State feedback controller design for the synchronization of Boolean networks with time delays

In this paper, we propose an adaptive fuzzy output feedback control method for trajectory tracking control problem for robotic systems. Using Lyapunov method, we first develop a stable adaptive fuzzy state feedback control algorithm by assuming that the systems output and its derivatives are available for feedback control design. The algorithm combines fuzzy systems with robust adaptive controller. The fuzzy system approximates the certainty equivalent (CE)-based optimal controller while robustifying adaptive control term is used to cope with uncertainties that appeared from the effect of external disturbance, fuzzy approximation errors and other modeling errors. Then, an output feedback form of the position-velocity (state feedback) controller is proposed where unknown velocity signal is replaced by the output of model-free linear estimator. We show via asymptotic analysis that the tracking performance of the output feedback design can recover the performance achieved under the state feedback control design. Finally, the proposed method is implemented and evaluated on a 2-DOF robotic system to demonstrate the theoretical development for the real-time applications.

State feedback controller design for synchronization of master–slave Boolean networks based on core input-state cycles

This paper is concerned with the output feedback control problem for a class of nonlinear system with time delay. First, a state feedback controller is design and a sufficient condition with exponential stability is obtained. Second, we study the observer design problem. And we proved that the observer designed in this paper ensure the observation error exponential converge to zero. Furthermore, output feedback controller using state feedback control and observer design is studied.

The stability analysis and controller design of discrete linear systems with time-varying delay are addressed. Firstly, the uniformly asymptotical stability criterion with adjustable parameter is derived by Lyapunov-Razumikhin approach. Then, the stabilization approaches for linear systems with time delay by state feedback and observer based-on state feedback are also presented. Sufficient conditions for the existence of state feedback gain and the observer gain are derived through the numerical solution of a set of obtained linear matrix inequalities. Compared with methods in the references, the dynamic performance of systems, such as the overshoot and the convergence rate of the response, can be adjusted by changing the adjustable parameter. Lastly, an illustrative example is given to show the effectiveness of the proposed.

This paper presents a new dilated linear matrix inequality (LMI) representation to design a state feedback controller and a dynamic feedforward disturbance compensator for linear parameter-varying (LPV) systems. The improved LMIs are convex and finite-dimensional without any iterative approach. The designs are based on a new proposed equivalent bounded real lemma (BRL) by means of matrix dilation for LPV systems and uncertain linear systems under time-varying parametric uncertainties (TVPUs). This dilated BRL provides lower conservative results than existing methods in terms of robust stability. Accordingly, a dynamic disturbance compensator is designed in addition to a state feedback controller. This paper mainly focuses on the design of compensators against disturbances in addition to the design of state feedback controllers. The dynamic matrices of the compensator change with the time-varying parameters of the LPV or uncertain system during operation, assuming that the disturbances and the parameters are measurable or observable. The compensator can be designed to attenuate the disturbances/noises or to improve reference tracking. Finally, numerical and simulation outcomes are presented to prove both the effectiveness and lower conservativeness of the proposed LMIs.

This paper is concerned with the design of state feedback controller for networked control systems. The networked control system with random network induced delay is modeled as a discrete-time system with uncertainties and two time-varying input delays. Based on this model, a method to design a state feedback controller is proposed. The controller gain can be obtained by solving a set of linear matrix inequalities. Two examples are given to illustrate the effectiveness of the method.

This paper presents the design and implementation of optimal and robust state feedback controller for rotary inverted pendulum system. The Particle Swarm Optimization (PSO) method is used to find the optimal values of the state feedback gains subject to time response specifications and H_∞ constraints. To improve the tracking of the system, a robust state feedback plus integral controller is designed. The simulation results show that the proposed controller can effectively stabilize the pendulum at the upright position. Further, the proposed controller can compensate the variations in system parameters. The effectiveness of the proposed controller is verified experimentally using real rotary inverted pendulum.

This paper presents the design and analysis process of state feedback controllers for NPC type 3-level sine wave inverter. In order to achieve good dynamic features in a state feedback control an internal model of reference input and a feedforward path are introduced. During synthesis process of the state feedback controllers maximum permissible dynamics of voltage control in the linear range of modulation is taken into account. It is shown that initially gains of the controller and feedforward path are non-stationary and depend on the angular velocity. Stationary approximation of a non-stationary state feedback controller is presented in details. Proposed state feedback control structures for continuous voltage shaping NPC type 3-level voltage source inverter are examined in FOC PMSM drive. The novelty of the presented controller lays in a stationary approximated state feedback control structure designed in terms of maximum permissible dynamics of a voltage control system. Simulation and experimental results (at the level of 3 kW) of the designed control algorithms are included.

6 - Design and Performance of Feedback Controllers

In this study an effective method is introduced to stabilize fractional-order singular time-delay systems, while time-delay can belong to a specified interval from zero to a given amount of delay. A new approach to decompose fractional-order singular time-delay systems (FOSTDSs) and transform them to normal fractional-order time-delay systems (FOTDSs) with a lower order is presented. Also, as this decomposition reduces the order of the system, reducing the computational complexity is one of the important benefits of this method. Then, a stabilization method is provided to stabilize the linear singular fractional delay systems in a range of zero to one given delay. By presenting three examples in this paper, the applicability and effectiveness of this method are shown.

This paper presents a Proportional-Derivative State Feedback (PDSF) controller approach to design an active suspension system for quarter car. The objective of the PDSF controller is to eliminate the effects of road disturbances to achieve ride comfort of the driver and passengers. Finding the optimal feedback gain matrix of the PDSF controller is formulated as an optimization problem. Then, two meta-heuristic optimizations named Bees Algorithm (BA) and Grey Wolf Optimization (GWO) are employed to optimize the feedback gain matrix of the PDSF controller based on the Integral Time of Absolute Error (ITAE) index. The results show the superiority of the BA-based PDSF controller in terms of reducing the ITAE index in comparison with the results obtained from GWO based PDSF.

This paper deals with the design of robust state feedback controller based on fuzzy logic and its evaluation in adjusting the speed of an induction machine. The basic idea of the proposed controller is similar to the gain scheduling approach. The design is based on a reduced order state space model of the motor drive from which a family of local state space models covering the operating range of the drive system are defined. We then use the state feedback design concept to get a linear state feedback controller for each local model using pole placement topology. The performance of the fuzzy state feedback controller is evaluated under different operating regimes of the drive system.

This paper is concerned with the drive-response synchronization for a class of fractional-order bidirectional associative memory neural networks with time delays, as well as in the presence of discontinuous activation functions. The global existence of solution under the framework of Filippov for such networks is firstly obtained based on the fixed-point theorem for condensing map. Then the state feedback and impulsive controllers are, respectively, designed to ensure the Mittag-Leffler synchronization of these neural networks and two new synchronization criteria are obtained, which are expressed in terms of a fractional comparison principle and Razumikhin techniques. Numerical simulations are presented to validate the proposed methodologies.

Results on the design of robust memoryless state feedback controllers for uncertain time-delay systems with norm bounded uncertainty are presented. It is proved that the feasibility of a linear matrix inequality (LMI) problem is necessary and sufficient for the quadratic stabilisation of an uncertain time-delay system. A robust state feedback controller can be constructed using the corresponding feasible solution of the LMI problem. A procedure is given to select a suitable state feedback controller that is also suboptimal in the sense of minimising a bound on a quadratic performance index.

Impulsive controller design for exponential synchronization of delayed stochastic memristor-based recurrent neural networks