Analysis and design of output feedback control systems with actuator saturation

A dynamic output feedback controller design approach based on cone complementary linearisation procedure is proposed for linear time-invariant （LTI） systems with actuator saturation. First, the estimation of the domain of attraction is given. Then, a design method to find a larger estimation of the domain of attraction is presented. In the process of design, nonconvex conditions are obtained, so a cone complementary linearisation procedure is exploited to solve the nonconvex feasibility problem. Two examples are given to illustrate the efficiency of the design method.     

Optimal control of nonlinear systems: a predictive control approach

A new nonlinear predictive control law for a class of multivariable nonlinear systems is presented in this paper. It is shown that the closed-loop dynamics under this nonlinear predictive controller explicitly depend on design parameters (prediction time and control order). The main features of this result are that an explicitly analytical form of the optimal predictive controller is given, on-line optimisation is not required, stability of the closed-loop system is guaranteed, the whole design procedure is transparent to designers and the resultant controller is easy to implement. By establishing the relationship between the design parameters and time-domain transient, it is shown that the design of an optimal generalised predictive controller to achieve desired time-domain specifications for nonlinear systems can be performed by looking up tables. The design procedure is illustrated by designing an autopilot for a missile.     

Approximate Feedback Linearisation Using Multilayer Neural Networks

In this paper we introduce the approximate feedback linearisation using multilayer feedforward neural networks. We propose to approximate a basis of the one-dimensional codistribution of an affine nonlinear system with the derivative of a multilayer neural network [6] and form a change of coordinates with n multilayer neural networks [5]. In this paper we will prove that the transformation can define a local diffeomorphism, with which a local stabilising feedback law can be designed for a kind of non-linearisable nonlinear systems.     

Global satisfactory control for nonlinear integrator processes with long delay

Integrator processes with long delay are difficult to control. Nonlinear characteristics of actuators make the control problem more challenging. A technique is proposed in this paper for global satisfactory control （GSC） of such processes with relay-type nonlinearity. An oscillatory control signal is injected into the nonlinear process; the amplitude and frequency of the oscillatory signal are designed to linearise the nonlinear process in the sense of harmonic analysis; and a state feedback controller is configured to implement GSC over the linearised process. An illustrative example is given to demonstrate the effectiveness of     

Robust input–output linearisation using uncertainty and disturbance estimation

This article proposes a new approach to robustify an input–output linearisation controller. The robustification is achieved by estimating the uncertainties and external unmeasurable disturbances using a novel uncertainty and disturbance estimator. A significant feature of the proposed approach is that it does not need any information about the uncertainties. The stability of the system and the estimator is established. Effectiveness of the proposed approach is demonstrated through application to the wing rock motion control problem.     

Asymptotic perturbed feedback linearisation of underactuated Euler's dynamics

A unifying methodology is introduced for smooth asymptotic stabilisation of underactuated rigid body dynamics under one and two degrees of actuation. The methodology is based on the concept of generalised inversion, and it aims to realise a perturbation from the unrealisable feedback linearising transformation. A desired linear dynamics in a norm measure of the angular velocity components about the unactuated axes is evaluated along solution trajectories of Euler's underactuated dynamical equations resulting in a linear relation in the control variables. This relation is used to assess asymptotic stabilisability of underactuated rigid bodies with arbitrary values of inertia parameters, and generalised inversion of the relation produces a control law that consists of particular and auxiliary parts. The generalised inverse in the particular part is scaled by a dynamic factor such that it uniformly converges to the Moore–Penrose inverse, and the null-control vector in the auxiliary part is chosen for asymptotically stable perturbed feedback linearisation of the underactuated system.     

Strict feedforward control systems,linearisability, and convergent normal forms

This article discusses the feedback equivalence of multi-inputs feedforward control systems via smooth (resp. analytic) feedback transformations. We first address the state (resp. feedback) linearisation problem, and provide easily computable algorithms that yield explicit state (resp. feedback) linearising coordinates for systems in strict feedforward form. The application of the algorithms does not require checking the commutativity (resp. involutivity) of the distributions associated with the system, and the algorithms fail after few steps if the system is not linearisable. In the latter case, the algorithms are extended to provide coordinate systems bringing the system into a normal form which is a smooth (resp. analytic) counterpart of Kang's formal normal form. Illustrative examples for both the linearisation and convergent normal form include the vertical take off and landing aircraft, the multi-vehicle wireless testbed among others.     

The eXogenous Kalman Filter (XKF)

It is well known that the time-varying Kalman Filter (KF) is globally exponentially stable and optimal in the sense of minimum variance under some conditions. However, nonlinear approximations such as the extended KF linearises the system about the estimated state trajectories, leading in general to loss of both global stability and optimality. Nonlinear observers tend to have strong, often global, stability properties. They are, however, often designed without optimality objectives considering the presence of unknown measurement errors and process disturbances. We study the cascade of a global nonlinear observer with the linearised KF, where the estimate from the nonlinear observer is an exogenous signal only used for generating a linearised model to the KF. It is shown that the two-stage nonlinear estimator inherits the global stability property of the nonlinear observer, and simulations indicate that local optimality properties similar to a perfectly linearised KF can be achieved. This two-stage estimator is called an eXogeneous KF (XKF).     

Robust backstepping control of an interlink converter in a hybrid AC/DC microgrid based on feedback linearisation method

This paper presents a robust dc-link voltage as well as a current control strategy for a bidirectional interlink converter (BIC) in a hybrid ac/dc microgrid. To enhance the dc-bus voltage control, conventional methods strive to measure and feedforward the load or source power in the dc-bus control scheme. However, the conventional feedforward-based approaches require remote measurement with communications. Moreover, conventional methods suffer from stability and performance issues, mainly due to the use of the small-signal-based control design method. To overcome these issues, in this paper, the power from DG units of the dc subgrid imposed on the BIC is considered an unmeasurable disturbance signal. In the proposed method, in contrast to existing methods, using the nonlinear model of BIC, a robust controller that does not need the remote measurement with communications effectively rejects the impact of the disturbance signal imposed on the BIC's dc-link voltage. To avoid communication links, the robust controller has a plug-and-play feature that makes it possible to add a DG/load to or remove it from the dc subgrid without distorting the hybrid microgrid stability. Finally, Monte Carlo simulations are conducted to confirm the effectiveness of the proposed control strategy in MATLAB/SimPowerSystems software environment.     

Linearisation of asymmetrical Doherty amplifier by the even-order non-linear signals

This paper considers the linearisation of an asymmetrical two-way Doherty amplifier by the method that uses the second harmonics and fourth-order non-linear signals for linearisation. These even-order signals for linearisation are extracted at the output of the peaking amplifier, adjusted in amplitude and phase and injected at the input and output of the carrier amplifier transistor in the Doherty configuration. The effect of linearisation has been experimentally confirmed on a fabricated asymmetrical Doherty amplifier with the additional circuit for linearisation. The suppression of the third-order intermodulation products has been carried out for two-tone test, 64QAM and WCDMA digitally modulated signals in a range of signal power.