Reduced-order Observer-based Control Research Articles

Reduced-Order Observer-Based Adaptive Fuzzy Self-Triggered Control for Fractional Order Nonlinear Systems Without Feasibility Conditions

Reduced-Order Observer-Based Adaptive Fuzzy Self-Triggered Control for Fractional Order Nonlinear Systems Without Feasibility Conditions

Dead-Time Compensation Using ADALINE for Reduced-Order Observer-Based Sensorless SynRM Drives

The inverter dead time effect is non-negligible for the control performance of sensorless synchronous reluctance motor (SynRM) drives at low speeds. In this paper, a reduced-order observer-based sensorless control method for SynRM drives combined with the adaptive linear neurons (ADALINE)-based dead-time compensation is proposed. The reduced-order observer-based sensorless control method is presented, for which is parameter tuning is easy. On this basis, the dead-time compensation strategy using ADALINE filters is proposed to reduce the voltage harmonics effect on the estimation performance of the reduced-order observer. With ADALINE filters, the sixth current harmonic can be successfully filtered out by compensating the voltage directly or fitting the current to compensate the voltage. In this way, the low-speed estimation performance of the reduced-order observer is improved. The effectiveness of the proposed method is verified on a 3 kW SynRM experimental platform.

Reduced-Order Observer-Based LQR Controller Design for Rotary Inverted Pendulum

Reduced-Order Observer-Based LQR Controller Design for Rotary Inverted Pendulum

Reduced-Order Observer-Based Resilient Control for MASs With Time-Varying Delay Against DoS Attacks

Reduced-Order Observer-Based Resilient Control for MASs With Time-Varying Delay Against DoS Attacks

Reduced-Order Observer-Based Position Control of a Magnetic-Geared Servo Drive

Magnetic gears (MGs) emerged as an interesting alternative to conventional mechanical gears, owing mainly to their high torque densities and contactless operation. This paper presents a novel observer-based position control system for a magnetic-geared servo drive. The presented control system is based on two well established control strategies—field-oriented control (FOC) and state feedback control. The former is used to achieve effective torque control of a permanent magnet synchronous motor (PMSM) which is considered as an actuator that drives the high-speed rotor, whereas the latter is used to control the position of the low-speed rotor. A reduced-order extended state observer is used to estimate the position and speed of the low-speed rotor, thereby reducing the number of sensors required for the implementation of the controller. The whole control system is implemented on a microcontroller and tested on an existing prototype with a gear ratio of 18:1. The experimental results show that the presented control system guarantees precise positioning within a short amount of time and excellent disturbance rejection.

Dynamic Gain Reduced-Order Observer-Based Global Adaptive Neural-Network Tracking Control for Nonlinear Time-Delay Systems.

In this article, a globally adaptive neural-network tracking control strategy based on the dynamic gain observer is proposed for a class of uncertain output-feedback systems with unknown time-varying delays. A reduced-order observer with novel dynamic gain is proposed. An n th-order continuously differentiable switching function is constructed to achieve the continuous switching control of the system, thus further ensuring that all the closed-loop signals are globally uniformly ultimately bounded (GUUB). It is proved that by adjusting the designed parameters, the tracking error converges to a region which can be adjusted to be small enough. The effectiveness of the control scheme is demonstrated by two simulation examples.

Output synchronization of wide-area heterogeneous multi-agent systems over intermittent clustered networks

In this paper, the communication network associated with a linear heterogeneous clustered multi-agent system (CMAS) contains several clusters, each of which is modeled by a strongly connected digraph and contains a leader. Intra-cluster agents are in continuous communication with their intra-cluster neighbors during the communication period, whereas only the inter-cluster leaders can communicate with other leaders at a series of discrete moments, known as the reset time. Thus this paper presents a reduced-order observer-based reset output feedback controller that solves the output synchronization problem associated with the linear heterogeneous CMAS. Specifically, a reset internal model is built to solve the output synchronization for each agent, and a reset reduced-order observer is developed to estimate the unavailable states of each agent. Then an output feedback control strategy is developed using only the output information, internal model state, and observer state. Sufficient conditions are also obtained for ensuring the output synchronization of the CMAS. Finally, an illustrative example is provided to demonstrate the efficiency of the proposed control strategy.

