2,754 research outputs found
Research on Advanced Control Strategies for Vehicle Active Seat Suspension Systems
Vehicle seat suspensions play a very important role in vibration reduction for vehicle drivers, especially for some heavy vehicles. Compared with small vehicles, these heavy vehicle drivers suffer much more from vibrations, which influence driving comfort and may cause health problems, so seat suspensions are necessary for those heavy vehicle drivers to reduce vibrations and improve driving comfort. Advanced control systems and control strategies are investigated for vehicle seat suspensions in this project. Firstly, for an active single-degree of freedom (single-DOF) seat suspension, a singular system-based approach for active vibration control of vehicle seat suspensions is proposed, where the drivers’ acceleration is augmented into the conventional seat suspension model together with seat suspension deflection and relative velocity as system states to make the suspen- sion model as a singular system. Then, an event-triggered H∞ controller is designed for an active seat suspension, where both the continuous and discrete-time event-triggered schemes are considered, respectively. The proposed control method can reduce the work- load of data transmission of the seat suspension system and work as a filter to remove the effect of noise, so it can decrease the precision requirement of the actuator, which can help to reduce the cost of the seat suspension. For complicated seat suspension systems, a singular active seat suspension system with a human body model is also established and an output-feedback event-triggered H∞ controller is designed. The accelerations of each part are considered as part of the system states, which makes the system a singular sys- tem. The seat suspension deflection, relative velocity, the accelerations of the seat frame, body torso, and head are defined as the system outputs. At last, to deal with whole-body vibration, a control system and a robust H∞ control strategy are designed for a 2-DOF seat suspension system. Two H∞ controllers are designed to reduce vertical and rotational vibrations simultaneously. All the proposed seat suspension systems and control methods are verified by simulations and some are also tested by experiments. These simulation and experimental results show their effectiveness and advantages of the proposed methods to improve the driving comfort and some can reduce the workload of data transmission
Event-Triggered Multi-Lane Fusion Control for 2-D Vehicle Platoon Systems with Distance Constraints
This paper investigates the event-triggered fixedtime multi-lane fusion control for vehicle platoon systems with
distance keeping constraints where the vehicles are spread in
multiple lanes. To realize the fusion of vehicles in different lanes,
the vehicle platoon systems are firstly constructed with respect to
a two-dimensional (2-D) plane. In case of the collision and loss of
effective communication, the distance constraints for each vehicle
are guaranteed by a barrier function-based control strategy.
In contrast to the existing results regarding the command
filter techniques, the proposed distance keeping controller can
constrain the distance tracking error directly and the error
generated by the command filter is coped with by adaptive fuzzy
control technique. Moreover, to offset the impacts of the unknown
system dynamics and the external disturbances, an unknown
input reconstruction method with asymptotic convergence is
developed by utilizing the interval observer technique. Finally,
two relative threshold triggering mechanisms are utilized in the
proposed fixed-time multi-lane fusion controller design so as to
reduce the communication burden. The corresponding simulation
results also verify the effectiveness of the proposed strategy
Double Asynchronous Switching Control for Takagi–Sugeno Fuzzy Markov Jump Systems via Adaptive Event-Triggered Mechanism
This article addresses the issue of adaptive event- triggered H∞ control for Markov jump systems based on Takagi-Sugeno (T-S) fuzzy model. Firstly, a new double asynchronous switching controller is presented to deal with the problem of the mismatch of premise variables and modes between the controller and the plant, which is widespread in real network environment. To further reduce the power consumption of communication, a switching adaptive event-triggered mechanism is adopted to relieve the network transmission pressure while ensuring the control effect. In addition, a new Lyapunov-Krasovskii functional (LKF) is constructed to reduce conservatism by introducing the membership functions (MFs) and time-varying delays informa- tion. Meanwhile, the invariant set is estimated to ensure the stability of the system. And the disturbance rejection ability is measured by the optimal H∞ performance index. Finally, two examples are presented to demonstrate the effectiveness of the proposed approach
Skyhook-PID Control Strategy to Improve Performance of a Pneumatic Active Suspension System
The research applies a skyhook-PID control method for an active suspension system. The control strategy has three feedback control loops. They are the innermost loop for the force tracking of the pneumatic actuator, the intermediate loops applying skyhook strategy for the elimination of the disturbances, and the outermost loop using PID controller for the determination of the desired force. Some experiments were carried out on a physical test rig with a hardware-in-the-loops feature. The performance of the proposed control method was evaluated and benchmarked to examine the effectiveness of the system in suppressing the disturbance effect of the suspension system. It was found that the experimental results demonstrate the superiority of the active suspension system with Skyhook-PID scheme compared to the PID and passive suspension systems
Adaptive Fuzzy Tracking Control with Global Prescribed-Time Prescribed Performance for Uncertain Strict-Feedback Nonlinear Systems
Adaptive fuzzy control strategies are established to achieve global
prescribed performance with prescribed-time convergence for strict-feedback
systems with mismatched uncertainties and unknown nonlinearities. Firstly, to
quantify the transient and steady performance constraints of the tracking
error, a class of prescribed-time prescribed performance functions are
designed, and a novel error transformation function is introduced to remove the
initial value constraints and solve the singularity problem in existing works.
Secondly, based on dynamic surface control methods, controllers with or without
approximating structures are established to guarantee that the tracking error
achieves prescribed transient performance and converges into a prescribed
bounded set within prescribed time. In particular, the settling time and
initial value of the prescribed performance function are completely independent
of initial conditions of the tracking error and system parameters, which
improves existing results. Moreover, with a novel Lyapunov-like energy
function, not only the differential explosion problem frequently occurring in
backstepping techniques is solved, but the drawback of the semi-global
boundedness of tracking error induced by dynamic surface control can be
overcome. The validity and effectiveness of the main results are verified by
numerical simulations on practical examples
Extended Dissipative Filter for Delayed T-S Fuzzy Network of Stochastic System with Packet Loss
This research investigates a time-varying delay-based adaptive event-triggered dissipative filtering problem for the interval type-2 (IT-2) Takagi-Sugeno (T-S) fuzzy networked stochastic system. The concept of extended dissipativity is used to solve the ,  and dissipative performances for (IT-2) T-S fuzzy stochastic systems in a unified manner. Data packet failures and latency difficulties are taken into account while designing fuzzy filters. An adaptive event-triggered mechanism is presented to efficiently control network resources and minimise excessive continuous monitoring while assuring the system’s efficiency with extended dissipativity. A new adaptive event triggering scheme is proposed which depends on the dynamic error rather than pre-determined constant threshold. A new fuzzy stochastic Lyapunov-Krasovskii Functional (LKF) using fuzzy matrices with higher order integrals is built based on the Lyapunov stability principle for mode-dependent filters. Solvability of such LKF leads to the formation of appropriate conditions in the form of linear matrix inequalities, ensuring that the resulting error mechanism is stable. In order to highlight the utility and perfection of the proposed technique, an example is presented
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