Stochastic Network-induced Delays Research Articles

Non-fragile robust output feedback control of uncertain active suspension systems with stochastic network-induced delay

The vehicle active suspension has attracted considerable attention owing to its great contributions to the vertical dynamics of vehicle. This paper investigates the non-fragile output feedback control problem of the uncertain vehicle active suspension with stochastic network-induced delay. Firstly, taking the variation of sprung and unsprung masses into consideration, an interval type-2 (IT-2) Takagi–Sugeno (T–S) fuzzy model is introduced to describe the nonlinear characteristics of active suspension systems (ASSs). Secondly, to ensure that the control strategy is practicable when some states are unmeasured, a novel output feedback method is proposed by employing a variable substitution approach. Meanwhile, in order to approximate the real physical conditions of the control system, the gain perturbations are taken into account. Thirdly, with regard to the complexity of signal transmission delay in network control process, a more generalized lumped delay form is employed to represent the network-induced delay. Moreover, to describe the stochasticity of lumped delay, a Markovian process is introduced. Finally, both numerical simulations and experimental tests are carried out to examine the effectiveness and practicability of the proposed controller.

Robust Gain-Scheduling Path Following Control of Autonomous Vehicles Considering Stochastic Network-Induced Delay

This paper concerns the robust gain-scheduling control issue for autonomous path following systems with stochastic network-induced delay. Firstly, to effectively approximate the highly nonlinear tire dynamics, the linear fractional transformation formulations are employed to describe the tire cornering stiffness with a norm-bounded uncertainty. Secondly, by taking the data dropout and delay encountered in signal computation and transmission into account, a more generalized lumped delay form is proposed to unify the time-varying data dropout and network-induced delay. Moreover, a Markovian process is presented to describe the lumped delay as a stochastic distribution. Thirdly, to address the issue of varying vehicle velocity, a linear parameter varying model is established to capture vehicle lateral behaviors. Based on the stochastic stability theory, a new robust gain-scheduling path following control method is proposed for the autonomous vehicles. Finally, the experimental study is presented to bridge the gap between the theoretical and practical investigations on path following control of autonomous vehicles, and results validate the superior performance of the proposed method compared with existing works.

Robust stability and stabilization of networked control systems with stochastic time-varying network-induced delays

This paper investigates the robust stability analysis and state feedback controller design of networked control systems (NCSs). A stochastic network-induced delay in given interval with known lower and upper bounds is considered. Therefore, the NCS is modeled as linear system with probabilistic time-varying delay distribution. Then, the Lyapunov-Krasovskii functional (LKF) is formulated using probabilistic informations of both lower and upper bounds of the time-varying network-induced delay, and Wirtinger-based integral inequalities are used to estimate the accuracy of the resulting time derivatives and also to reduce conservatism by introducing some new cross terms. Afterwards, stability condition based on [Formula: see text] disturbance attenuation level is expressed in terms of a set of linear matrix inequalities (LMIs), and Finsler’s lemma is used to relax it by adding slack decision variables and decoupling the systems matrices from those of Lyapunov-Krasovskii. This procedure makes the state feedback controller design as simple as a variables change. Finally, a maximum allowable upper bound of the network-induced delay and state feedback controller gains are calculated by resolving the above relaxed LMIs’ convex optimization problem. Practical numerical examples are provided to validate the proposed approach; the results show that the negative effects of the unpredictable network-induced delays are compensated and the stability of NCSs with high disturbance attenuation level is guaranteed. A comparative study with other results in recent researches is also given and the superiority of the proposed method in terms of robustness and conservatism reduction is shown.

Optimal linear quadratic control for wireless sensor and actuator networks with random delays and packet dropouts

In this article, the optimal linear quadratic control problem is considered for the wireless sensor and actuator network with stochastic network-induced delays and packet dropouts. Considering the event-driven relay nodes, the optimal solution is obtained, which is a function of the current plant state and all past control signals. It is shown that the optimal control law is the same for all locations of the controller placement. Since the perfect plant state information is available at the sensor, the optimal controller should be collocated with the sensor. In addition, some issues such as the plant state noise and suboptimal solution are also discussed. The performance of the proposed scheme is investigated by an application of the load frequency control system in power grid.

