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Summary: This article develops a new framework of adaptive actuator failure compensation control for cooperative manipulator systems with parameter uncertainties in addition to actuator failures, and designs and analyzes effective actuator failure compensation schemes for such robotic systems. The new adaptive control design uses an integration of multiple individual failure compensators and direct adaptation to handle various types of uncertainties in such robotic systems. The design can also be used for concurrent actuator failure cases, to expand the capability of adaptive actuator failure compensation. With a complete proof and performance analysis, it is shown that the proposed control scheme guarantees the desired closed‐loop stability and asymptotic output tracking, despite actuator failures whose patterns, time instants and values are all unknown. Simulation results of a benchmark cooperative manipulator system are presented to verify the desired control performance of the system with both typical constant and square‐wave actuator failure signals. [ABSTRACT FROM AUTHOR]

Summary: In this article, adaptive compensation designs are developed for nonlinear systems with uncertainties from the system functions and persistent actuator failures of characterizations that (i) some unknown system inputs are stuck at some unknown fixed or varying values at unknown time instants and (ii) the failure pattern always switches from one to another and the switching does not stop. Such a controlled plant is described by an uncertain time‐varying nonlinear system, and some robust adaptive feedback linearization based failure compensation results are studied for closed‐loop system stabilization and bounded output tracking for some specific conditions. To improve the tracking performance in the presence of persistent actuator failures, a new adaptive control scheme is developed, using the failure indicator function which contains the failure pattern and failure time in the formulation. Detailed stability and tracking performance are shown. Simulation results are shown to verify the effectiveness of the proposed adaptive actuator failure compensation method. [ABSTRACT FROM AUTHOR]

Summary: This paper addresses a new adaptive output tracking problem in the presence of uncertain plant dynamics and uncertain sensor failures. A new unified nominal state‐feedback control law is developed to deal with various sensor failures, which is directly constructed by state sensor outputs. Such a new state‐feedback compensation control law is able to ensure the desired plant‐model matching properties under different failure patterns. Based on the nominal compensation control design, a new adaptive compensation control scheme is proposed, which guarantees closed‐loop signal boundedness and asymptotic output tracking. The new adaptive compensation scheme not only expands the sensor failures types that the system could tolerate but also avoids some signal processing procedures that the traditional fault‐tolerant control techniques are forced to encounter. A complete stability analysis and a representative simulation study are conducted to evaluate the effectiveness of the proposed adaptive compensation control scheme. [ABSTRACT FROM AUTHOR]

Summary: In this paper, an adaptive leader‐following consensus problem of multiagent systems with possibly persistent switching topology is solved. The control goal is to achieve state consensus of multiagent systems with switching topology in the presence of system parameter uncertainties. After introducing an indicator function, a new uniform nominal controller structure is developed to ensure consensus for multiagent systems with switching topology for the case of known system parameters, which provides the a priori knowledge for the adaptive control design. Then, an adaptive state consensus control scheme is developed for dealing with unknown dynamics of both the leader and the followers, for multiagent systems with switching topology. Complete stability and asymptotic state consensus analysis is shown to guarantee the desired consensus performance despite possibly persistent topology switches. A simulation study with several different cases is conducted to evaluate the effectiveness of the proposed adaptive consensus control scheme. [ABSTRACT FROM AUTHOR]

Adaptive control schemes are developed for uncertain multivariable systems with unmatched input disturbances and are applied to an aircraft flight turbulence compensation problem. Key relative degree conditions from system input and disturbance are derived in terms of system interactor matrices for the design of a nominal state or output feedback control law that ensures desired asymptotic output tracking and disturbance rejection. To deal with an uncertain system high-frequency gain matrix, a gain matrix decomposition technique is employed to parametrize an error system model in terms of the parameter and tracking errors, for the design of an adaptive parameter update law with reduced system knowledge. Both adaptive state and output feedback control schemes are presented in detail for systems with general interactor matrices, based on an LDS gain decomposition parametrization, and LDU and SDU decomposition-based designs are also discussed, to develop unified adaptive disturbance rejection techniques for multivariable systems. All closed-loop system signals are bounded, and the system output tracks a reference output asymptotically despite the system and disturbance parameter uncertainties. Simulation results of an aircraft flight control system with adaptive turbulence compensation are presented to show the desired system disturbance rejection performance. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

