• Nonlinear Functional Analysis and Applications
• /
• v.26 no.4
• /
• pp.839-853
• /
• 2021

Let 𝕽ⁿ be an Euclidean space and g : 𝕽ⁿ → 𝕽ⁿ be a monotone and continuous mapping. Suppose the convex constrained nonlinear monotone equation problem x ∈ 𝕮 s.t g(x) = 0 has a solution. In this paper, we construct an inertial-type algorithm based on the three-term derivative-free projection method (TTMDY) for convex constrained monotone nonlinear equations. Under some standard assumptions, we establish its global convergence to a solution of the convex constrained nonlinear monotone equation. Furthermore, the proposed algorithm converges much faster than the existing non-inertial algorithm (TTMDY) for convex constrained monotone equations.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.10
• /
• pp.4971-4987
• /
• 2019

Node localization is the basic task of underwater wireless sensor networks (UWSNs). Most of the existing underwater localization methods rely on ranging accuracy. Due to the special environment conditions in the ocean, beacon nodes are difficult to deploy accurately. The narrow bandwidth and high delay of the underwater acoustic communication channel lead to large errors. In order to reduce the ranging error and improve the positioning accuracy, we propose a localization algorithm based on ranging correction and inertial coordination. The algorithm can be divided into two parts, Range Correction based Localization algorithm (RCL) and Inertial Coordination based Localization algorithm (ICL). RCL uses the geometric relationship between the node positions to correct the ranging error and obtain the exact node position. However, when the unknown node deviates from the deployment area with the movement of the water flow, it cannot communicate with enough beacon nodes in a certain period of time. In this case, the node uses ICL algorithm to combine position data with motion information of neighbor nodes to update its position. The simulation results show that the proposed algorithm greatly improves the positioning accuracy of unknown nodes compared with the existing localization methods.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.35 no.7
• /
• pp.627-632
• /
• 2007

Dual quaternion is efficient methodology to express rotation and translation of the vehicle's movements in the unified frame work. Recently, a strapdown inertial navigation algorithm based on dual quaternion was introduced. By comparing and analyzing the classical and dual-quaternion algorithms, this paper proposes a new strapdown inertial navigation algorithm that maintains the accuracy benefit of the dual-quaternion algorithm with considerable computational reduction. Simulation results show the efficiency of the proposed hybrid strapdown navigation algorithm.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.856-859
• /
• 1996

In this paper, a coarse alignment algorithm for strapdown inertial navigation system is proposed and evaluated analytically. The algorithm computes roll and pitch angles of the vehicle using accelerometer outputs, and then determines yaw angle with gyro outputs. It is referred, as two-step coarse alignment in this work. With the geometric relation between sensor outputs and roll, pitch and yaw angles, the algorithm error is analytically derived and compared with the previous coarse alignment algorithm introduced by Britting. The results show that the proposed two-step coarse alignment algorithm has better performance for pitch angle computation.

• Nonlinear Functional Analysis and Applications
• /
• v.29 no.2
• /
• pp.393-418
• /
• 2024

In this paper, we propose a new inertial subgradient extragradient algorithm with a new linesearch technique that combines the inertial subgradient extragradient algorithm and the KrasnoselskiiMann algorithm. Under some suitable conditions, we prove a weak convergence theorem of the proposed algorithm for finding a common element of the common solution set of a finitely many variational inequality problem and the fixed point set of a nonexpansive mapping in real Hilbert spaces. Moreover, using our main result, we derive some others involving systems of variational inequalities. Finally, we give some numerical examples to support our main result.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.58 no.5
• /
• pp.1010-1018
• /
• 2009

An inertial navigation system for pedestrian position tracking is proposed, where the position is computed using inertial sensors mounted on shoes. Inertial navigation system(INS) errors increase with time due to inertial sensor errors, and therefore it needs to reset errors frequently. During normal walking, there is an almost periodic zero velocity instance when a foot touches the floor. Using this fact, estimation errors are reduced and this method is called the zero velocity updating algorithm. When implementing this zero velocity updating algorithm, it is important to know when is the zero velocity interval. The gait states are modeled as a Markov process and each state is estimated using the hidden Markov model smoother. With this gait estimation, the zero or nearly zero velocity interval is more accurately estimated, which helps to reduce the position estimation error.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.672-675
• /
• 1996

This paper presents algorithm including Kalman filter for transfer alignment of velocity and quaternion matching method, when master inertial navigation system is a gimbled type and slave inertial navigation system is a strapdown type on a cruising ship which is naturally in motion of horizontal axis attitude. And relative attitudes are considered on a measurement equation for quaternion matching between master INS and slave INS.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.2
• /
• pp.133-140
• /
• 2008

In this paper, a small and effective attitude estimation system for a humanoid robot was developed. Four small inertial sensors were packed and used for inertial measurements(3D accelerometer and three 1D gyroscopes.) An effective 3D pose estimation algorithm for low cost DSP using an extended Kalman filter was developed and evaluated. The 3D pose estimation algorithm has a very simple structure composed by 3 modules of a linear acceleration estimator, an external acceleration detector and an pseudo-accelerometer output estimator. The algorithm also has an effective switching structure based on probability and simple feedback loop for the extended Kalman filter. A special test equipment using linear motor for the testing of the 3D pose sensor was developed and the experimental results showed its very fast convergence to real values and effective responses. Popular DSP of TMS320F2812 was used to calculate robot's 3D attitude and translated acceleration, and the whole system were packed in a small size for humanoids robots. The output of the 3D sensors(pitch, roll, 3D linear acceleration, and 3D angular rate) can be transmitted to a humanoid robot at 200Hz frequency.

• Journal of Ocean Engineering and Technology
• /
• v.26 no.5
• /
• pp.81-86
• /
• 2012

Unmanned underwater vehicles have many applications in scientific, military, and commercial areas because of their autonomy. In many cases, an underwater vehicle adopts a control algorithm based on a tactical inertial sensor for precise control. However, a control algorithm that uses a tactical inertial sensor is unsuitable for some underwater vehicle missions such as torpedo decoys. This paper proposes a control algorithm for an unmanned underwater vehicle that does not require precise control. The control algorithm proposed for an unmanned underwater vehicle adopts a low cost MEMS inertial sensor, and simulations using the specifications of the MEMS inertial sensor under development are performed to verify the control algorithm under a real environment. The results of these simulations are presented.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.1671-1674
• /
• 1997

In tihs paper, an acceleratiion transformation algorithm which compensates the sculling error is proposed for strapdown inertial navigation system. The algorithm utilize the corss-product of the acceleromenter outputs and gyro outputs to keep the accuracy of the vehicle velocity under high frequency dynamic motion. From the error analysis of the algorithm, it is shown that the magnitude of estimation error is reduced by four orders.