Jagat Jyoti Rath

Output Feedback Active Suspension Control With Higher Order Terminal Sliding Mode

The control of an automotive suspension system using hydraulic actuators is a highly complex nonlinear control task dealing with system nonlinearities, external disturbances, and uncertainties. In this work, an output feedback active suspension control scheme is proposed to achieve a ride comfort while maintaining the road holding for the vehicle. To design the controller, the states of the nonlinear system are first estimated using a highgain observer where the suspension stroke is the only measurable output. The controller is then designed using a recursive derivative nonsingular higher order terminal sliding mode approach that avoids singularity. The practical stability for the closed-loop observer-controller pair is established. Simulation results for the quarter-wheel vehicle over various road conditions demonstrate the effectiveness of the proposed control in improving the suspension performance in both the time and frequency domains.

Simultaneous Estimation of Road Profile and Tire Road Friction for Automotive Vehicle

The longitudinal motion control of automotive vehicles is heavily reliant on information about the time-varying tire road friction coefficient. In the presence of varying road roughness profiles, the effective vertical load on each wheel varies dynamically, influencing the tire friction. In this paper, we integrated the vertical and longitudinal dynamics of a quarter wheel to form an integrated nonlinear model. In the modeled dynamics, the time-varying random road profile and the tire friction are treated as unknown inputs. To estimate these unknown inputs and states simultaneously, a combination of nonlinear Lipschitz observer and modified super-twisting algorithm (STA) observer is developed. Under Lipschitz conditions for the nonlinear functions, the convergence of the estimation error is established. Simulation results performed with the high-fidelity vehicle simulation software CarSim demonstrate the effectiveness of the proposed scheme in the estimation of states and unknown inputs.

Rollover Index Estimation in the Presence of Sensor Faults, Unknown Inputs, and Uncertainties

The rollover status of a vehicle indicated by the lateral load transfer (LTR) as the vehicle traverses over various driving scenarios is critical in the implementation of antirollover control procedures. The determination of LTR is often carried out by the measurements of the roll angle, the lateral acceleration, vertically acting suspension forces, etc. In all these measurements, sensor faults may occur, which lead to a faulty computation of the rollover status, raising a false alarm. In this work, a scheme based on a robust higher order sliding-mode observer is proposed to estimate the states of a nonlinear two-wheel vehicular system affected by road disturbances, uncertainties in the height of the vehicles center of gravity, and possible multiple sensor faults. Applying the proposed approach, the unknown inputs and sensor faults are reconstructed. To perform the estimations, adaptive sliding-mode-based observers that do not require the knowledge of the bounds of the uncertainties and unknown inputs are designed. Consequently, the true rollover status of the vehicle is determined, in spite of the presence of sensor faults. The validity of the proposed scheme has been assessed on the vehicle simulation software CarSim as the vehicle undergoes a double lane change maneuver.

Adaptive Super-Twisting Observer for Estimation of Random Road Excitation Profile in Automotive Suspension Systems

The estimation of road excitation profile is important for evaluation of vehicle stability and vehicle suspension performance for autonomous vehicle control systems. In this work, the nonlinear dynamics of the active automotive system that is excited by the unknown road excitation profile are considered for modeling. To address the issue of estimation of road profile, we develop an adaptive supertwisting observer for state and unknown road profile estimation. Under Lipschitz conditions for the nonlinear functions, the convergence of the estimation error is proven. Simulation results with Ford Fiesta MK2 demonstrate the effectiveness of the proposed observer for state and unknown input estimation for nonlinear active suspension system.

Active Control of Nonlinear Suspension System Using Modified Adaptive Supertwisting Controller

The suspension system is faced with nonlinearities from the spring, damper, and external excitations from the road surface. The objective of any control action provided to the suspension is to improve ride comfort while ensuring road holding for the vehicle. In this work, a robust higher order sliding mode algorithm combining the merits of the modified supertwisting algorithm and the adaptive supertwisting algorithm has been proposed for the nonlinear active suspension system. The proposed controller is robust to linearly growing perturbations and bounded uncertainties. Simulations have been performed for different classes of road excitations and the results are presented.

