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This chapter designs a non-fragile H∞ controller for a class of active suspension systems with actuator uncertainty. By using Lyapunov stability theory, a nonfragile controller is designed for the purpose of ensuring that the resulting active suspension system is asymptotically stable with a prescribed H∞ disturbance attenuation level. The designed non-fragile H∞ controller is constructed via convex optimization by guaranteeing its sufficient condition in terms of feasible linear matrix inequalities (LMIs). Simulation results are given to show the effectiveness of the proposed control approach.
A novel interval type-2 fuzzy controller architecture is proposed for resolving nonlinear control problems of vehicle active suspension systems. It integrates Takagi-Sugeno (T-S) fuzzy model, interval type-2 fuzzy reasoning, the Wu-Mendel uncertainty bounds method, and selected optimization algorithms in order to construct the switching routes between generated linear model control surfaces. The stability analysis of the proposed approach is presented. The proposed method is implemented into a numerical example and a case study on a nonlinear half-vehicle active suspension system. The simulation results demonstrate the effectiveness and efficiency of the proposed approach.
In recent years, the motor vehicle industry has shown a tendency of replacing electro-mechanical components by mechatronic systems with intelligent and autonomous properties. The integration of hardware components and implementation of advance control function characterize this replacement. In this text, we have applied the system approach and system engineering methods in the initial phase of vehicle active suspension development. An emphasis has been placed upon the interrelations between computer-aided simulation and other elements of development process. The benefits of the application of active suspension simulation are numerous: reduction of time to market, the new and improved functions of mechatronic components/devices, and the increased system reliability. In suspension model development, we used CAD/CAE tools, as well as the multipurpose simulation programs. For simulation, we used the quarter-car model. The modeling was carried out through the state-space equation, after which we designed two variants of controller for the suspension system - proportional-integral-derivative (PID) controller and neural network controller.
This chapter focuses on H∞, fuzzy control of suspension systems under actuator saturation. The Takagi-Sugeno (T-S) approach is used to model the suspension system (quarter, half and full cars) by interpolation of different local linear models. A nonlinear state feedback control parallel distributed compensation (PDC) is employed for designing control system. The main idea of this controller consists in designing a linear feedback control for each local linear model. To address the input saturation problem, both constrained and saturated control input cases are proposed. In the two cases, H∞, stabilization conditions are derived using Lyapunov method. Moreover, a controller design with the largest domain of attraction is formulated and solved as a linear matrix inequality optimization problem. An application to quarter-car suspension system is given. Our simulation results show that both saturated and constrained controls can stabilize the resulting closed-loop suspension quarter car via PDC control and eliminate the effect of external disturbances despite the presence of saturation. Indeed, the main roles of car suspension systems which consist of improving ride comfort of passengers and the road holding capacity of the vehicle are achieved.
This chapter presents the study of robust active control of an integrated vehicle suspension system that consists of chassis suspension, seat suspension, and driver body models. This integrated system has five control inputs and ten control outputs and each control input may require different feedback signals and have different saturation limits. Taking the measurement available variables as feedback signals, an H∞ static output feedback controller is designed to improve vehicle ride comfort performance in terms of driver head acceleration under the constraints of actuator saturation, suspension deflection limitation, and road holding capability. The parameter uncertainties to the driver body are considered in the controller design procedure. The controller design conditions, which are expressed as linear matrix inequalities (LMIs), are derived by dealing with each control input separately under a common Lyapunov function so that a feasible solution can be found. Furthermore, force tracking control strategy is applied to implement the proposed control system using electrohydraulic actuators. The improvement of ride comfort is evaluated by using numerical simulations on the driver head acceleration responses under a typical road disturbance.
