An AFS (active front steering) on the basic of a C-EPS (column electric power steering) system was developed. Based on the mathematical model of essential components, the AFS controller was designed covering two units: an EPS actuator unit was used to reduce the steering torque requirement to the driver; an AFS actuator unit was used to compensate the steering angle for steering characteristics...

This work presents the BDU technique (Bounded Data Uncertainties) and the tuning of the linear quadratic regulator (LQR) via this technique, which considers models with bounded uncertainties. The BDU method is based on constrained game-type formulations, and allows the designer to explicitly incorporate a priori information about bounds on the sizes of the uncertainties into the problem stateme...

In present work the various aspects on mathematical modelling, stability and control strategies of flexible double link manipulator have been investigated. A mathematical model of flexible double link manipulator has been developed using lagrangian method. This mathematical model has been characterized using classical and modern control theories. Their time domain and frequency domain analysis ...

Penelitian ini membahas penerapan metode Regulator Kuadratik Linier (LQR) pada sistem kendali optimal. LQR menggunakan kombinasi linier dari state plant untuk melakukan proses kontrol, sehingga memerlukan semua dalam yang tersedia diukur atau diakses. Namun, jika beberapa tidak dapat diukur, mengestimasi state-state tersebut berdasarkan model dan keluaran diukur. berfokus perancangan pengendali...

This paper studies the lateral control problem for intelligent vehicles based on concept of shared control. Considering participation drivers in loop, a control-based controller is designed, which consists two differed controllers: one an LQR-based autonomous driving and other driver’s intention-based fuzzy controller. For vehicle dynamic model with two-degrees freedom, LQR are designed. Then, ...

Linear Quadratic Regulator (LQR) design is one of the most classical optimal control problems, whose well-known solution an input sequence expressed as a state-feedback. In this work, finite-horizon and discrete-time LQR solved under stability constraints uncertain system dynamics. The resulting feedback controller balances cost value closed-loop stability. Robustness modeled using scenario app...

This paper explores the applicability of a Linear Quadratic Regulator (LQR) controller design to the problem of bipedal stance on the Minitaur [1] quadrupedal robot. Balancing the body on only the rear legs affords the possibility of using the front legs for other tasks such as manipulation or bracing. Restricted to the sagittal plane, this behavior exposes a 3DOF (degree of freedom) double inv...

This article studies the robustness of policy iteration in context continuous-time infinite-horizon linear quadratic regulator (LQR) problem. It is shown that Kleinman's algorithm small-disturbance input-to-state stable, a property stronger than Sontag's local stability but weaker global stability. More precisely, whenever error each bounded and small, solutions are also enter small neighborhoo...

<p>A two-wheeled self-balancing robot (TWSBR) is an underactuated system that inherently nonlinear and unstable. While many control methods have been introduced to enhance the performance, there no unique solution when it comes hardware implementation as robot’s stability highly dependent on accuracy of sensors robustness electronic systems. In this study, a TWSBR controlled by embedded N...