Robust Fault-Tolerant Cruise Control of Electric Vehicles based on Second-order Sliding Mode Observer

This paper presents fault-tolerant cruise control of an electric vehicle based on the permanent magnet synchronous motor (PMSM). A higher order sliding mode (HOSM) observer is designed to estimate the unknown back electro motive forces (EMFs) in the plant dynamics. A finite-time smooth estimation without low-pass filtering is obtained and the chattering phenomenon is eliminated. With the estimated back EMFs, an accurate speed estimate of PMSM can be algebraically computed. The estimated speed is provided as a feedback whenever fault occurs in the measurement speed. The corresponding torque output drives the electric vehicle (train, car) to maintain the vehicle speed to a desired vehicle speed reference. Simulations in a high fidelity CarSim confirm the validity of the overall approach.

Estimation of road profile for suspension systems using adaptive super-twisting observer

The performance evaluation of active suspension system of vehicle is critically reliant on estimation of random road roughness profile. In this paper, the nonlinear dynamics of spring and damper of the active suspension system are considered to develop a nonlinear model excited by the random road excitation profile as an unknown input. To estimate the unknown input, an adaptive super-twisting algorithm based observer is designed for estimation of the road profile and states of the system. Under Lipschitz conditions, the convergence of the error dynamics is then proven. The effectiveness of the proposed observer for state and unknown input estimation is shown through simulation results performed for the Ford Fiesta MK2 vehicle suspension dynamics.

Estimation of side slip and road bank angle using high-gain observer and higher-order sliding mode observer

The estimation of vehicle side slip and road bank angle is a significant issue in automotive research. In this work, to solve the state and unknown inputs estimation problem for the nonlinear vehicle dynamics, a high-gain observer in combination with higher-order sliding mode observer is employed. The high-gain observer is designed to overcome the parametric uncertainties and the higher-order sliding mode observer is employed for smooth estimation of unknown inputs. The combined observer does not impose the small-Lipschitz-constant condition on the system nonlinearity. Simulation results demonstrate the effectiveness of the proposed observer for estimation of the vehicle side slip and the road bank angle.

An induction motor sensor fault detection and isolation based on higher order sliding mode decoupled current controller

This paper presents a novel decoupled current-control method for induction motor (IM) based on higher order sliding mode (HOSM) controller. In the proposed scheme, the decoupled control of d - q currents does not require the knowledge of the speed. The HOSM controllers play the same role as the compensation voltages produced by a decoupling compensator. Based on this observation, the speed is estimated accurately through algebraic calculations by avoiding the low-pass filtering. The estimated speed is then employed for fault detection and isolation. Simulations on a 1/4-hp three-phase IM in the presence of noise highlights the performance of the proposed approach.

Sliding-Mode-Based Observer–Controller Structure for Fault-Resilient Control in DC Servomotors

This paper presents a robust observer–controller scheme for sensor fault-resilient control in dc servomotor drive-based applications (such as antennae control for satellite tracking, radio telescopes, and conveyor belt systems). In contrast to the earlier works on abrupt faults, this paper considers incipient sensor faults and detects using the higher order sliding mode (HOSM) observer, followed by a tracking controller, which maintains the acceptable drive performance. A robust output tracking controller based on fractional integral terminal sliding mode surface with HOSM terms is developed to ensure faster and finite-time convergence of the error trajectory. Moreover, various slopes of incipient faults are considered to analyze the detection delay, and switching strategy reconfigures the system with the estimated speed whenever the residual crosses the threshold. The closed-loop performance in the presence of most common faults (abrupt, incipient, and intermittent) is experimentally validated on a dc motor-based industrial mechatronic drives unit with belt-drive inertial load (which exhibits nonlinear friction, torque variations, and other disturbances).