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To address vehicle drivetrain vibrations that cause discomfort and poor drivability, this study proposes a new active damping strategy with simple backlash compensation based on the simultaneous perturbation stochastic approximation (SPSA) with norm limited update vector. First, an experimental device developed for a simplified drivetrain mechanism is demonstrated. A mechanism for reproducing both the contact mode and the backlash mode is included in the device. For the contact mode, a model based 2 controller is employed as the baseline damping strategy. Further, to mitigate the backlash effect, a simple algorithm based on mode switching based compensation is used with the 2 controller. In particular, for the critical controller parameters, this paper presents a systematic design approach to search for their optimal values. The key parameters, which are needed for the backlash and contact mode controllers, are simultaneously auto tuned using norm limited update vector based SPSA, which ensures the stability in the iterative tuning. The novelty of this study is that both the backlash mode controller and the contact mode controller are simultaneously optimized by the improved version of SPSA, thus realizing a comprehensive auto tuning design of an active drivetrain damping system. Finally, the active controller is experimentally verified using the actual test device. Comparative studies show that the proposed approach significantly reduces drivetrain vibrations and is robust against fluctuations in the backlash.

This study experimentally verifies robustness of a model-free vibration controller based on a virtual controlled object (VCO) considering parametric uncertainty of actuator. A proof-mass actuator, which can be modeled as a single-degree-of-freedom (SDOF) system, is used. A VCO, which is defined as an SDOF structure, is introduced between a real controlled object and the actuator model. The parameters of the VCO are determined so as to achieve model-free vibration control. A state equation to derive the model-free controller is constructed using the two-degree-of-freedom (2DOF) structure composed of the actuator model and the VCO. The parametric uncertainty of the actuator is quantitatively characterized in the 2DOF structure. The mixed H-2 /H(infinity )control theory is used to design a model-free controller. The vibration suppression performance and robustness to the actuator uncertainty of the proposed method are validated by experiments. Simulation studies are also conducted to enhance the validity of the experimental results. As a result, the proposed damping method exhibits good damping performance and strong robustness to the actuator uncertainty and characteristic changes in controlled object.

A one-shot data-driven tuning method for a fractional-order proportional-integral-derivative (FOPID) controller is proposed. The proposed method tunes the FOPID controller in the model-reference control formulation. A loss function is defined to evaluate the match between a given reference model and the closed-loop response while explicitly considering the closed-loop stability. A loss function value is based on the fictitious reference signal computed using the input/output data. Model matching is achieved via loss function minimization. The proposed method is simple and practical: it needs only one-shot input/output data of a plant (no plant model required), considers the bounded-input bounded-output stability of the closed-loop system, and automatically determines the appropriate parameter value via optimization. Numerical simulations show that the proposed approach facilitates good control performance, and destabilization can be avoided even if perfect model matching is unachievable.

A parameter tuning technique without manual trial-and-error procedures is proposed for a controller in a model-free vibration control system based on a virtual controlled object (VCO), which is defined as a single-degree-of-freedom (SDOF) system. The model-free control system is constructed by inserting a VCO between the actuator and the actual controlled object. A reference controlled object (RCO), which is also expressed as an SDOF system, is defined for the configured model-free control system. Then the loss function, which is calculated using the RCO vibration control simulation results, is used to evaluate the vibration suppression performance. The simultaneous perturbation stochastic approximation (SPSA) adjusts the controller tuning parameters to minimize the loss function. The SPSA- and RCO-based tuning procedures automatically tune the model-free controller without manual trial-and-error procedures. Simulations and experiments demonstrate that a model-free linear quadratic regulator designed by the proposed approach provides sufficient vibration reduction.

