YaBeSH Digital Library
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The DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material.2023-12-22T02:44:52ZModel Predictive Control of a Multi-Mode Suspension System Using Preview Information and Weight Optimization
http://yetl.yabesh.ir/yetl1/handle/yetl/4295071
Model Predictive Control of a Multi-Mode Suspension System Using Preview Information and Weight Optimization
Batta, Nathan A.; Doscher, Daniel P.
This study examines the effectiveness of a model predictive controller (MPC) on the multimode active suspension concept to reduce driver absorbed power. A multimode suspension uses additional degrees-of-freedom beyond a traditional active suspension. This allows the suspension to address disturbances with multiple frequencies when coupled with a noncausal control scheme such as MPC. A half-car model is developed by placing both active and passive components in series to mitigate high and low frequency disturbances at the tire-road interface. A stepwise MPC with preview information is applied to the model to measure an incoming disturbance. The model includes noise in state feedback and preview information. A Kalman filter addresses process and measurement noise while the preview information is filtered using an exponential moving average. Process and Measurement noise are considered to be known. Four disturbance profiles are examined: step, two-mode, three-mode, and an ISO8608 Class D profile. Weights used for the MPC process are optimized for each profile according to an objective function based on driver absorbed power. For each profile the response for uncontrolled, controlled, and controlled with preview is examined to assess effectiveness of the multimode suspension. Results demonstrate the utility of the multimode suspension supplemented with MPC for each profile. Driver absorbed power decreases by 68%, 99%, 73%, and 89% for the step, two-mode, three-mode, and ISO8608 Class D profile, respectively. Examination of the natural, disturbance, and forcing frequencies suggests that the MPC accounts for the damped natural frequencies of the system in response to incoming disturbances. The system shows potential to improve performance of vehicles traversing extreme terrain or maintaining a stable chassis for a variety of applications. Future work includes examination of the relationship between the damped natural frequencies, the disturbance, and the resulting control law.
0004-01-01T00:00:00ZOn the Benefits and Limitations of Modulated Damping With Passive Motor Control
http://yetl.yabesh.ir/yetl1/handle/yetl/4295070
On the Benefits and Limitations of Modulated Damping With Passive Motor Control
Vailati, Léo G.; Goldfarb, Michael
Conventional emulated damping, in which velocity feedback is employed in combination with motor current control to emulate damping, is used in a number of mechatronic applications. As known in the field, although such damping should be strictly passive, several implementation factors render this emulation nonpassive and subject to instability, especially with increasing damping ratios. This paper describes an alternative implementation of emulated damping that employs passive motor control, which does not draw energy from a battery or any other power source. The method is specifically described in the context of a brushless direct-current (BLDC) motor; an unique controller architecture is used along with a particular MOSFET switching scheme which employs only a subset of the standard BLDC motor driver and does not require electronic commutation. This paper employs analytical and experimental means to compare damping control with the described passive motor approach, relative to using a conventional BLDC motor control approach. Stability considerations for each scheme are discussed. Benchtop testing demonstrates the advantage of the passive control scheme in terms of providing smooth behavior, enhancing control robustness, preventing energy leaks, and providing accurate behavior. The special cases of unilateral and asymmetric behaviors (i.e., different damping command for each direction of rotation) are also considered.
0005-01-01T00:00:00ZControl Oriented Modeling, Experimentation, and Stability Analysis of an Autorotating Samara
http://yetl.yabesh.ir/yetl1/handle/yetl/4295069
Control Oriented Modeling, Experimentation, and Stability Analysis of an Autorotating Samara
McConnell, Jonathan; Das, Tuhin
This paper presents a control-oriented model for describing the steady-state and dynamic behavior of a single-winged samara seed-pod in autorotative descent. A negligible lateral center of mass motion and constant, prescribed roll-angle to develop a simplified and compact model. Spanwise aerodynamic dependence is exchanged for an independent blade element representation with two tuned parameters to account for the effects of leading-edge vortex phenomena. The resulting model is a fourth-order nonlinear dynamical system. The accuracy of this model is established by validating it against our own experimental data as well as against those reported in the literature by other researchers. The validation exercise reveals that zero roll-angle is a viable assumption that significantly reduces model complexity while retaining accuracy. A necessary condition is derived for the existence of steady autorotation of the samara under free descent. Furthermore, a stability analysis is conducted suggesting that the eigenvalues of the fourth-order system, linearized about the autorotational equilibrium, can be well-represented by those of two decoupled two-dimensional systems. The analysis reveals the critical parameters that determine stability of sustained autorotation. Such stability analysis provides a platform for similar analytical exploration of future model improvements. The validity of this compact model suggests the plausibility of designing and controlling simple autorotative mechanisms based on these dynamics.
0005-01-01T00:00:00ZModel-Free H∞ Output Feedback Control of Road Sensing in Vehicle Active Suspension Based on Reinforcement Learning
http://yetl.yabesh.ir/yetl1/handle/yetl/4295068
Model-Free H∞ Output Feedback Control of Road Sensing in Vehicle Active Suspension Based on Reinforcement Learning
Wang, Gang; Li, Kunpeng; Liu, Suqi; Jing, Hui
An active suspension system ensures the controllability of a vehicle in the vertical direction, which greatly enhances the control redundancy and safety of an intelligent driven vehicle. However, many calibrated model parameters are not conducive to the application of optimal control. To reduce the control cost of active suspension, a model-free H∞ output feedback control method is studied in this research. First, the optimal governing equation of the active suspension is transformed into a zero-sum game problem of two players, and an off-policy reinforcement learning algorithm is established to solve the game algebraic Riccati equation. This method could overcome the disadvantage of constant interactions between Q-learning and the environment. Secondly, with the consideration that some state variables are difficult to measure, a data-driven H∞ output feedback controller is designed using road sensing information and historical measurement data, and the Bellman equation of the system is solved using the least squares method to obtain the optimal control solution of the active suspension. The simulation and rapid prototype experimental results show that the proposed method could produce the optimal control strategy of the system without model parameters, overcome the strong dependence and sensitivity of traditional design methods to model parameters and improve the robust control effect of the active suspension.
0005-01-01T00:00:00Z