Active Force Control

— Anti-lock braking systems (ABS) are safety and control devices implemented in ground vehicles that prevent the wheel lock-up during panic braking. The existing ABS controls have the ability to regulate the level of pressure to optimally maintain the wheel slip within the vehicle stability range. However, the ABS shows strong nonlinear characteristics in which the vehicles equipped with the existing controllers can still have a tendency to oversteer and become unstable. In this paper, a new intelligent robust control method based on an active force control (AFC) strategy is proposed via a rigorous simulation study. It is designed and implemented in a hybrid form by having the AFC loop associated with an iterative learning (IL) algorithm cascaded in series with a self-tuning fuzzy logic (FL)-based proportional-integral-derivative (PID) control for the effective overall performance of the proposed ABS. Both the IL and FL techniques are for the appropriate acquisition and computation of the important parameters in the controller. From the results, it is evident that the FL-PID with ILAFC scheme shows faster and better response compared to the FL-PID and FL-PID+AFC controllers in the wake of the given load and operating conditions. The incorporation of the AFC-based scheme into the ABS serves to provide an enhanced and robust performance that has the potentials to be implemented in a practical and real-time system.

Featured Application: Assembly tasks with industrial robot manipulators. Abstract: Industrial robot manipulators are playing a more significant role in modern manufacturing industries. Though peg-in-hole assembly is a common industrial task which has been extensively researched, safely solving complex high precision assembly in an unstructured environment remains an open problem. Reinforcement Learning (RL) methods have been proven successful in solving manipulation tasks autonomously. However, RL is still not widely adopted on real robotic systems because working with real hardware entails additional challenges, especially when using position-controlled manipulators. The main contribution of this work is a learning based method to solve peg-in-hole tasks with position uncertainty of the hole. We proposed the use of an off-policy model-free reinforcement learning method and bootstrap the training speed by using several transfer learning techniques (sim2real) and domain randomization. Our proposed learning framework for position-controlled robots was extensively evaluated on contact-rich insertion tasks on a variety of environments.

This study examines how cultural performance orientation moderates the influence of human resource management (HRM) controls on boundary-spanning employees' behavioural strategies and satisfaction. Based on primary data obtained from 1049 salespeople in six countries (France, Ireland, Italy, Spain, United Kingdom, and the United States of America) and secondary data on cultural performance orientation, multilevel regression analyses show that national culture has a strong effect on the way boundary-spanning employees allocate their effort in response to HRM control. In particular, our results suggest that the more behaviour controls are used with boundary-spanning employees, the less attention they pay to customers and the more emphasis they place on their supervisors and non-selling tasks. Specifically, cultural performance orientation is shown to moderate significantly those relationships. Furthermore, results indicate that cultural performance orientation heightens boundary-spanning employees' job satisfaction resulting from behaviour control. Preliminary explanations for the differing impact of HRM control efficiency across cultures can be proposed.

This paper investigates the anti-synchronization of identical hyperchaotic Bao systems (Bao and Liu, 2008), identical hyperchaotic Xu systems (Xu, Cai and Zheng, 2009) and non-identical hyperchaotic Bao and hyperchaotic Xu systems. Active nonlinear control has been deployed for the anti-synchronization of the hyperchaotic systems addressed in this paper and the main results have been established using Lyapunov stability theory. Since the Lyapunov exponents are not required for these calculations, the active nonlinear control method is very effective and convenient to achieve anti-synchronization of identical and non-identical hyperchaotic Bao and hyperchaotic Xu systems. Numerical simulations have been provided to validate and demonstrate the effectiveness of the anti-synchronization results for the hyperchaotic Cao and hyperchaotic Xu systems.

The Anti-lock braking system (ABS) is the most common safety system in the vehicles, which works to increase the generating braking force between the tire and the road surface in way to keep the stability in vehicles during braking. The high nonlinearity due to the interaction between the tire and road, the uncertainties in vehicle dynamics always exist and using the standard PID controller will not be accurate enough to the extent required to deal with the uncertainties. Two robust control techniques, the sliding mode control (SMC) and an intelligent active force control (AFC) that both of them deal with the dynamic systems to provide durability and quell the unrest that may found in the system. In this paper highlights the ability of this proposed technique to improve the dynamic system robustly by combining them with standard PID in one control scheme (PID-AFC) comparing with (PID-SMC). Results showed the robustness of AFC and solo performance to improving the slip track without chattering phenomenon and thus reduce the stopping distance of the vehicle compared to other control schemes.

Patanjali, foremost exponent of Yoga, described pranayama as the gradual unforced cessation of breathing. Pranayama is derived from two Sanskrit words-prana (life) or yama (control). Pranayam or control of prana or life force yields heart beat pulse and mind control. Yoga combines scientific technique of right behavior (Yama-Niyama), proper posture (asana), life force control (pranayama), interiorisation of the mind (pratyahara),

... Akash Deodhar, Panos S. Shiakolas, Sunil Belligundu H ... D. Ghosh, A. Deshmukh, C. Carrillo, L. Gibson, Design of a Microfabrication Manufacturing System Based on Hot Embossing Technology, TexMEMS Conference, Arlington, TX, USA, 2003 [6] Aditya Deshmukh, Analyis ...

Antilock braking systems (ABS) are safety and control devices implemented in ground vehicles that prevent the wheel lock-up during panic braking. The existing ABS controls have the ability to regulate the level of pressure to optimally maintain the wheel slip within the vehicle stability range. However, the ABS shows strong nonlinear characteristics in which the vehicles equipped with the existing controllers can still have a tendency to oversteer and become unstable. In this paper, a new intelligent robust control method based on active force control (AFC) strategy is proposed via a simulation study. It is designed and implemented in a hybrid form by having the AFC loop directly cascaded in series with a fuzzy logic (FL) self-tuning proportional-integral-derivative (PID) control as the outermost loop position control for the effective overall performance. From the results, it is evident that FL-PID with AFC scheme shows faster and better response compared to the classic PID controller for the given loading and operating conditions. The incorporation of the AFC-based scheme into the ABS serves to provide enhanced performance that has great potentials to be implemented in real-time system.