Reduced-order observer-based fuzzy adaptive dynamic event-triggered consensus control for multi-agent systems with communication faults

Reduced-order observer-based fuzzy adaptive dynamic event-triggered consensus control for multi-agent systems with communication faults

Pole assignment and distributed output feedback control via graph-based decomposition

ABSTRACT A new distributed observer-based output feedback control design with an arbitrary control structure is proposed. Assuming that the linear time-invariant (LTI) system does not have any fixed-modes with respect to the control structure, the pole placement at the desired locations becomes theoretically feasible. In this paper, the structural output feedback controller design is transformed into equivalent problems based on a graph-theoretic approach. Two augmented structures are established and formulated as the solution of a set of binary linear programs (BLP). The first one facilitates the incorporation of the maximum number of edges in the principal bipartite graph and the second one results in the least order of dynamic control for the principal block. Next, the distributed design problem is segmented into two stages: (i) design of a set of static control loops based on convex optimisation, to maximise the controllability/observability radius and (ii) design of the control loops corresponding to the principal bipartite graph based on the reduced-order observer-based control. The performance of the proposed approach is investigated in terms of the pole-placement accuracy, control effort, robustness to perturbations in system dynamics, and effect of controller order reduction.

Bipartite consensus of multi-agent systems with reduced-order observer-based distributed control protocols

This paper considers the bipartite consensus problem for multi-agent systems, in which both bipartite leaderless consensus and bipartite tracking problems are investigated under signed digraph. Two distributed output feedback control laws are proposed based on reduced-order observer design, respectively, for solving the bipartite leaderless consensus and bipartite tracking consensus problems. Some sufficient conditions are obtained for achieving the bipartite consensus of the multi-agent systems, by using the algebraic Riccati equation design and Jordan decomposition technique. Finally, two simulation examples are presented to illustrate the effectiveness of the obtained theoretical results.

Output feedback containment control of multi-agent systems with semi-Markovian switching topologies and input-bounded leaders

This paper investigates the containment control problem of multi-agent systems with semi-Markovian switching topologies. Different from the related works, this paper considers a more general case that the control inputs of leaders are nonzero, the sojourn time distributions of the semi-Markovian switching topologies are mode transition-dependent, and the states of agents are not measurable. Reduced-order observer-based control protocols are proposed, respectively, for two cases that the transition rates are completely known and partially unknown, which ensures that the containment of the multi-agent systems can be achieved in the mean square sense. Finally, simulation examples are given to illustrate the validity of the theoretical results.

Reduced-order observer-based consensus control of linear multi-agent systems over directed networks with nonuniform communication delays

This paper considers a consensus control of a general linear multi-agent system with time-varying communication delays. Since each agent can only use the relative output information from its neighbors, a reduced-order observer-based control protocol is proposed to guarantee consensus on the directed communication network. The stability of the closed-loop system is analyzed for the cases with uniform delays and nonuniform time-varying delays, respectively. Moreover, the upper bounds of the communication delays are obtained respectively for the two cases. Finally, two numerical examples are provided to illustrate the proposed theoretical results.

Reduced-Order Observer-Based Dynamic Event-Triggered Adaptive NN Control for Stochastic Nonlinear Systems Subject to Unknown Input Saturation.

In this article, a dynamic event-triggered control scheme for a class of stochastic nonlinear systems with unknown input saturation and partially unmeasured states is presented. First, a dynamic event-triggered mechanism (DEM) is designed to reduce some unnecessary transmissions from controller to actuator so as to achieve better resource efficiency. Unlike most existing event-triggered mechanisms, in which the threshold parameters are always fixed, the threshold parameter in the developed event-triggered condition is dynamically adjusted according to a dynamic rule. Second, an improved neural network that considers the reconstructed error is introduced to approximate the unknown nonlinear terms existed in the considered systems. Third, an auxiliary system with the same order as the considered system is constructed to deal with the influence of asymmetric input saturation, which is distinct from most existing methods for nonlinear systems with input saturation. Assuming that the partial state is unavailable in the system, a reduced-order observer is presented to estimate them. Furthermore, it is theoretically proven that the obtained control scheme can achieve the desired objects. Finally, a one-link manipulator system and a three-degree-of-freedom ship maneuvering system are presented to illustrate the effectiveness of the proposed control method.

H∞ reduced-order observer-based controller synthesis approach for T-S fuzzy systems

For continuous-time nonlinear systems represented by Takagi–Sugeno fuzzy models, a new H∞ reduced-order-observer based controller synthesis structure is investigated in this paper. By the fuzzy reduced-order observer and fuzzy controller, an augmented error system composed of the estimation and control errors is obtained. The fuzzy modeling residual terms are seen as part of the external disturbance, and an extra design matrix is added to facilitate the design process. The robustness and stability conditions are given based on Lyapunov function approach, then the conditions are transformed into convex form to facilitate the numerical solving process. Finally, by the comparison with existing methods in simulation section, the control performance and conservativeness reduction effects of the proposed methods are verified.

