Control of the Force exerted on an object is important for boosting system performance in robotics manipulators. Any undesired applied Force may leave remarkable effects on the system, with the potential to damage the object. In addition, measuring external Force is another challenge associated with such cases. Proposing an appropriate Force estimation algorithm is a solution to overcome this deficiency. In this research, a Control strategy is proposed to Control the external Force applied on the n-dof robotics. To eliminate Force measurement in the Controller, a Force estimation strategy based on a disturbance observer is employed. Subsequently, a sliding-mode based Control is implemented to cope with the Force estimation error. The closed-loop stability of the system in the presence of estimated Force is analytically considered. The proposed algorithm was implemented on piezoelectric actuators as the experimental setup. The experimental results confirm that by employing the proposed Control scheme, precise Force Control is achievable. The Force estimation algorithm can also suitably estimate external Force.

Micro ultrasonic machining (Micro-USM) is a process with a great capability to generate micro features in hard and brittle materials. Despite some developments in micro-USM process, issues such as precision measurement and Control of the machining Force, which is crucial for stable machining conditions, need further investigations. In this paper, the precision measurement and Control of the machining Force is studied using a newly-developed Force measurement configuration. The results of the Force measurement for different levels of static Force, abrasive particle size and amplitude of vibration demonstrated that the variation of measured machining Force increases at higher static Forces. Furthermore, a better Control over the static load was acquired when feeding the abrasive slurry with particle size of 0.37 mm as compared to 1 mm and 3 mm particles leading to more stable machining conditions in micro-USM process. Finally, applying lower levels of vibration amplitude to the work piece resulted in more stable machining conditions and lower static load errors.

In this paper we present a robust hybrid motion/Force Control1er for rigid robot manipulators. The main contribution of this paper is that the proposed hybrid Control system is able to at complies motion objectives in free directions and Force objectives in constrained directions under parametric uncertainty both in robot dynamics and stiffness constraint constant. Also, the given scheme is proved global1y stable in the sense that the Control objectives are achieved asymptotically, when a signum function is used in the Control law, though giving rise to chattering effects. To avoid this problem a saturation function is used. In this case the motion and Force errors are proved to be bounded functions. Using the proposed Control structure there is no need to measure the derivative of the interaction Forces. Some simulation results are given to illustrate the Control system performance.

Bearing-less induction motors (BLIMs) are suitable candidates for high-speed applications but suffer from low torque density and complex Control issues due to the interaction of torque and levitation Forces. To address these challenges, this paper presents a new Control strategy that combines vector Control and direct torque Control (DTC) for torque management, alongside a novel Force Control method based on finite element analysis (FEA). The proposed approach minimizes interference between torque and Force magnetic fields by employing a parallel winding structure and distinct Control units for torque and Force. Simulation results demonstrate that the proposed method significantly reduces torque ripple and improves steady-state performance compared to conventional vector Control and DTC. Furthermore, the Force Control unit outperforms a dual field-oriented Control (FOC) method in regulating rotor position, offering better suspension Force Control and faster stabilization. This work contributes to the development of more efficient Control strategies for BLIMs, enhancing their performance in industrial applications.