Mixed‐Objective Robust Dynamic Output Feedback Controller Synthesis for Continuous‐Time Polytopic Lpv Systems

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 a design method of robust dynamic output feedback controllers for a class of uncertain switched linear systems. The proposed controller consists of a switching rule, a dynamic output feedback controller with an adaptive compensation input, and the adaptive compensation input is tuned by updating laws. In this paper, we show that sufficient conditions for the existence of the proposed robust output feedback control system are given in terms of linear matrix inequalities (LMIs).

This chapter investigates the stabilization problem for a class of uncertain NCSs with random communication network-induced delays. The synthesis design procedure of a robust dynamic output feedback controller for linear NCSs is presented in this chapter. The sampling effects and the resulting system delays are incorporated into the design procedure. A system transformation approach is applied to convert the hybrid system which consists of both continuous and discrete signals into a system in the continuous realm. Based on the Lyapunov–Razumikhin method, the existence of such a controller is given in terms of the solvability of BMIs. An iterative algorithm is proposed to change this non-convex problem into quasi-convex optimization problems, which can be solved effectively by available mathematical tools. An illustrative example is given along with the theoretical presentation.

A robust adaptive NN-based output feedback control scheme is presented for a dynamic positioning ship with uncertainties and unknown external disturbances. We tackle the problem that velocity vector of a ship is not available by employing a high-gain observer, and develop the proposed control approach by combing vectorial backstepping with dynamic surface control approach, which is simpler and easier to implement in engineering practice. The neural network (NN) approximation technique is used to compensate for the uncertainties and unknown external disturbances, and it removes the requirement for the prior knowledge about the vessel parameters and external disturbances. Also, it is demonstrated that the proposed control strategy can force the position and yaw angle of a dynamic positioning ship to approach the desired point while guaranteeing all singles of the designed closed-loop dynamic positioning system semi-globally uniformly ultimately bounded by means of the Lyapunov function. Simulation results of a supply ship illustrate the effectiveness of the proposed scheme.

Robust adaptive fuzzy filters output feedback control of strict-feedback nonlinear systemsIn this paper, an adaptive fuzzy robust output feedback control approach is proposed for a class of single input single output (SISO) strict-feedback nonlinear systems without measurements of states. The nonlinear systems addressed in this paper are assumed to possess unstructured uncertainties, unmodeled dynamics and dynamic disturbances, where the unstructured uncertainties are not linearly parameterized, and no prior knowledge of their bounds is available. In recursive design, fuzzy logic systems are used to approximate unstructured uncertainties, and K-filters are designed to estimate unmeasured states. By combining backstepping design and a small-gain theorem, a stable adaptive fuzzy output feedback control scheme is developed. It is proven that the proposed adaptive fuzzy control approach can guarantee the all the signals in the closed-loop system are uniformly ultimately bounded, and the output of the controlled system converges to a small neighborhood of the origin. The effectiveness of the proposed approach is illustrated by a simulation example and some comparisons.

Novel direct adaptive robust state and output feedback controllers are presented for the output tracking control of a class of nonlinear systems with unknown system dynamics and disturbances. Both controllers employ a variable-structure radial basis function (RBF) network that can determine its structure dynamically to approximate unknown system dynamics. Radial basis functions are added or removed online in order to achieve the desired tracking accuracy and prevent to network redundancy. The raised-cosine RBF is employed to enable fast and efficient training and output evaluation of the RBF network. The direct adaptive robust output feedback controller is constructed by utilizing a high-gain observer to estimate the tracking error for the controller implementation. The closed-loop systems driven by the variable neural direct adaptive robust controllers are actually switched systems.

This paper addresses robust control design problem for parameter dependent (PD) systems subject to actuator saturation. The dead-zone nonlinearity is considered for regional stability and performance analysis of control design strategy. The parallel distributed compensation static output feedback controller is derived in new gain-scheduling scheme satisfied the generalized sector condition. Based on the fuzzy Lyapunov function approach, the parametrized stabilization non-convex conditions are reformulated in linear matrix inequalities (LMI) by congruence transformations. The proposed method leads to less conservative constraint on saturated PD controller synthesis. The effectiveness of the design methodology is demonstrated through simulations.