New Designs of Reduced-Order Observer-Based Controllers for Singularly Perturbed Linear Systems

The slow and fast reduced-order observers and reduced-order observer-based controllers are designed by using the two-stage feedback design technique for slow and fast subsystems. The new designs produce an arbitrary order of accuracy, while the previously known designs produce the accuracy of O(ϵ) only where ϵ is a small singular perturbation parameter. Several cases of reduced-order observer designs are considered depending on the measured state space variables: only all slow variables are measured, only all fast variables are measured, and some combinations of the slow and fast variables are measured. Since the two-stage methods have been used to overcome the numerical ill-conditioning problem for Cases (III)–(V), they have similar procedures. The numerical ill-conditioning problem is avoided so that independent feedback controllers can be applied to each subsystem. The design allows complete time-scale separation for both the reduced-order observer and controller through the complete and exact decomposition into slow and fast time scales. This method reduces both offline and online computations.

Nonlinear Reduced-Order Observer-Based Predictive Control for Diving of an Autonomous Underwater Vehicle

The attitude control and depth tracking issue of autonomous underwater vehicle (AUV) are addressed in this paper. By introducing a nonsingular coordinate transformation, a novel nonlinear reduced-order observer (NROO) is presented to achieve an accurate estimation of AUV’s state variables. A discrete-time model predictive control with nonlinear model online linearization (MPC-NMOL) is applied to enhance the attitude control and depth tracking performance of AUV considering the wave disturbance near surface. In AUV longitudinal control simulation, the comparisons have been presented between NROO and full-order observer (FOO) and also between MPC-NMOL and traditional NMPC. Simulation results show the effectiveness of the proposed method.

Dynamic Modeling and Observer-based Servomechanism Control of a Towing Rope System

This paper presents a control-oriented dynamical model of a towing rope system with variable-length. In this system, a winch driven by a motor's torque uses the towing rope to pull a cart. In general, it is a difficult and complicated process to obtain an accurate mathematical model for this system. In particular, if the rope length is varied by operating the winch, the varying rope dynamics needs to be considered, and the key physical parameters need to be re-identified... However, real time parameter identification requires long computation time for the control scheme, and hence undesirable control performance. Therefore, in this article, the rope is modeled as a straight massless segment, with the mass of rope being considered partly with that of the cart, and partly as halfway to the winch. In addition, the changing spring constant and damping constant of the towing rope are accounted for as part of the dynamics of the winch. Finally, a reduced-order observer-based servomechanism controller is designed for the system, and the performance is evaluated by computer simulation.

Observer-based output feedback control of discrete-time linear systems with input and output delays

In this paper, we study observer-based output feedback control of discrete-time linear systems with both multiple input and output delays. By generalising our recently developed truncated predictor feedback approach for state feedback stabilisation of discrete-time time-delay systems to the design of observer-based output feedback, two types of observer-based output feedback controllers, one being memory and the other memoryless, are constructed. Both full-order and reduced-order observer-based controllers are established in both the memory and memoryless schemes. It is shown that the separation principle holds for the memory observer-based output feedback controllers, but does not hold for the memoryless ones. We further show that the proposed observer-based output feedback controllers solve both the l2 and l∞ semi-global stabilisation problems. A numerical example is given to illustrate the effectiveness of the proposed approaches.

Distributed Reduced-order Observer-based Consensus Control of Discrete-time Linear Multi-agent Systems

Abstract This paper proposes a distributed reduced-order observer-based control protocol to address the consensus problem of discrete-time linear multi-agent system. By solving modified discrete-time algebraic Riccati equation and using a multi-step algorithm, we design proper gain matrix and gain coefficient used in the protocol. By constructing a parameter-dependent common Lyapunov function, it is proved that under suitable conditions on communication, the multi-agent system will reach consensus under directed fixed topology no matter with a leader or without. Finally, a simulation example is provided to show the effectiveness of our result.

ACTIVE VIBRATION CONTROL OF SEISMICALLY EXCITED STRUCTURES BY ATMDS: STABILITY AND PERFORMANCE ROBUSTNESS PERSPECTIVE

This paper demonstrates the trade-off between nominal performance and robustness in intelligent and conventional structural vibration control schemes; and, proposes a systematic treatment of stability robustness and performance robustness against uncertainty due to structural damage. The adopted control strategies include an intelligent genetic fuzzy logic controller (GFLC) and reduced-order observer-based (ROOB) controllers based on pole-placement and linear quadratic regulator (LQR) conventional schemes. These control strategies are applied to a seismically excited truss bridge structure through an active tuned mass damper (ATMD). Response of the bridge-ATMD control system to earthquake excitation records under nominal and uncertain conditions is analyzed via simulation tests. Based on these results, advantages of exploiting heuristic intelligence in seismic vibration control, as well as some complexities arising in realistic conventional control are highlighted. It has been shown that the coupled effect of spill-over (due to reduction and observation) and mismatch between the mathematical model and the actual plant (due to uncertainty and modeling errors) can destabilize the conventional closed-loop system even if each is alone tolerated. Accordingly, the GFLC proves itself to be the dominant design in terms of the compromise between performance and robustness.