significance for improving tractor’s adaptability to complex and changeable working environment and promoting agricultural production efficiency.

Robust stabilization control of a spatial inverted pendulum using integral sliding mode controller

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Ishan Chawla ◽  
Vikram Chopra ◽  
Ashish Singla
Keyword(s):  
Inverted Pendulum ◽  
Sliding Mode ◽  
Robust Stabilization ◽  
Linear Quadratic Regulator ◽  
Humanoid Robots ◽  
Sliding Mode Controller ◽  
Linear Quadratic ◽  
Integral Sliding Mode ◽  
Wide Range ◽  
Lqr Controller

AbstractFrom the last few decades, inverted pendulums have become a benchmark problem in dynamics and control theory. Due to their inherit nature of nonlinearity, instability and underactuation, these are widely used to verify and implement emerging control techniques. Moreover, the dynamics of inverted pendulum systems resemble many real-world systems such as segways, humanoid robots etc. In the literature, a wide range of controllers had been tested on this problem, out of which, the most robust being the sliding mode controller while the most optimal being the linear quadratic regulator (LQR) controller. The former has a problem of non-robust reachability phase while the later lacks the property of robustness. To address these issues in both the controllers, this paper presents the novel implementation of integral sliding mode controller (ISMC) for stabilization of a spatial inverted pendulum (SIP), also known as an x-y-z inverted pendulum. The structure has three control inputs and five controlled outputs. Mathematical modeling of the system is done using Euler Lagrange approach. ISMC has an advantage of eliminating non-robust reachability phase along with enhancing the robustness of the nominal controller (LQR Controller). To validate the robustness of ISMC to matched uncertainties, an input disturbance is added to the nonlinear model of the system. Simulation results on two different case studies demonstrate that the proposed controller is more robust as compared to conventional LQR controller. Furthermore, the problem of chattering in the controller is dealt by smoothening the controller inputs to the system with insignificant loss in robustness.

scholarly journals Design of hybrid sliding mode controller based on fireworks algorithm for nonlinear inverted pendulum systems

2017 ◽  
Vol 9 (1) ◽  
pp. 168781401668427 ◽  
Author(s):  
Te-Jen Su ◽  
Shih-Ming Wang ◽  
Tsung-Ying Li ◽  
Sung-Tsun Shih ◽  
Van-Manh Hoang
Keyword(s):  
Inverted Pendulum ◽  
Sliding Mode ◽  
Linear Quadratic Regulator ◽  
Sliding Mode Controller ◽  
Proportional Integral Derivative ◽  
Linear Quadratic ◽  
Pendulum System ◽  
Fireworks Algorithm ◽  
Simulation Process ◽  
Inverted Pendulum System

The objective of this article is to optimize parameters of a hybrid sliding mode controller based on fireworks algorithm for a nonlinear inverted pendulum system. The proposed controller is a combination of two modified types of the classical sliding mode controller, namely, baseline sliding mode controller and fast output sampling discrete sliding mode controller. The simulation process is carried out with MATLAB/Simulink. The results are compared with a published hybrid method using proportional–integral–derivative and linear quadratic regulator controllers. The simulation results show a better performance of the proposed controller.

scholarly journals Mathematical Modelling and Control of a Two-Wheeled PUMA-LikeVehicle

2016 ◽  
Vol 6 (2) ◽  
pp. 11 ◽  
Author(s):  
Khaled M Goher
Keyword(s):  
Mathematical Modelling ◽  
Sliding Mode ◽  
Impact Load ◽  
State Space Model ◽  
Linear Quadratic Regulator ◽  
The Body ◽  
Pole Placement ◽  
General Motors ◽  
Linear Quadratic ◽  
And Control

<p class="1Body">This paper presents mathematical modelling and control of a two-wheeled single-seat vehicle. The design of the vehicle is inspired by the Personal Urban Mobility and Accessibility (PUMA) vehicle developed by General Motors® in collaboration with Segway®. The body of the vehicle is designed to have two main parts. The vehicle is activated using three motors; a linear motor to activate the upper part in a sliding mode and two DC motors activating the vehicle while moving forward/backward and/or manoeuvring. Two stages proportional-integral-derivative (PID) control schemes are designed and implemented on the system models. The state space model of the vehicle is derived from the linearized equations. Controller based on the Linear Quadratic Regulator (LQR) and the pole placement techniques are developed and implemented. Further investigation of the robustness of the developed LQR and the pole placement techniques is emphasized through various experiments using an applied impact load on the vehicle.</p>

Sign in / Sign up

Export Citation Format

Share Document