The paper presents a new control architecture consisting of two control loops to balance an Inertia Wheel Pendulum (IWP) of which the wheel is driven by a DC motor. The outer control loop uses a lqr controller to calc...
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ISBN:
(纸本)9781509020980
The paper presents a new control architecture consisting of two control loops to balance an Inertia Wheel Pendulum (IWP) of which the wheel is driven by a DC motor. The outer control loop uses a lqr controller to calculate the required torque to balance the IWP around the upright position based on the measurement of the pendulum angle and angular velocity. The inner control loop uses a PI controller to calculate the voltage applied to the DC motor such that the torque provided by the motor meets the requirement of the outer loop. Matlab simulation and real hardware experiments have been carried out to validate the effectiveness of the proposed method.
A control system for a piezoelectric beam actuator, which had one or two control inputs, was a subject of numerical and laboratory research. The actuator had a prismatic shape with a rectangular cross-section and cons...
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A control system for a piezoelectric beam actuator, which had one or two control inputs, was a subject of numerical and laboratory research. The actuator had a prismatic shape with a rectangular cross-section and consisted of one layer of carrying substrate made from PCB-FR4 and two patches of Macro Fiber Composite of P1 type. MFC patches were glued on both sides of the carrying substrate. An article presents a comparison of the control quality of piezoelectric actuator with one control signal (one-input actuator) and the control quality of piezoelectric actuator with two control signals (two-input actuator). An application of two-input actuator led to a reduction of control voltage compared to the control voltage of one-input actuator. The decrease in the maximum voltage was approximately from 30% to 39% in conducted laboratory experiments. An application of two-input actuator causes a reduction of an overshoot value compared to one-input actuator. An application of limit of maximum control voltage leads to a greater decrease of the control quality for one-input actuator compared to two-input actuator.
In emergency situations, it is difficult to meet the requirements of safe driving only by relying on the braking system, and the probability of accidents can be reduced by employing an emergency lane-changing mode. To...
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In emergency situations, it is difficult to meet the requirements of safe driving only by relying on the braking system, and the probability of accidents can be reduced by employing an emergency lane-changing mode. To improve the adaptability of the distributed electric vehicle adaptive cruise control (ACC) strategy to complicated and volatile conditions, a multimode ACC strategy with emergency lane-changing function is proposed. Firstly, the ACC is divided into four modes aimed at the problem of complex conditions, and a switching strategy is designed to control the switching of them. Simultaneously, the car-following mode is divided in greater detail based on time to collision (TTC), and the acceleration weighted average algorithm is adopted for accuracy and output continuity during switching. Then, the ACC is established with a hierarchical control framework, in which a PID-based cruise mode and a multi-objective optimized car-following mode based on model predictive control (MPC) are devised. The target brake wheel cylinder pressure is selected as the emergency brake pressure in takeover mode. In addition to the MPC-based system, the emergency lane-changing mode incorporates a yaw moment controller in the upper-level controller to improve body stability during emergency lane changing in the upper-level controller. In the lower-level controller, the upper-level output is converted into driving torque, wheel cylinder pressure, and front wheel angle to control vehicle travel and generate additional yaw moment. Finally, the results indicate that the presented multimode switching strategy can adapt to complex and instable transportation environments. In the cruise control scenario, the host vehicle can rapidly reach cruising speed within 5 s. In the car-following scenario, the host vehicle can stably follow the preceding vehicle with an acceleration of -5-3.5 m/s2 and a jerk of -2-2 m/s3 throughout the entire process, maintaining a safe distance from the preceding ve
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