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In this paper, vehicle stability enhancement, based on the integrated vehicle control notion, is presented. A new method for adaptive optimal distribution of braking and lateral tyre forces is employed. The control inputs considered are the individual wheel steering and braking for each wheel. Since a unique set of tyre forces satisfying control objectives cannot be easily determined, an adaptive optimization problem subjected to two equality and four inequality constraints has been solved to achieve an optimal solution. A proper adaptation mechanism is suggested to minimize the negative effects of direct yaw moment control, such as the undesirable decrease in the total speed of the vehicle. The effectiveness of the proposed vehicle stability enhancement system, especially online balancing of tyre forces in an optimal form with and without an adaptation mechanism, is demonstrated through digital simulations. A comprehensive non-linear vehicle dynamics model is utilized for simulation purposes. The results indicate that the proposed control system can effectively utilize the tyres' frictional forces and significantly improve the vehicle stability and handling performances.

In this paper, two-time scale control design for trajectory tracking of two cooperating planar rigid robots moving a flexible beam which does not require any vibration measurement of the beam is presented. First, kinematics and dynamics of the robots and the object are derived. Then, using the relations between different forces acting on the object by the manipulators' end-effectors, the dynamic equations of the robots and the object are combined. Applying two-time scale control theory on the combined dynamics, a control scheme is elaborated which makes the position and orientation of the mass center of the beam track a desired trajectory while suppressing the beam vibration. For the controller algorithm, first a slow controller is applied for the slow (rigid) subsystem and then a fast stabilizing controller is considered for the fast (flexible) subsystem; these two controllers constitute the composite control scheme. To avoid requiring any beam vibration measurement for the fast control law, a linear observer is also designed. The simulation results show the efficiency of the proposed control scheme. WeB01.21-4244-0989-6/07/$25.00 ©2007 IEEE. 2 1 0 0 J J J

This paper considers robust boundary control with disturbance adaptation to stabilize the vibration of a rectangular plate under disturbances with unknown upper-bounds. Disturbances are considered to be distributed both over the plate interior domain and along the boundary (in-domain and boundary distributed disturbances). Applying Hamilton's principle, the dynamics of the plate is represented in the form of a fourth-order partial differential equation subject to static and dynamic boundary conditions. The proposed model considers the membrane effect of axial force and the effect of actuator mass dynamics on the plate vibration. A robust boundary control is established that stabilizes the plate in presence of both in-domain and boundary disturbances. A rigorous Lyapunov stability analysis shows that the vibration of the plate is uniformly ultimately bounded and converges to the vicinity of zero by proper selection of control gains. For the vanishing in-domain disturbances, it is seen that exponential stability is achieved by the proposed control. Next, a disturbance adaptation law is introduced to stabilize the plate vibration in response to disturbances with unknown bounds, and the stability of the robust boundary control with disturbance adaptation is studied using Lyapunov. Simulation results verify the efficiency of the suggested control.

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Nonlinear vehicle control allocation is achieved by distributing the control task to tire forces with nonlinear saturation constraints. The overall vehicle control is accomplished by developing a hierarchical scheme. First, a high-level sliding mode control with adaptive gain is considered to obtain the body force/moment for stable vehicle motion. The proposed controller only requires online adaptation of control gains without acquiring the knowledge of upper-bounds on system uncertainties. Then, optimal distribution of tire forces (ODF) with nonlinear saturation constraints is considered. The high-level control objectives are mapped to individual tire forces by formulating a nonlinear optimization problem. The interior-point (IP) method is adopted for a nonlinear programming task at each time step. Evaluation of the overall system is accomplished by simulation testing with a nine-degrees-of-freedom vehicle nonlinear model. Comparison with a well-recognized control system shows the effect of saturation constrained ODF (SCODF) on improving vehicle handling and stability.

This paper presents dynamic modeling and Lyapunov-based boundary control of a hybrid Euler-Bernoulli beam. The beam is hybrid in the sense that it holds both rigid and elastic motions. The beam is equipped with actuators hub at one end and it carries the payload as the tip mass at the free end. The distributed parameter dynamic equations (i.e. partial differential equations governing the hybrid beam motion) are derived using Hamilton's principle. The dynamic model consists of four distributed parameter dynamic equations, representing the beam vibration and rigid motion in the plane, coupled to the discrete dynamic boundary equations. This paper uses the system equations to achieve model-based control laws that asymptotically stabilize the beam vibration while driving the rigid body position and orientation to the desired set point. The control system applies three forces/torque at the hub to regulate the rigid body position/orientation and a transverse force at the free end to suppress the beam vibration. In this regard, the control system only applies actuation and makes measurement at the beam boundary, thus excluding the need for distributed actuators or sensors. Furthermore, the proposed method directly uses the system equations for the control design without model truncation to rule out spillover instabilities. The closed-loop system stability is shown through Lyapunov-based analysis. Numerical simulations demonstrate the effectiveness of the proposed method.

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