Journal of Control
Year:2017 | Volume:11 | Issue:3 |Papers Count:7

In this paper, the problem of distributed state estimation of a nonlinear dynamical system in a decentralized Wireless Sensor Network (WSN) in the presence of state-dependent observation noise is considered. Some bearings or ranging devices, such as ultrasonic sensors, have distance-dependent measurement error and their measurement noise variance grows as their relative distance to the target increases. This state-dependent measurement error leads to poor performance of estimation algorithm. To solve this problem, a consensus-based distributed state estimation methodology is presented in this paper by reaching a consensus on likelihood functions in the presence of state-dependent observation noise of bearings sensors. To reduce energy consumption in WSN, a distributed sensor selection algorithm is proposed. Unlike centralized networks, no fusion center is deployed in decentralized networks to gather and process the collected data, globally. Moreover, there is no global knowledge of the network topology in decentralized networks. Therefore, the Posterior Cramér-Rao Lower Bound (PCRLB) is derived in a distributed fashion in the presence of state-dependent noise of bearings sensors, to perform an adaptive sensor selection algorithm. Simulation results demonstrate the effectiveness of the proposed state estimation and sensor selection algorithms for a target tracking problem.

This paper presents the implementation of the event-triggered technique on sliding mode control (SMC) method in the case of linear systems with bounded uncertainty. Event triggered technique is a scheduling strategy to reduce the number of control updates in a feedback loop. The Main contribution of this paper is to implement event-triggered SMC on the linear multi input linear systems with parameter uncertainties. Although the chattering is inevitable in SMC, to tackle this phenomenon, hysteresis bounds are offered to reduce the frequency of control updates; nevertheless it induces a limit cycle. By updating control law at hysteresis boundaries, as the event triggering rule, system finally ends to limit cycle. Another contribution of this paper is to reduce the amplitude of this limit cycle according to the variable control input, while guaranteeing no request for successive control updates too. In this paper by properly designing dynamic control law and hysteresis bands based on state trajectory, as the system moves towards the stable point, its amplitude decreases and the limit cycle amplitude fades accordingly. This method is illustrated by an example of linear system with uncertainty in the system matrix. Simulation results depict the applicability of SMC combination with the event-triggered technique.

In this paper, a constrained nonlinear optimal control law is analytically developed for vehicle active suspension system considering the limitation of hydraulic actuator. In the design of the controller, the nonlinear characteristics of spring and damper forces and hydraulic actuator are considered. The control input is the displacement of the hydraulic valve spool which is bounded in practice and its constraint should be considered in the design process. In the proposed method, the control problem is firstly transformed to a constrained nonlinear optimization problem by performing a performance index defined as a weighted combination of predicted responses of nonlinear suspension system and control input. Then, this equivalent constrained optimization problem is solved using Kuhn-Tucker theorem to find the constrained optimal control law. The derived control law is in the closed form which is easy to solve and implementation. The controller performance is evaluated through computer simulation of the vehicle suspension model excited by a random road input. The obtained result indicate a remarkable decrease of the body acceleration Downloaded from which leads to the ride comfort. Meanwhile, other suspension responses including suspension and tire deflections are in suitable ranges.

In this paper, the state feedback and design problem of state observer are presented to stabilize the discrete-time piecewise linear systems. In this article, we have two discrete-time systems that one of them is the disturbed system and the other is the system without disturbance.The linear matrix inequalities approach, piecewise quadratic Lyapunov functions and the Finsler’s lemma are used to design the state observer. In addition to the above mentioned methods, the H¥ control approach used to design the state observer for the system with external disturbance. The H¥control approach undermines the disturbance signal and provides an appropriate estimation of the system states. In this paper, by using the Finsler’s lemma, a set of slack variables are introduced to reduce the design conservatism. The Simulation results show the high performance of the proposed method for stabilize the closed-loop system and achieve to the acceptable estimation of state variables.

This paper investigates the problem of finite-time stabilization of a class of uncertain nonlinear systems and a controller is proposed based on combination of integral sliding mode control with finite-time state feedback. The proposed controller consists of two parts. One part rejects matched uncertainties and the other part provides finite time stability. An adaption mechanism is also employed to estimate unknown parameters of the system. The proposed control law guarantees finite-time convergence of the sliding variable in the presence of uncertainties and unknown parameters. By elimination of the reaching phase, in which the system states are quite sensitive to any uncertainties or disturbances, the robustness of the system is guaranteed throughout the entire response. Furthermore, the upper bound of disturbance and uncertainties is not required to be known in advance which makes the suggested controller more flexible in terms of implementation.

In this paper, stabilization and trajectory tracking control of the double inverted pendulum (DIP) as a benchmark under actuated highly nonlinear dynamical system, attributed with specific control complexities using hybrid observer based indirect fuzzy adaptive control is investigated. Due to inherent nature of the process that the equal number of control inputs as the degrees of freedom of the plant are not available, therefore, setting up the control action faces with serious challenges. Meanwhile, inaccessibility assumption to some state parameters as the most important factor in designing the controller by means of the proposed control method is for the first time addressed stabilizing the specified plant in this research. In order to illustrate the performance of the proposed approach, specific simulation software is developed in Matlab/Simulink platform.Set of conducted simulation results and comparative studies with the published papers addressing the same aim, showing the capability and excellence of the proposed hybrid fuzzy adaptive observer control approach achieving the targets in terms of establishing stabilization, trajectory tracking and robustifying the under controlled plant.