Magnetorheological fluid (MRF) dampers have been utilized in semi-active air suspension (SAAS) due to their attractive advantages. This paper investigates a novel robust fuzzy output feedback controller for semi-active air suspension with MRF damper (SAAS-MRFD), considering time delay and actuator saturation. An aero-thermodynamics theory is first utilized to describe the nonlinear air spring. The damping force of the MRF damper is represented by a hyperbolic tangent model. The interval type-2 (IT-2) Takagi–Sugeno (T-S) fuzzy method is second employed to capture those nonlinearities of the air spring and MRF damper. Considering the difficulty to measure all states, a novel dynamic output feedback (DOF) controller is developed by an appropriate Lyapunov–Krasovskii function and the reciprocally convex technique with consideration of time delay, actuator saturation, and output constraints. The effectiveness of the proposed controller is validated by both simulation and a quarter-car test rig (QCTR). The results indicate that the proposed controller has better performance in vibration reduction than the recent similar controllers in the literature.

To guarantee the control performance of the discrete system under unmeasurable state and partial actuator failure, a robust dynamic output feedback predictive fault-tolerant control method derived from switching strategy is developed. A new iterative error switching model is established, which both ensures tracking performance and lays the foundation for the development of the next switching controller. Based on this model, output feedback switching fault-tolerant controller is developed. Compared with conventional fault-tolerant control methods, the designed controller can be used under the case of unmeasurable states, and it is more fault tolerant and less conservative. According to the Lyapunov stability theory, the robust stability analysis is carried out under normal and fault conditions, respectively. Then, depending on the findings of the stability analysis, sufficient conditions to guarantee the stability of the closed-loop normal and faulty system are derived. Finally, the suggested method's efficacy is confirmed using the injection moulding process as an example.

The paper presents a robust nonlinear output feedback control system for the attitude control of satellites, with unstructured (unmodelled) dynamics in elliptic orbits, using solar radiation pressure. The nonaffine-in-control spacecraft model includes the gravity gradient torque, the control torque produced by two solar flaps, and external time-varying disturbance torque. The objective is to control the pitch angle of the spacecraft using the solar flaps. A robust feedback linearizing control law is derived for the trajectory control of the pitch angle. The controller includes a high-gain observer, which estimates the derivatives of the pitch angle as well as a lumped unstructured nonlinearity including the external disturbance moment in the pitch dynamics for synthesis. In the closed-loop system, the designed output feedback law accomplishes large angle rotational maneuvers. Simulation results are presented which show that in the closed-loop system, precise pitch angle control is accomplished, despite unmodelled nonlinearities and external disturbance torque in the model.KeywordsPitch AngleElliptic OrbitSolar Radiation PressureAttitude Control SystemSolar SailThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

International audience

The problem of dynamic output feedback control stabilization is considered for a class of multi-time delays uncertain nonlinear systems. Based on LMI and proper Lyapunov functions, a sufficient condition for the existence of robust output feedback controller is proposed, which ensures that the closed-loop system is robust stable. The dynamic output feedback controller is designed by the feasible solution of the matrix inequality with constraint. At last, by using matrix orthogonal complement, the parameters solving methods of output feedback controller is also provided.

This work presents a robust finite-time output feedback control method for a number of nonlinear systems that suffer unpredictable time-varying disturbances. The developed method takes advantage of control techniques based on a finite-time state observer used to estimate the lumped disturbance, where the estimator plays an important role in online compensation after being transmitted to a corresponding controller. Besides, with the state estimation provided by the finite-time state observer, the finite-time output feedback controller can guarantee the finite-time stability of the closed-loop system. The experimental results validate the effectiveness of the developed method on the trajectory tracking control of a robot manipulator.

The development of control approaches for systems preceded with hysteresis non-linearities has received great attentions in recent decades. The most common approach is the construction of an inverse model as the compensator to mitigate hysteresis effects. However, most of the developed schemes are state-based, requiring the availability of states of systems, which may not be the case for some practical systems. In this study, output control with inverse compensation will be addressed. By using the inverse as a feedforward compensator for the model described by the modified generalised Prandtl–Ishlinskii model, an corresponding analytical expression of the inverse compensation error is first obtained. Then, an observer-based robust adaptive output feedback controller is developed. It is shown that the proposed output feedback control scheme can not only guarantee the stability of the control systems, but also can achieve the desired tracking accuracy.

In this paper, we study stability and performance properties of linear fractional transformation (LFT) parameter-dependent systems using duality theory and tools from convex analysis. A pair of conjugate functions, the convex hull and the maximum of a family of quadratic functions, are used for analysis and synthesis of LFT systems. Sufficient synthesis conditions for both robust state feedback and gain-scheduling output feedback control problems are formulated as a set of linear matrix inequalities (LMIs) with linear search over scalar variables. Finally, a numerical example is used to demonstrate the advantages of the proposed approaches.