Consensus of high-order linear systems using dynamic output feedback compensator: Low gain approach

In this paper, we study the consensus (and synchronization) problem for multi-agent linear dynamic systems. All the agents have identical MIMO linear dynamics which can be of any order, and only the output information of each agents is delivered throughout the communication network. It is shown that consensus is reached if there exists a stable compensator which simultaneously stabilizes N−1 systems in a special form, where N is the number of agents. We show that there exists such a compensator under a very general condition. Finally, the consensus value is characterized as a function of initial conditions with stable compensators in place.     

High-gain output-feedback control for nonlinear systems based on multiple time scaling

We consider a general high-gain scaling technique for global control of strict-feedback-like systems. Unlike previous results, the scaling utilizes arbitrary powers (instead of requiring successive powers) of the high-gain parameter with the powers chosen to satisfy certain inequalities depending on system nonlinearities. The scaling induces a weak-cascading upper diagonal dominance (w-CUDD) structure on the dynamics. The analysis is based on our recent results on the w-CUDD property and uniform solvability of coupled state-dependent Lyapunov inequalities. The application of the general scaling technique to the design of a high-gain observer enables relaxation of the assumption in our earlier papers on cascading dominance of upper diagonal terms. The high-gain observer is coupled with a backstepping-based controller to obtain robust global stabilization in the presence of uncertainties that are incrementally linearly bounded in unmeasured states.     

Linear output feedback with dynamic high gain for nonlinear systems

We propose a linear output feedback with dynamic high gain for global regulation of a class of nonlinear systems. The uncertain nonlinearities are assumed to be bounded by a polynomial function of the output multiplied by unmeasured states. The crucial point made in this paper is that a linear observer-based output feedback can globally regulate an equilibrium of strongly nonlinear systems, provided that a single high gain is appropriately tuned.     

On pole assignment of linear systems by gain output feedback

In this paper, the Geometric Approach is used to derive in a straightforward way a sufficient condition for pole assignability by gain output feedback. This result leads to a pole assignment procedure which reduces to solving a system of min (n - m, n - p) polynomial equations where n is the number of states, m the number of inputs, p the number of outputs. In the case where m + p > n, this system clearly appears to be linear. The degrees of freedom related to the pole assignment problem are expressed in terms of (right or left) eigenvectors.     

Contraction-based stabilisation of nonlinear singularly perturbed systems and application to high gain feedback

Recent development of contraction theory-based analysis has opened the door for inspecting differential behaviour of singularly perturbed systems. In this paper, a contraction theory-based framework is proposed for stabilisation of singularly perturbed systems. The primary objective is to design a feedback controller to achieve bounded tracking error for both standard and non-standard singularly perturbed systems. This framework provides relaxation over traditional quadratic Lyapunov-based method as there is no need to satisfy interconnection conditions during controller design algorithm. Moreover, the stability bound does not depend on smallness of singularly perturbed parameter and robust to additive bounded uncertainties. Combined with high gain scaling, the proposed technique is shown to assure contraction of approximate feedback linearisable systems. These findings extend the class of nonlinear systems which can be made contracting.     

A note on stability, robustness and performance of output feedback nonlinear model predictive control

In recent years, nonlinear model predictive control (NMPC) schemes have been derived that guarantee stability of the closed loop under the assumption of full state information. However, only limited advances have been made with respect to output feedback in the framework of nonlinear predictive control. This paper combines stabilizing instantaneous state feedback NMPC schemes with high-gain observers to achieve output feedback stabilization. For a uniformly observable MIMO system class it is shown that the resulting closed loop is asymptotically stable. Furthermore, the output feedback NMPC scheme recovers the performance of the state feedback in the sense that the region of attraction and the trajectories of the state feedback scheme can be recovered to any degree of accuracy for large enough observer gains, thus leading to semi-regional results. Additionally, it is shown that the output feedback controller is robust with respect to static sector bounded nonlinear input uncertainties.     

Output feedback control of sensorless photovoltaic systems,with maximum power point tracking

This paper presents an output feedback control of sensorless photovoltaic systems with maximum power point tracking (MPPT). The system consists of a Photovoltaic Generator (PVG) which supplies a DC centrifugal pump, via a DC/DC boost converter. This later being connected to the PVG by a long PV cable. Generally, PV systems are established near the control unit of the converter. The MPPT methods and control laws are based on the PVG voltage and current measurements. However, PV arrays must be located in a site that guarantees good solar radiation. In most cases, such a site is at great distance from the control unit. Thus, on the one hand, the PVG voltage and current measurements become difficult and, on the other hand, the PV cable parameters could significantly effect the MPPT control accuracy if only voltage and current measurements in the cable converter side are used. To overcome these issues, a state estimation for PV systems is considered in this paper. A high gain observer is designed on the basis of a PV system model that accounts for PV cable parameters. It provides estimates of PVG output voltage and current using only current and voltage measurements in the converter side of the cable. A backstepping controller is then synthesized with the view of ensuring the MPPT objective. The output feedback control convergence is formally analyzed and its performances are illustrated by simulation.     

Output feedback control of large-scale nonlinear time-delay systems in lower triangular form

This paper is concerned with the stabilization problem for a class of large-scale nonlinear time-delay systems in lower triangular form. The uncertain nonlinearities are assumed to be bounded by continuous functions of the outputs or delayed outputs multiplied by unmeasured states or delayed states. An observer based output feedback control scheme is proposed using the dynamic gain control design approach. Based on Lyapunov stability theory, global asymptotic stability of the closed-loop control system is proved. Contrary to many existing control designs for lower triangular nonlinear systems, the celebrated backstepping method is not utilized here. An example is finally given to demonstrate the effectiveness of the proposed design procedure.     

Output feedback control of hypersonic vehicles based on neural network and high gain observer

In this paper,the output feedback control problem for a genetic hypersonic vehicle is considered under the restriction that only the vehicle's velocity and altitude are measurable. High gain observers (HGO) are utilized to provide estimation signals for unmeasurable derivatives of the vehicle's velocity and altitude. Neural network based feedforward function is designed to compensate for model uncertainties. The proposed control design require less knowledge of the hypersonic vehicle's dynamic model. A comp...     

On multivariable stability in the gain space

General existence conditions under which the stability of the individual loops of a multivariable system in a given compact and bounded gain space imply the global asymptotic stability of the multivariable system in the same space are very useful in practice and essentially indicate when in principle it is possible to obtain stable closed-loop performance of a multivariable system by tuning every loop separately. Such conditions are particularly useful for fault tolerant control of multivariable systems. This paper gives the required necessary and sufficient conditions and effectively unifies all previous work on diagonal stabilizability which includes as special cases: the diagonal dominance, the H matrix, the GKK matrix and the decentralized integral controllability (DIC) conditions reported previously in the literature. Some application examples are included.