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This paper proposes a sequential design scheme for switching ℌ∞ LPV (Linear Parameter-Varying) control, aiming to reduce the computational complexity of the associated optimization problem. Different from the traditional approach that simultaneously designs switching LPV controllers and solves a high-dimensional optimization problem, the proposed sequential design approach renders a bundle of low-dimensional optimization problems to be solved iteratively. Individual ℌ∞ LPV controller for each subregion is synthesized by independent PLMIs (Parametric Linear Matrix Inequalities) to guarantee ℌ∞ performance, and controller variables are interpolated on the overlapped subregions such that the ℌ∞ performance is also guaranteed on the overlapped subregion. Numerical examples are used to demonstrate the effectiveness of this method to reduce the computational load in each design iteration and improved ℌ∞ performance over the conventional simultaneous design method with well-tuned interpolation coefficient. [ABSTRACT FROM AUTHOR]

This note presents an algorithm to design discrete time controllers which are robust with respect to parameter variations and which also guarantee specified [l.sub.2] performance constraints for stochastic inputs and [l.sub.infinity] performance constraints for deterministic inputs. This is not an analysis but a design method guaranteeing the specified robust performances. Also an upper bound on the covariance matrix is provided.

The robust disturbance rejection bounds in [1] are tight with respect to the disturbance set that has a specified [L.sub 2] norm bound. This note shows that the robust disturbance rejection bounds in [1] are also tight with respect to a weighted [I.sub.2] disturbance set that has a specified bound on its outer product by choosing a special weight matrix in the [L.sub.2] norm. The matrix can be computed by numerical iteration.

Sudden vehicle propulsion torque change under tip-in/out maneuver often leads to low-frequency longitudinal vibration due to the flexibility in the half-shaft and tire slip, which greatly affects vehicle drivability. Note that the vibration frequency is between 1 and 10 Hz and is difficult to be absorbed by the vehicle mechanical system. To optimize the vehicle drivability under tip-in maneuver, an Adaptive Linear Quadratic Tracking (ALQT) anti-jerk traction controller is proposed in this paper. Based on the experimental data, a Carsim-Simulink co-simulation model is developed for assessing control performance. A control-oriented model, considering the nonlinear characteristics of the tire-road friction coefficient and slip ratio, is then proposed. A reference model with rigid axle is used to provide the equilibrium points and reference velocity trajectory. Jacobi linearization method is then used to linearize the model along the desired trajectory and a linear deviation model based on equilibrium points is obtained. Finally, the deviation compensation receding horizon LQT controller is designed along with the Kalman state estimation. The effectiveness of the designed controller is assessed via simulation studies under different road surfaces and compared with PID and LQR controllers. The LQT controller is able to track the desired velocity profile with minimum jerk while increasing road safety. Furthermore, the effect of LQT weighting coefficients under different road surfaces are discussed. Simulation results show that the ALQT controller is able to optimize vehicle drivability under different road surfaces and the weighting matrices shall be selected based on the road condition for optimal drivability. [ABSTRACT FROM AUTHOR]

A faulty sensor may lead to degraded system performance, system instability or even a fatal accident. On the other hand, the increasing need for safety and reliability has motivated the development of fault-tolerant control techniques. In this work, the sensor performance degradation due to its aging is modelled by the increment of sensor measurement noise covariance. The main contribution of this paper is the characterisation of the control synthesis conditions using parametrised linear matrix inequalities (PLMIs) for a multi-objective gain-scheduled noisy output-feedback controller that minimises the output cost on H 2 performance with satisfactory system stability, H ∞ performance and control input covariance constraints ( H 2 constraints on the control inputs) in the presence of sensor aging. The closed-loop system stability and performance, in terms of mixed H 2 / H ∞ performances, relative improvement, numerical complexity, computation time, and initial conditions response, are studied, and a numerical example is used to illustrate the effectiveness of the proposed control scheme. The synthesised controller guarantees not only the stability but also the closed-loop mixed H 2 / H ∞ performances, and it is feasible for real-time applications. [ABSTRACT FROM AUTHOR]