Design of a denoising hybrid fuzzy-pid controller for active suspension systems of heavy vehicles based on model adaptive wheelbase preview strategy

Active suspension is an effective approach to improve vehicle performance, and it is of great importance to attenuate the vibration of the rear part of heavy vehicles with freight. This paper proposes a new hybrid fuzzy proportional-integral-derivative (PID) controller with model adaptive wheelbase preview and wavelet denoising filter in an active suspension system for heavy vehicles with freight. A half vehicle model is first built, followed with the construction of the road excitation profiles of the shock and vibration pavement. After the design and implementation of the control method, four performance indices of the vehicle are evaluated. To verify the effectiveness of the proposed method, the control performance of the integrated controller and the separate function of every single controller are evaluated respectively. Numerical results show that the integrated control algorithm is superior to the single controllers and is effective in improving the vehicle performance as compared with other methods. Moreover, the wavelet denoising filter is shown to be an effective way to improve the vehicle performance and enable the stability of the system against noise

Intelligent Based Terrain Preview Controller for a 3-axle Vehicle

Presented at 13th International Symposium on Advanced Vehicle Control, AVEC'16; Munich 13-16/09/2016The paper presents a six-wheel half longitudinal model and the design of a dual level control architecture. The first (top) level is designed using a Sugeno fuzzy inference feedforward architecture with and without preview. The second level of controllers are locally managing each wheel for each axle. As the vehicle is moving forward the front wheels and suspension units will have less time to respond when compared to the middle and rear units, hence a preview sensor is used to compensate. The paper shows that the local active suspensions together with the Sugeno Fuzzy, (locally optimised using subtractive clustering), Feedforward control strategy is more effective and this architecture has resulted in reducing the sprung mass vertical acceleration and pitch accelerations

Preview-based techniques for vehicle suspension control: a state-of-the-art review

Abstract Automotive suspension systems are key to ride comfort and handling performance enhancement. In the last decades semi-active and active suspension configurations have been the focus of intensive automotive engineering research, and have been implemented by the industry. The recent advances in road profile measurement and estimation systems make road-preview-based suspension control a viable solution for production vehicles. Despite the availability of a significant body of papers on the topic, the literature lacks a comprehensive and up-to-date survey on the variety of proposed techniques for suspension control with road preview, and the comparison of their effectiveness. To cover the gap, this literature review deals with the research conducted over the past decades on the topic of semi-active and active suspension controllers with road preview. The main formulations are reported for each control category, and the respective features are critically analysed, together with the most relevant performance indicators. The paper also discusses the effect of the road preview time on the resulting system performance, and identifies control development trends

Advanced robust control strategies of mechatronic suspensions for cars

Two novel mechatronic suspensions for road vehicles are studied in this thesis: the Series Active Variable Geometry Suspension (SAVGS) and the Parallel Active Link Suspension (PALS). The SAVGS and the PALS complement each other in terms of the vehicle categories they serve, which range from light high-performance vehicles (the Grand Tourer) to heavy SUV vehicles, respectively, based on the sprung mass and the passive suspension stiffness. Previous work developed various control methodologies for these types of suspension. Compared to existing active suspension solutions, both the SAVGS and the PALS are capable of low-frequency chassis attitude control and high-frequency ride comfort and road holding enhancement. In order to solve the limitation of both SAVGS and PALS robustness, mu-synthesis control methodologies are first developed for SAVGS and PALS, respectively, to account for structured uncertainties arising from changes to system parameters within realistic operating ranges. Subsequently, to guarantee robustness of both low-frequency and high-frequency vehicle dynamics for PALS, the mu-synthesis scheme is combined with proportional-integral-derivative (PID) control, employing a frequency separation paradigm. Moreover, as an alternative robustness guaranteeing scheme that captures plant nonlinearities and road unevenness as uncertainties and disturbances, a novel robust model predictive control (RMPC) based methodology is proposed for the SAVGS, motivated by the promise shown by RMPC in other industrial applications. Finally, aiming to provide further performance stability and improvements, feedforward control is developed for the PALS. Nonlinear simulations with a set of ISO driving situations are performed to evaluate the efficiency and effectiveness of the proposed control methods in this thesis.Open Acces