Predictive Approach for Sensorless Bimanual Teleoperation Under Random Time Delays With Adaptive Fuzzy Control

Robot teleoperation techniques are applied in industrial automation, space, and surgery. Considering the high cost of force–torque (F/T) sensors, an “indirect estimation” of the external force is preferable to “direct sensing” of the force. This study provides a predictive control method for a bimanual teleoperation system without F/T and acceleration sensors. Two types of mirror predictors are built into the control architecture. One of them is a position predictor estimating the position states of the remote side under stochastic network-induced delays. The force predictor estimates the contact forces and dynamic uncertainties utilizing the local time-delayed information. By accurately estimating the local force, the position predictors/observers are used to estimate the internal dynamics of the master and slave simultaneously, and thereby, avoid using the delayed transmitted information. An adaptive fuzzy control strategy based on linear matrix inequalities (LMIs) is proposed to evaluate and suppress the uncertainties, thereby, ensuring that the synchronization errors of the system positions converge to zero and the estimated force approaches real values. The system stability of the closed-loop system is proven using LMIs based on a Lyapunov–Krasovskii functional synthesis. An experimental test involving a dual-arm robot, YuMi, holding and moving a yoga ball is performed based on a semiphysical platform.

Stochastic optimal linear control of wireless networked control systems with delays and packet losses

In this study, the design of the optimal decentralised state-feedback controllers is considered for a wireless sensor and actuator network (WSAN) with stochastic network-induced delays and packet losses. In particular, taking advantage of multiple controllers, the authors model the WSAN as a wireless networked control system with decentralised controllers, and then formulate the stochastic optimal state-feedback control problem as a non-cooperative linear quadratic game. The optimal control law of each controller is obtained that is a function of the current plant state and past control signals. The performance of the proposed algorithm is investigated by an unstable linearised inverted pendulum and an application of the load frequency control system in power grid.

Decentralized feedback control for wireless sensor and actuator networks with multiple controllers

In this paper, the design of the optimal decentralized full-state-feedback control is considered for a wireless sensor and actuator network with multiple controllers in the presence of stochastic network-induced delays and plant state noise. In particular, using the quadratic cost function, the design problem with decentralized controllers is formulated as a non-cooperative linear quadratic game. Then, the optimal control law of each controller is obtained that is a function of the current plant state and finite past control signals. The performance of the proposed algorithm is evaluated by a stable control system and an application of the load frequency control system in power grid.

Robust <i>Η<sub>∞</sub> </i>Controller Design for Networked Control Systems with Exponential Convergence

The output feedback exponential robust control for networked control systems with stochastic network-induced delay and packet dropout is studied. Firstly, a state observer is designed for estimating the state values and compensating data dropouts. Then the closed system is modeled as asynchronous dynamical system constrained by configuration event rate. By using Lyapunov principle, sufficient and necessary conditions for robust stability and exponential stability of the closed loop system is obtained and the output feedback controller design method is presented. Simulation example for the design is done, comparing with the other relative methods, the results shows the validity of the method.

Robust H∞ control for networked control systems *

The robust H ∞ control for networked control systems with both stochastic network-induced delay and data packet dropout is studied. When data are transmitted over network, the stochastic data packet dropout process can be described by a two-state Markov chain. The networked control systems with stochastic network-induced delay and data packet dropout are modeled as a discrete time Markov jump linear system with two operation modes. The sufficient condition of robust H ∞ control for networked control systems stabilized by state feedback controller is presented in terms of linear matrix inequality. The state feedback controller can be constructed via the solution of a set of linear matrix inequalities. An example is given to verify the effectiveness of the method proposed.