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In this study, a nonlinear predictive control method is developed for the active steering control of a sport utility vehicle. The method is tested on a nonlinear mathematical model of an 11-degree-of-freedom vehicle. The system performance is evaluated by considering that the control law must keep the actual yaw rate close to the desired yaw rate and minimizing the vertical load changes at each wheel. The latter is proposed for this work. The vertical load changes play an important role in the dynamics and the stability of the system. The effectiveness of the control method is demonstrated through numerical simulation by using a vehicle model that includes three case studies: rapid lane change at low and high velocities and the fishhook manoeuvre. The results show that the stability of the vehicle is maintained and its rollover propensity is decreased. In addition, the proposed controller is compared with a well-known linear model predictive controller.

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In rubber-wheeled road vehicles, the mechanical connection between steering wheel and front wheels provides steeringrelated feedback to the driver. The torque fed back to the driver through the steering linkages and steering wheel, which is called steering feel, helps the driver in controlling the vehicle. The torque feedback is reproduced via artificial methods in steer-by-wire systems due to the lack of mechanical connection. In this work, in order to minimize the physical workload and the lateral acceleration under the consideration of handling performance, optimization of a hysteresis-based steering feel has been studied. A 2-degree-of-freedom bicycle model based on the magic formula tire model has been used for simulations and hardware-in-the-loop experiments. A mathematical model is proposed in order to create an adaptive model-based optimization of the hysteresis parameters simultaneously while driving. A hardware-in-the-loop experimental setup has been used for the driving tests. The weave and the double-lane change tests have been performed with different drivers in order to demonstrate and quantify the optimization methods that are presented in this work.

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The design and control of a cable-driven rehabilitation robot, which can be configured easily for exercising different articulations such as elbows, shoulders, hips, knees and ankles without requiring any orthosis, are introduced. The passive, active-assisted and active-resisted exercises were designed and implemented using impedance control. The controller could switch between exercises according to the force feedback. The effectiveness of the proposed controller was demonstrated by experimental studies. The robot was tested first with a dummy extremity and then with a healthy subject mimicking various types of patients during the tests. Experimental results showed that satisfactory closed-loop performances were achieved.

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