A vector decomposition approach to F–M model realization and its application to robust observed-state feedback control

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.

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.

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 studies the robust discrete-time pole-placement state feedback controller design in the LMI framework. The inner ellipse is used to approximate originally non-convex discrete-time closed loop pole region respective to the prescribed damping factor. The resulting LMI conditions use parameter dependent Lyapunov function to reduce conservatism in robust controller design. Contribution of this paper is in the application of this procedure on the case study - unstable Magnetic Levitation System, analysis of the results and comparison with standard robust stabilizing controller design.

Circle Condition-Based Robust Feedback Control Against Plant Perturbation

This paper describes a procedure for multivariable state feedback robust controller design. The plant in state space is given by the operational point description or in terms of a vector of slow varying physical parameters. Through solution of the Sylvester matrix equation, a nonunique static feedback controller, which assigns the prespecified closed-loop spectrum, is calculated. In addition, all the remaining feedback degrees of freedom are utilized to optimize a multiobjective function that reflects further design properties. The robust feedback gains is calculated through a three-phase computational algorithm. Numerical examples show that under the robust state feedback control, the closed-loop systems can both achieve satisfied transient characteristics and greatly reduce state trajectory sensitivity to small or large parameter variations in the plant. The pro-posed procedure is still applied to a VTOL aircraft model.

This paper addresses the problem of robust output feedback controller design with guaranteed cost and multiple quadratic Lyapunov function for linear switched systems in the continuous-time domain. The approach followed in this paper looks at the existence of switched quadratic Lyapunov function to check asymptotic stability of the switched system under consideration. Two different linear matrix inequality based conditions allow checking the existence of a family of quadratic Lyapunov functions. Then, a switched robust output feedback design method is established. The proposed method is illustrated on numerical example.

This article investigates the robust optimal output regulation problem for the constrained uncertain nonlinear systems. A two‐step design framework is proposed to overcome the difficulties brought by uncertainties, constraint and performance optimization. First, the feedforward controller is designed by the internal model principle, and the robust output regulation problem is transformed into the robust stabilization problem. Then, the optimal control problem with input saturation is further considered in the robust feedback controller design process. With the help of a non‐quadratic cost functional, actor‐critic algorithm and robust redesign technique are brought together to design the constrained robust optimal feedback controller. Finally, stability analysis based on Lyapunov method shows that all the signals of the closed‐loop system remain bounded, and the tracking error is uniformly ultimately bounded with arbitrarily small ultimate bound. Simulation results illustrate the effectiveness of the proposed methodology.

The deployment of Autonomous Underwater Vehicles (AUVs) for ocean observation is one of the important methods in marine scientific research. The stability of AUV attitude control determines the efficiency and safety of underwater operations. In practical systems, the actuators carried by AUVs have saturation, and the saturation of the actuators greatly affects the performance and stability of AUV attitude control. This article designs an anti-windup [Formula: see text] robust state feedback controller and an anti-windup [Formula: see text] robust dynamic output feedback controller for the pitch attitude control of AUVs to solve the pitch attitude control problem of AUVs subject to input constraints. Firstly, building a Linear-parameter varying (LPV) model for the AUV. Then, we design two anti-windup [Formula: see text] robust controllers based on LPV model. Simulation results verify the reasonable of LPV model and the effectiveness of proposed controllers. Proposed controllers can enable the system to quickly reach the desired attitude under input constraints.

This paper proposes guaranteed cost design of robust output feedback controller for continuous linear parametric uncertain systems. New necessary and sufficient conditions for static output feedback stabilizability of linear continuous time systems underly the design procedure. Proposed algorithms are computationally simple and tightly connected with the Lyapunov stability theory and the LQR optimal state feedback design. The proposed approach allows for prescribing the structure of the output feedback gain matrix (including the decentralized one) by the designer. New design method proposed in this paper, exploit genetic algorithm to design robust controller with guaranteed cost for polytopic linear continuous time systems. Numerical example is given to illustrate the performance of the proposed robust controller.

The aim of this paper is to develop a novel robust variable sampling period controller (RVSPC) for networked control systems (NCSs) in the presence of random time delays and packet losses. Different from the existing control techniques for NCSs, the RVSPC controller is constructed as a hybrid robust controller with the adaptive variable sampling period. To adapt to the delay variation, a so-called variable sampling period adjuster based on a time delay predictor (TDP) and a time delay and packet detector is designed to adjust effectively the sampling period. To efficiently compensate for the random delays and packet losses, the hybrid controller is designed as a combination of a quantitative feedback theory (QFT)-based robust controller and a robust state feedback controller (RSFC) with adaptive control gain. A smart switch based on the TDP is then used to select properly the main control unit as the QFT or RSFC corresponding to the current delay and packet loss status. Illustrative examples with NCSs including both computation and communication delays and packet losses are finally carried out to illustrate the effectiveness of the proposed method.

Control design for nonlinear process models using linear robust control methods: An FCCU example

We focus on the design of robust reduced-order dynamic feedback control for a class of nonlinear systems with uncertainties. A robust nonlinear reduced-order dynamic controller (RNRDC) is proposed. The resulting closed-loop system can be robustly stabilized for all admissible uncertainties via the proposed controller. The application of the proposed RNRDC to a permanent magnet brush DC motor driving a single-link manipulator is also considered. The parameters uncertainties can be up to /spl plusmn/80%. The load can vary ranging from 50% to +100% of the nominal value. Our simulation results show that for the example system the proposed RNRDC can achieve good performance.

In this paper, the problem of robust stabilization is considered for a class of uncertain time-delay dynamical systems with completely unknown upper bounds of the delayed state perturbations, uncertainties, and external disturbances. For such a class of uncertain time-delay dynamical systems, a new design method is presented whereby a class of continuous memoryless adaptation-free robust state feedback controllers is constructed. That is, no adaptation law is introduced to update those completely unknown upper bounds. It is also shown that the solutions of the resulting closed-loop time-delay dynamical systems can be guaranteed to be uniformly exponentially bounded, instead of uniform ultimate boundedness. Finally, as an application of the results, the problem of water pollution control is considered for uncertain river time-delay systems due to industrial waste treatment facility, and the corresponding simulations are provided to demonstrate the validity of the theoretical results.

Decentralized robust guaranteed cost control for a class of interconnected singular large-scale systems with time-delay and parameter uncertainty