浅井 佑仁

This paper addresses the control problem of an autonomous bicycle. Conventional control methods based on linearized models face difficulties in sufficiently accounting for physical phenomena, such as the strong nonlinearities associated with large roll and steering angles. To overcome these challenges, this research applies nonlinear control to the complex bicycle system, aiming to achieve stability over a broader operating range compared to linear control. By transforming the system into a Takagi-Sugeno fuzzy model and applying state-feedback control inputs, an efficient controller is designed to handle nonlinear characteristics. Furthermore, the effectiveness of the proposed method is demonstrated through simulations of balancing control.

This paper proposes a simplified lateral motion model for a Powered Paraglider (PPG) based on actual flight experiments. First, we propose a new motion model and determine some unknown parameters by conducting flight experiments. This approach enables the construction of the model that accounts for the effects of counter torque. Next, we verify the accuracy of the proposed model by comparing the simulation results directly with the measured flight data. Finally, a nonlinear fuzzy controller is designed based on the proposed model. The effectiveness of our approach is validated in a simulation.

As an effective framework for handling nonlinear systems, we propose an output feedback control design with a guaranteed cost for Takagi-Sugeno fuzzy systems, which can represent a wide class of nonlinear systems. In practical systems, since not all system states can be measured, the design of an output-feedback controller is essential. In this paper, we consider guaranteed cost control that can take into account not only the stabilization of the fuzzy system but also its control performance. The proposed design condition is formulated in terms of linear matrix inequalities via a Lyapunov function that involves special functions obtained by integrating the membership functions. Finally, a numerical example is provided to verify the effectiveness of the proposed controller.

Thisstudyproposesanovelapproachthatappliesfuzzylogictoenhancethepathplanningperformanceofautonomous mobile robots operating in environments with both static and dynamic obstacles. Conventional Dynamic Window Approach (DWA) is effective for static obstacles; however, in complex environments it often results in unnecessary detours or stops, and in the presence of dynamic obstacles, collision risks remain. To address these limitations, the proposed method dynamically adjusts the evaluation function parameters in real time through fuzzy inference, using the distances to the goal and to obstacles as inputs. Simulation results confirm that, under complex environments including dynamic obstacles, the proposed method achieves more efficient and safer path planning compared to the conventional DWA.

This paper presents a 3D control approach for a flying-wing unmanned aerial vehicle. By converting its high-precision model into a Takagi-Sugeno fuzzy model, it is possible to design a controller to stabilize its complex 3D motion. Finally, the simulation results demonstrate the effectiveness of the designed 3D controller.

This paper presents a control approach for straight path tracking and parking of an autonomous bicycle. A simplified model of the autonomous bicycle is constructed by adding the dynamics regarding a bank angle to a conventional four-wheeled vehicle model. The control objective is achieved by extending a fuzzy-system-based control approach developed for four-wheeled vehicles.

We provide a new design condition for Takagi-Sugeno fuzzy descriptor system with norm-bounded time varying uncertainties. Our obtained condition guarantees a stability of the closed loop system and a norm bounded constraints for all uncertainties in the system parameters. In this paper, to reduce the conservativeness in a design condition, we propose a Lyapunov function candidate with integral functions of the membership functions. Furthermore, some lemmas are used for obtaining a less conservative and a linear matrix inequalities (LMIs) based design condition.

We discuss the robust stability and control design for uncertain Takagi-Sugano fuzzy descriptor system that can contain not only differential equations but also algebraic equations. The fuzzy system can accurately describe nonlinear systems because it is composed of multiple local subsystems and membership functions, but modeling error absolutely occurs when we obtain a mathematical model via system identification. Therefore, in order to improve the quality of the fuzzy controller, we propose a control design condition for Takagi-Sugano descriptor fuzzy system including uncertainties by using multiple Lyapunov function, which uses the integral structure of the membership function. Numerical example is given to show the effectiveness of the proposed approach.

This paper discusses robust stabilization for fuzzy systems with uncertainties in Takagi-Sugano fuzzy model. In actual system control, model errors always exist in system parameters obtained through system identification. Therefore, in order to improve control quality of a fuzzy controller, it is necessary to consider a control design for the fuzzy systems with the uncertainties of the system parameters. In this paper, we propose a new controller based on Lyapunov function that includes integral functions of membership functions for fuzzy system with uncertainties.

