LEADER 03554nam 2200469 450 001 9910583384703321 005 20230120002721.0 010 $a0-12-813464-X 010 $a0-12-813380-5 035 $a(CKB)4100000001786954 035 $a(CaSebORM)9780128134641 035 $a(MiAaPQ)EBC5217417 035 $a(EXLCZ)994100000001786954 100 $a20180209h20182018 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aPID control with intelligent compensation for exoskeleton robots /$fWen Yu 205 $aFirst edition. 210 1$aLondon, England :$cAcademic Press,$d2018. 210 4$dİ2018 215 $a1 online resource (236 pages) $cillustrations 320 $aIncludes bibliographical references and index. 327 $aPreliminaries -- Stable PID control and systematic tuning of PID gains -- PID control in task space -- PD control with neural compensation -- PID control with neural compensation -- PD control with fuzzy compensation -- PD control with sliding mode compensation -- PID admittance control in task space -- PID admittance control in joint space -- Robot trajectory generation in joint space. 330 $aPID Control with Intelligent Compensation for Exoskeleton Robots explains how to use neural PD and PID controls to reduce integration gain, and provides explicit conditions on how to select linear PID gains using proof of semi-global asymptotic stability and local asymptotic stability with a velocity observer. These conditions are applied in both task and joint spaces, with PID controllers compensated by neural networks. This is a great resource on how to combine traditional PD/PID control techniques with intelligent control. Dr. Wen Yu presents several leading-edge methods for designing neural and fuzzy compensators with high-gain velocity observers for PD control using Lyapunov stability. Proportional-integral-derivative (PID) control is widely used in biomedical and industrial robot manipulators. An integrator in a PID controller reduces the bandwidth of the closed-loop system, leads to less-effective transient performance and may even destroy stability. Many robotic manipulators use proportional-derivative (PD) control with gravity and friction compensations, but improved gravity and friction models are needed. The introduction of intelligent control in these systems has dramatically changed the face of biomedical and industrial control engineering. Discusses novel PD and PID controllers for biomedical and industrial robotic applications, demonstrating how PD and PID with intelligent compensation is more effective than other model-based compensations Presents a stability analysis of the book for industrial linear PID Includes practical applications of robotic PD/PID control, such as serial sliding mode, explicit conditions for linear PID and high gain observers for neural PD control Includes applied exoskeleton applications and MATLAB code for simulations and applications 606 $aPID controllers 606 $aIntelligent control systems 606 $aRobotics 615 0$aPID controllers. 615 0$aIntelligent control systems. 615 0$aRobotics. 676 $a629.8 700 $aYu$b Wen$c(Robotics engineer),$0760806 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910583384703321 996 $aPID control with intelligent compensation for exoskeleton robots$92132345 997 $aUNINA