The paper extends the concept of universal motion controller (UMC), by introducing an adaptive mechanism in the original form. The adaptive universal motion controller (AUMC) allows superior position tracking in free motion by allowing better utilization of available control resources. AUMC, as well as UMC, allows concurrent position and force control with a single control structure. Thus, it can be used for trajectory tracking in free motion and also for the interaction force control. This control strategy is of essential importance for the growing field of human-robot interaction (HRI) applications.
This paper presents unified force and position control based on sliding mode control (SMC) for a series elastic actuator (SEA). Compliant motion of robotic systems is crucial when dealing with unstructured environments as in the case of physical human-robot interaction. Therefore, not only traditional mechanical systems with stiff joints but also mechanically compliant systems such as SEAs have been actively studied. In order to accomplish versatile tasks, the strategy enabling both position control and force control is favorable. In this paper, the controller synthesizing position and force controllers on the basis of SMC for the control problem of SEAs is proposed by extending our previous work. Simulation results demonstrate the feasibility of the proposed method.
This paper presents a combination of two methods that can be effectively combined for control of electrical machines. The first method enables real-time identification of electrical and mechanical parameters based on differential geometry and geometric algebra. The second method enables robust control of electrical machines, even when the knowledge about parameters is incomplete. In combination, the two methods open a path for successful control of electrical machines with unknown and/or time varying parameters.
The paper discusses a control strategy that merges position and force control into a single control structure. The structure, denoted as the universal motion controller in our previous work, can be utilized to build a smart actuating system that runs a mechanical system with $n$ degrees of freedom. A smart actuating system has an integrated controller and it can be used in plug-and-play fashion for different trajectory tracking and force control tasks, defined either in configuration space, or in the task space. The only input of the actuating system is the attraction force in configuration space. Based on the attraction force, the smart actuating system is capable of imposing input forces to the mechanical system that will ensure execution of a specified task.
This paper presents a comprehensive treatment of the complex motion control systems in the the Sliding Mode Control (SMC) framework. The single and multi degrees of freedom (DOF) plants and applications to haptics and functionally related systems are discussed. The paper concentrates on presenting the designs that are easy to apply and tune. The proposed algorithms are based on the application of the equivalent control observer and the convergence term that guaranty stability of the closed loop in a Lyapunov sense and enforces the sliding mode on selected manifolds. Presented SMC design leads to a solution that easily could be modified to include majority of the algorithms presented in the literature.
This paper presents a comprehensive treatment of the complex motion control systems in the the Sliding Mode Control (SMC) framework. The single and multi degrees of freedom (DOF) plants and applications to haptics and functionally related systems are discussed. The paper concentrates on presenting the designs that are easy to apply and tune. The proposed algorithms are based on the application of the equivalent control observer and the convergence term that guaranty stability of the closed loop in a Lyapunov sense and enforces the sliding mode on selected manifolds. Presented SMC design leads to a solution that easily could be modified to include majority of the algorithms presented in the literature.
The paper presents a concept of universal motion controller. The controller merges both position and force control into a single control structure. Therefore, it gives a possibility to use the same control algorithm, both for position tracking tasks as well as for the interaction force control. The universal motion controller can be used not only to make the interaction force track its reference, but also for the limiting of the interaction force, so that safety is ensured. This makes it very useful for human-robot interaction applications.
This paper introduces a novel control approach for Doubly-Fed Induction Generator (DFIG) operating in island mode based on the cascaded control structure with disturbance estimation. The control of the DFIG is a challenging task due to its inherent nonlinearity, fast dynamics, and unpredictable disturbances acting on the system. The proposed control structure involves a nominal controller for plant and disturbance observer (DOB) in each of the inner and outer control loop. The first-order disturbance observers are designed to estimate the time-varying and unknown disturbances. With disturbance estimation, the nominal linear dynamics is obtained in both loops. This enables the same approach for designing controllers for the inner and outer loop which significantly simplifies implementation. The controllers are designed based on the demanded error dynamics and ensure stable operation of the system, while proposed DOBs estimate disturbances including external load. Finally, the effectiveness and quality of the proposed control structure were verified through numerical simulations in terms of external disturbances rejection and closed-loop tracking performance.
The paper introduces a novel control strategy for simultaneous control of position and interaction force for multi-degrees of freedom robotic systems (multi-DOF). The strategy enables both position control in free motion, and interaction force control during contact with an environment. In that sense, it differs from classical control algorithms which are switching between two different controllers, namely, position controller and force controller. The transition between position control mode and force control mode in the newly proposed structure is smooth, removing oscillations often present in the classical algorithms. This improves safety of the interaction between a controlled system and its environment.
This paper investigates the bilateral teleoperation with the possibility of continuously variable scaling during real-time operation. The algorithm proposed for this purpose provides the operator with the ability to change the scaling gains of force and velocity loops during operation. The controllers are derived to enforce exponentially decaying error dynamics on systems which have inner loop disturbance compensation. The proposed architecture assumes the scale factors as continuous functions of time which have continuous derivatives that are also included in the mathematical derivation. Unlike the existing studies, the presented framework allows real-time adaptation of scaling gains, which provides the user with the ability to conduct coarse and fine motion in the same operation. The Lyapunov stability proof of the proposed method is made and the margins of the controller gains are identified for practical operation. Furthermore, the operational accuracy is enhanced by the application of a PD force control loop which is also new for scaled bilateral teleoperation. The realization of PD loop is made using an α - β - γ filter to differentiate the force signal. The algorithm is validated on a setup consisted of two single DOF motion control systems. In order to provide a complete analysis, a wide range of experiments are made, velocity and force scales having sinusoidal patterns with different amplitudes and frequencies. Moreover, comparison with a classical bilateral control architecture is made to highlight the flexibility of the proposed control method. The efficacy of the proposed approach is solidified by the successful tracking responses obtained from these experiments.
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