We discuss the problem of guaranteed cost control for systems. In control field, Takagi-Sugeno fuzzy model that can represent a large class of systems is widely utilized. Especially, Takagi-Sugeno fuzzy systems in descriptor form is attracting much attention due to handling physical restriction of the systems. In the literature, a less conservative admissibility conditions were proposed via Lyapunov function using an integral function of a membership function. In this paper, we propose a guaranteed cost controller that can consider not only admissibility but also consider a control performance for fuzzy descriptor systems, furthermore, we propose an algorithm on a minimization of cost function. In final section, we show meaningful result for our proposed method.

This paper is concerned with a mixed control problem of H∞ disturbance attenuation control and guaranteed cost control for nonlinear systems, which are modelled by Takagi-Sugeno fuzzy model. We propose a controller that not only attenuates the disturbance but also improves the control performance based on multiple Lyapunov function, which uses the integral of the membership function. Finally, a numerical example is provided to illustrate the validity of the proposed approach.

This paper is concerned with the problem of designing fuzzy controller for Takagi-Sugeno fuzzy models. Many results and improvements regarding stabilization issues have been proposed for Takagi-Sugeno fuzzy system. In the literature, stabilization conditions for Takagi-Sugeno fuzzy system has been improved and its stabilization area has been expanded. However, there is still room to reduce the conservativeness for design condition. In this paper, a new fuzzy controller via a Lyapunov function with double integral of the membership functions is proposed. Our proposed stabilization conditions are derived based on higher order derivatives of the Lyapunov function, which reduces the existing conservative design condition. Finally, an illustrative example is given to show the effectiveness of our control design method by comparing with the previous work.

This paper presents the stabilization using dynamic output feedback controller for Takagi-Sugeno fuzzy systems that can represent nonlinear systems accurately. Many different stabilization conditions by state feedback control have been obtained in the literature. However, few papers have considered stabilizing output feedback controllers, which is useful for practical systems, of Takagi-Sugeno fuzzy systems. Therefore, we propose a control design based on dynamic output feedback controllers in this paper. Based on the idea of Lyapunov function having the structure of the integral of the membership functions, new stabilization conditions are obtained. This approach is known to reduce the conservativeness of the stabilization conditions. Furthermore, relaxation lemmas are used to reduce the conservativeness of the conditions. Finally, numerical examples are given to show the effectiveness of the design methods presented in the paper.

This paper is concerned with the problem of guaranteed cost control for Takagi-Sugeno fuzzy systems. Since all state is not necessarily obtained in a real system, we introduce the output feedback control design with guaranteed cost. A guaranteed cost control not only stabilizes systems but also considers a control performance. In this paper, output feedback control design of controller with guaranteed cost is proposed. Finally, an illustrative example is given to show the effectiveness of our propose.

This paper introduces a new static output feedback controller design method for continuous-time Takagi-Sugeno fuzzy systems, which can represent a wide class of nonlinear systems. Although many papers discuss state feedback controller design for fuzzy sytems, a fewer number of papers consider an output feedback controller design due to its difficulty. In this paper, our target is to propose an output feedback controller design method. In our control design, the integral structure of the membership functions, which are the same properties as the original membership functions, is utilized. A similar approach for state feedback controller design methods has been in the literature. Our proposed output feedback controller is designed based on a new fuzzy Lyapunov function which includes the double integral of the original membership functions of the system, and it shows a wider stabilizing area than the existing methods. At the end of the paper, a numerical example is provided to illustrate the newly proposed controller design method and to asymptotically stabilize the system.

This paper presents a stabilization condition of Takagi-Sugeno fuzzy systems via static output feedback controller. Many papers discuss state feedback controller design but a fewer number of papers propose output feedback controller design. Since many physical systems that appear in our real society are a nonlinear system and it is rare that all the states of the systems are measurable, output feedback control design is important. Based on the idea of Lyapunov function that has the integral of the membership function, a new static output feedback controller is proposed. At the end of the paper, a numerical example illustrates the newly proposed controller design condition.