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In this paper, we propose two adaptive control schemes to solve the output tracking control problem of a class of uncertain switched nonlinear systems. The first is a robust scheme constructed based on common Lyapunov function method, aiming to achieve the insensitivity of closed-loop system to parameter switches by estimating the bound on switching parameters. It is analyzed that the system stability under arbitrary switching is established with such a scheme, but the control input required may be relatively large since the estimate of the bound on switching parameters is utilized. To avoid this, we further propose a direct adaptive control scheme by estimating the switching parameters directly, and derive a dwell-time condition for parameter switches based on an extended multiple Lyapunov functions method newly developed, such that the global boundedness of all the closed-loop signals and the convergence of tracking error to a residual around zero are ensured. The effectiveness of the proposed control schemes is illustrated through simulation studies. [ABSTRACT FROM AUTHOR]

This paper studies a class of robust cooperative learning control problems for directed networks of agents (a) with nonidentical nonlinear dynamics that do not satisfy a global Lipschitz condition and (b) in the presence of switching topologies, initial state shifts and external disturbances. All uncertainties are not only time-varying but also iteration-varying. It is shown that the relative formation of nonlinear agents achieved via cooperative learning can be guaranteed to converge to the desired formation exponentially fast as the number of iterations increases. A necessary and sufficient condition for exponential convergence of the cooperative learning process is that at each time step, the network topology graph of nonlinear agents can be rendered quasi-strongly connected through switching along the iteration axis. Simulation tests illustrate the effectiveness of our proposed cooperative learning results in refining arbitrary high precision relative formation of nonlinear agents. [ABSTRACT FROM AUTHOR]

This paper presents a data-driven receding horizon fault estimation method for additive actuator and sensor faults in unknown linear time-invariant systems, with enhanced robustness to stochastic identification errors. State-of-the-art methods construct fault estimators with identified state-space models or Markov parameters, without compensating for identification errors. Motivated by this limitation, we first propose a receding horizon fault estimator parameterized by predictor Markov parameters. This estimator provides (asymptotically) unbiased fault estimates as long as the subsystem from faults to outputs has no unstable transmission zeros. When the identified Markov parameters are used to construct the above fault estimator, stochastic identification errors appear as model uncertainty multiplied with unknown fault signals and online system inputs/outputs (I/O). Based on this fault estimation error analysis, we formulate a mixed-norm problem for the offline robust design that regards online I/O data as unknown. An alternative online mixed-norm problem is also proposed that can further reduce estimation errors at the cost of increased computational burden. Based on a geometrical interpretation of the two proposed mixed-norm problems, systematic methods to tune the user-defined parameters therein are given to achieve desired performance trade-offs. Simulation examples illustrate the benefits of our proposed methods compared to recent literature. [ABSTRACT FROM AUTHOR]

The problem of fault-tolerant attitude tracking control for an over-actuated spacecraft in the presence of actuator faults/failures and external disturbances is addressed in this paper. Assuming that information on the inertia and bounds on the disturbances are unknown, a novel fault-tolerant control (FTC) law incorporating on-line control allocation (CA) is developed to handle actuator faults/failures. To improve the robustness of the adaptive law and stop the adaptive gain from increasing, the time-varying dead-zone modification technique is employed in parameter adaptations. It is shown that uniform ultimate boundedness of the tracking errors can be ensured. To illustrate the efficiency of the CA-based FTC strategy, numerical simulations are carried out for a rigid spacecraft under actuator faults and failures. [ABSTRACT FROM AUTHOR]

Quasi-linear feedback theory (Kelemen, 2002; Kelemen and Bensoussan, 2004) enabled simultaneously improving time performance and frequency performance of feedback systems, by using compensators whose poles are gain dependent. Although simulation results show theoretical improvements, the gain magnitude of quasi-linear compensators is prohibitive. This paper intends to present a different quasi-linear controller (Bensoussan, 2011) that achieves simultaneous time and frequency optimization: The design is based on gain considerations in order to propose a framework within which phase circuits can be used in order to affect essentially the time response. A practical design methodology is outlined. [ABSTRACT FROM AUTHOR]

A novel two step adaptive identification framework is proposed for sinusoidal signals to estimate the unknown offset, amplitude, frequency and phase, where only the output measurements are used. After representing the sinusoidal signal as a linearly parameterized form, several adaptive laws are developed. The proposed adaptive laws are driven by parameter estimation error information that is derived by applying filter operations on the output measurements, so that globally exponential convergence of the parameter estimation is proved. By using the sliding mode technique, we further improve the design of adaptations to achieve finite-time (FT) parameter estimation. The proposed approaches are independent of any observer/predictor design and robust to bounded measurement noises. The developed estimation methods are finally extended to the full parameter estimation of multi-sinusoids with only output measurements. Comparative simulation results are provided to illustrate the efficacy of the proposed methods. [ABSTRACT FROM AUTHOR]

This paper proposes a robust tube-based model predictive control for polytopic linear parameter varying systems subject to bounded additive disturbances. In the proposed method, the future scheduling evolutions are described by a known nominal trajectory and some constant uncertainty sets around the nominal signals. Then, by using the notion of polar dual set, a cross-section varying tube parameterization is constructed to robustly satisfy the state and control constraints. Additionally, in contrast to the classical robust MPC problems with a priory known and fixed disturbance set, the shape and size of the additive disturbance set is maximized online through the MPC optimization problem. Therefore, at each time step, the control sequence and the largest allowable disturbance set can be computed simultaneously by solving a single constrained optimal control problem. Numerical simulation demonstrates the efficacy of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper investigates the tracking control problem of multi-input and multi-output nonlinear systems simultaneously considering the user-specified tracking performance, the asymmetric input saturation, and external disturbances. By introducing the modification signals into the user-specified performance functions, we propose a flexible performance-based control scheme, featuring the capability of avoiding the violation of the resulted modified performance functions (MPFs) due to the input saturation. These modification signals are associated with input saturation errors (the errors between the actual and desired control inputs) and generated by a novel auxiliary system in which all the states are guaranteed to be nonnegative. Consequently, the MPF can degrade the user-specified tracking performance when saturation happens and can recover it when no saturation occurs. Furthermore, the disturbance observer is utilized to estimate external disturbances and relieve the burden on the selection of control gains. With the developed control scheme, it is theoretically shown that the output can always track the reference signal and satisfy the constraints of the MPFs. Finally, the numerical simulation results are presented to show the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]