A Robust Tracking Method for MIMO Uncertain Discrete-Time Systems: Mechatronic Applications

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Majorant-Based Control Methodology for Mechatronic and Transportation Processes

This paper provides a unified approach via majorant systems, which allows one to easily design a family of robust, smooth and effective control laws of proportional - h order integral - k order derivative (PIhDk) -type for broad classes of uncertain nonlinear multi-input multi-output (MIMO) systems, including mechatronic and transportation processes with ideal or real actuators, subject to bounded disturbances and measurement errors. The proposed control laws are simple to design and implement and are used, acting on a single design parameter, to track a sufficiently smooth but generic reference signal, yielding a tracking error norm less than a prescribed value, with a good transient phase and feasible control signals, despite the presence of disturbances, parametric and structural uncertainties, measurement errors, and in case of real actuators and amplifiers. Moreover, some guidelines to easily design the proposed controllers are given. Finally, the stated unified methodology and various performance comparisons are illustrated and validated in two case studies

Majorant-Based Control Methodology for Mechatronic and Transportation Processes

This paper provides a unified approach via majorant systems, which allows one to easily design a family of robust, smooth and effective control laws of proportional - h order integral - k order derivative (PI_{h} D_{k}) -type for broad classes of uncertain nonlinear multi-input multi-output (MIMO) systems, including mechatronic and transportation processes with ideal or real actuators, subject to bounded disturbances and measurement errors. The proposed control laws are simple to design and implement and are used, acting on a single design parameter, to track a sufficiently smooth but generic reference signal, yielding a tracking error norm less than a prescribed value, with a good transient phase and feasible control signals, despite the presence of disturbances, parametric and structural uncertainties, measurement errors, and in case of real actuators and amplifiers. Moreover, some guidelines to easily design the proposed controllers are given. Finally, the stated unified methodology and various performance comparisons are illustrated and validated in two case studies

On filtering over Îto-Volterra observations

In this paper, the Kalman-Bucy filter is designed for an Îto-Volterra process over Ito-Volterra observations that cannot be reduced to the case of a differential observation equation. The Kalman-Bucy filter is then designed for an Ito-Volterra process over discontinuous Ito-Volterra observations. Based on the obtained results, the filtering problem over discrete observations with delays is solved. Proofs of the theorems substantiating the filtering algorithms are given

Comprehensive approach to design robust tracking controllers for mechatronic processes

This paper presents a comprehensive approach, which allows one to design in a unified way robust smooth proportional-integral-derivative (PID) or proportional-second order derivative (PD2)-type control laws for broad classes of uncertain nonlinear multi-input multi-output (MIMO) systems, including mechatronic and transportation ones, subject to bounded disturbances and noises. The proposed controllers are used to track a reference signal with a bounded third derivative, yielding a tracking error norm less than a prescribed value. The proposed control laws are simple to design and implement and have various engineering applications. Two cases studies are considered: the first one concerns mechatronic processes, and the second one deals with a transportation/assembling robot

Optimal Estimator Design for LTI Systems with Bounded Noises, Disturbances, and Nonlinearities

This paper presents a new estimation technique for linear time-invariant (LTI) systems with bounded additional nonlinearities and/or disturbances, measurement noises, and initial states. A new direct methodology is developed to design an estimator optimizing the maximum estimation error of the system state or its linear function in a prefixed time interval. For some mechanical systems, both the parameters of the optimal estimator and the related maximum estimation error in a closed form are provided. The proposed method is illustrated through four simulation and experimental examples