This study presents a simple active vibration controller with a self-tuning mechanism free from a mathematical model of an actual controlled object. First, a virtual controlled object (VCO), which is defined as a single-degree-of-freedom (SDOF) system, is inserted between an actuator model and an actual controlled object. Traditional model-based control theories are applied to a twodegree-of-freedom (2DOF) system composed of the actuator and the VCO instead of a model of the actual controlled object to realize a model-free vibration controller. Then a self-tuning method based on the simultaneous perturbation stochastic approximation (SPSA) is introduced to the VCO-based model-free controller to obtain sufficient damping performances for various controlled objects. The model-free controller design is easily achieved because the traditional model-based control theory can be applied to the 2DOF system composed of the actuator and the VCO. Moreover, the proposed self-tuning mechanism provides sufficient vibration suppression effects for various controlled objects without manual controller tunings. Simulation studies compare the damping performance of the VCO-based model-free adaptive control scheme with that of the conventional approach. The simulations employ five controlled objects with different structures and characteristics, including time-varying properties. The proposed control scheme provides better damping effects than the conventional method for all controlled objects.

Purpose This study improves the robustness of the model- free controller based on a virtual structure. Additionally, the adverse interference between the proof-mass actuator resonance and a controlled object is investigated as it is not clarified in the previous studies. Methods and Results A virtual structure modeled as a SDOF system was inserted between the actuator and the actual controlled object. This achieved the indirect damping of the actual controlled object and model-free control. Vibration control simulations were conducted for various finite element models with a model-free H-infinity controller based on a virtual structure. The results demonstrate that the actuator resonance adversely affects the stability of the control system when the controlled object has a mode whose natural frequency is too close to that of the actuator. Therefore, a notch filter was applied to the model-free H-infinity controller design approach to suppress the resonance without affecting the damping performance. The improved controller with notch filter is more robust to the resonance of the actuator than the previous one. Conclusions The resonance of the proof-mass actuator adversely affects the stability of the control system composed of the previous model-free H-infinity controller when the low-order vibration mode of the actual controlled object is too close to the natural frequency of the actuator. Introducing a notch filter into the model-free approach based on a virtual structure effectively reduces the negative impact due to the resonance of the actuator and improves the robustness of the control system.

For active vibration control of powertrain oscillations, the purpose of this research is to present a simple fuzzy-reasoning-based compensation strategy for a time-varying control cycle limitation of an actuator. A simplified drivetrain dynamics model is shown, and the simulation configuration with the control cycle limitation is constructed. A model predictive compensation using a sampled-data controller is employed to tackle the maximal phase delay of the control input due to the time-varying control cycle. The control input update timing, which is perturbed from that of the fixed periodical controller, is expressed as fuzzy sets such as Approximately past step and Approximately future step. Based on these fuzzy sets, the Tsukamoto-type fuzzy reasoning with only four intuitive rules can flexibly infer unknown control inputs updated at various timings. Simulation verifications demonstrate that the 2-norm of the vibration performance by the proposed method is reduced by more than 27.8% compared to other previous controllers. Moreover, it is revealed that the better transient performance can be maintained even with 10% plant parameter variations, indicating the high robustness of the proposed damping controller.

The purpose of this research is to construct a simple and practical controller design method, considering the actuator's parameter uncertainty, without using a model of controlled objects. I n this method, a controller is designed with an actuator model including a single-degree-of-freedom virtual structure inserted between actuator and controlled object, resulting in a model-free controller design. Furthermore, an H-infinity control problem is defined so that the actuator's parameter uncertainty is compensated by satisfying a robust stability condition. Because the actuator model including the virtual controlled object is a simple low-order system, and the actuator's parameter uncertainty is considered, a controller with high robustness to the actuator's parameter uncertainty can be designed based on traditional model-based control theory. The effectiveness of the proposed method is verified by both simulation and experiment.

The purpose of this study is to develop a simple and practical controller design method without modeling controlled objects. In this technique, modeling of the controlled object is not necessary and a controller is designed with an actuator model, which includes a single-degree-of-freedom virtual structure inserted between the actuator and the controlled object. The parameters of the virtual structure are determined so that indirect active vibration suppression is effectively achieved by considering the frequency transfer function from the vibration response of the controlled object to that of the virtual structure. Since the actuator model, which includes a virtually controlled object, is a simple low-order system, a controller with high control performance can be designed by traditional model-based optimal control theory. In this research, a mixed H2/H infinity controller is designed considering both control performance and robust stability. The effectiveness of the proposed method is validated experimentally. The robustness of the controller is demonstrated by applying the same controller to various structures.