A new discrete-time actuator failure compensation control scheme is developed, using a multiple-model adaptive control approach which has the capacity to achieve faster and more accurate compensation of failure uncertainties. An individual adaptive system, for each possible failure pattern in a failure pattern set of interest for compensation, is designed using an indirect model reference adaptive control scheme for actuator failure compensation. A multiple-model control switching mechanism for discrete-time systems is set up by finding the minimal performance index to select the most appropriate control law. The performance indices are based on the adaptive estimation errors of individual parameterized systems with actuator failures. Simulation results from an aircraft flight control system example are presented to show the desired closed-loop system stability and tracking performance despite the presence of uncertain actuator failures. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY This paper develops an extended model reference adaptive control scheme to expand the capacity of state feedback state tracking adaptive control to handle the plant-model matching uncertainties for single-input LTI systems. The extended scheme is developed, using multiple reference model systems (only one of which is required to be able to match the controlled plant), and multiple controllers (which are updated from adaptive laws generated from multiple reference model systems based estimation errors), as two key features of such design to relax a plant-model matching condition. A switching mechanism is constructed using those multiple estimation errors, capable of selecting the suitable control input from the multiple control signals, to achieve the desired system performance. An aircraft flight control example is presented to show the capacity of such design in relaxing a practical design condition. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The goal of this special issue is to show the state-of-the-art in recent developments of advanced control methods using adaptive control and fault-tolerant control techniques to deal with uncertain system faults, for the recovery of desired control system performance. Control system resilience is the system's ability to accommodate its faults, disturbances, and uncertainties, to recover its desired performance. Control system resilience is the system's ability to accommodate its faults, disturbances, and uncertainties, to recover its desired performance. [Extracted from the article]

SUMMARY This paper addresses the problem of adaptive compensation of actuator nonlinearities with unknown parameters, for state feedback control of unknown multi-input multi-output (multivariable) linear time-invariant dynamic systems. A new controller parametrization is derived to deal with bilinear parameters that resulted from the two sets of the actuator nonlinearity parameters and the dynamic system parameters. To overcome the difficulty caused by a nondiagonal high-frequency gain matrix and a special actuator nonlinearity parameter structure, the new controller structure is parametrized on the basis of the high-frequency gain matrix LDU or SDU decomposition, leading to a linear parametrization coordinating the actuator nonlinearity parameters. The developed control scheme is a model reference adaptive control based design, employing an adaptive state feedback control law combined with an adaptive inverse, to deal with uncertain parameters in the system dynamics and actuator nonlinearities. To ensure the robustness with respect to actuator nonlinearity parametrization errors and the nonsingularity of the adaptive inverse, the parameter estimates are updated with an adaptive law using a combined switching- σ and parameter projection modification. An application is studied for adaptive aircraft flight control with synthetic jet actuators, which have nonlinear characteristics to be compensated. Simulation results show the desired adaptive control system performance.Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY This paper derives a new prediction model of the global discrete-time input-output multiple-delay Takagi-Sugeno (T-S) fuzzy systems with multiple delays and employs it for adaptive fuzzy control in the presence of system parameter uncertainties. On the basis of a model-based approach, a new system parametrization and adaptive control scheme are developed with detailed design procedure and complete stability analysis. The derived new fuzzy prediction model involves not only the current values of the membership functions but also their past values, expanding its capacity of approximating dynamic systems. A stable adaptive law is developed on the basis of an error model resulting from a new augmented parametric model for which a signal bounding property is also proved, crucial for closed-loop system stability. An illustrative example is presented to demonstrate the studied new concepts and to verify the desired performance of the new types of adaptive fuzzy control systems. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]