State Dependent Riccati Equation Control of an Active Hydro Pneumatic Suspension System

In this study, a nonlinear active Hydro-Pneumatic (HP) suspension system is modelled. The HP suspension system model is then incorporated into the quarter car model and a nonlinear controller for the vehicle system is developed. A linear structured model with state dependent matrices of the nonlinear quarter car model is derived for use in controller design. A nonlinear control method, State Dependent Riccati Equation control (SDRE) is used to attenuate sprung mass acceleration, suspension deflection, and tire deflection. The performance of the controller is examined in both frequency and time domains. Active HP suspension system is simulated with sinusoidal inputs at discrete amplitudes and frequencies, and the approximate frequency response functions are obtained. The active HP suspension system is simulated with random road inputs and the root mean square values of the responses are used to evaluate the performance of the controller. The results show that the active suspension successfully and simultaneously decreases the sprung mass acceleration, suspension deflection, and tire deflection around body bounce frequency and thus improved ride comfort and road holding are obtained

Feasibility of Using Nonlinear Time-Frequency Control for Magnetorheological Dampers in Vehicle Suspension

Semi-active vehicle suspensions that use magnetorheological (MR) dampers are able to better dissipate vibrations compared to conventional dampers because of their controllable damping characteristics. The performance of current MR damper control methods is often hindered by incorrect assumptions and linearized models. Therefore, a need exists to design an adaptive controller with improved accuracy and reliability. The objective of this research is to design an improved controller for MR dampers in vehicle suspension using the nonlinear time-frequency control approach and evaluate its feasibility by numerically employing MATLAB Simulink. Simulations in this research are performed using a simplified quarter car suspension model and modified Bouc-Wen damper model. The proposed control method is evaluated based on its ability to reduce the amplitude of vibrations and minimize acceleration of the car body for various test cases. Simulations are also performed using the skyhook controller and passive suspension to assess the performance of the proposed controller. The results of the simulations show that the proposed nonlinear time-frequency controller can successfully be applied to an MR damper suspensions system for vibration control. The proposed controller outperforms the skyhook controller in terms of reducing acceleration of the car body in each of the tested scenarios. The proposed controller also shows the ability to more efficiently manage the current input to the system. In general, the skyhook controller gives more improved vibration amplitude responses but is prone to generate large spikes in car body acceleration at higher frequency road profile inputs. Simulations performed with the passive system show large displacement amplitudes and inability to prevent oscillation. The feed-forward aspect and adaptive nature of the proposed controller gives it the ability to better compensate for the time-delay in the operation of the MR damper. The proposed controller shows sensitivity to controller parameters when pursuing the best response for different road profile input cases

Discrete-time optimal preview control

There are many situations in which one can preview future reference signals, or future disturbances. Optimal Preview Control is concerned with designing controllers which use this preview to improve closed-loop performance. In this thesis a general preview control problem is presented which includes previewable disturbances, dynamic weighting functions, output feedback and nonpreviewable disturbances. It is then shown how a variety of problems may be cast as special cases of this general problem; of particular interest is the robust preview tracking problem and the problem of disturbance rejection with uncertainty in the previewed signal. . (', The general preview problem is solved in both the Fh and Beo settings. The H2 solution is a relatively straightforward extension ofpreviously known results, however, our contribution is to provide a single framework that may be used as a reference work when tackling a variety of preview problems. We also provide some new analysis concerning the maximum possible reduction in closed-loop H2 norm which accrues from the addition of preview action. / Name of candidate: Title of thesis: I DESCRIPTION OF THESIS Andrew Hazell Discrete-Time Optimal Preview Control The solution to the Hoo problem involves a completely new approach to Hoo preview control, in which the structure of the associated Riccati equation is exploited in order to find an efficient algorithm for computing the optimal controller. The problem tackled here is also more generic than those previously appearing in the literature. The above theory finds obvious applications in the design of controllers for autonomous vehicles, however, a particular class of nonlinearities found in typical vehicle models presents additional problems. The final chapters are concerned with a generic framework for implementing vehicle preview controllers, and also a'case study on preview control of a bicycle.Imperial Users onl