03694ntm a2200337 i 4500003000800000005001700008006001900025007000300044008004100047020003300088040002700121090002900148100004500177245012600222264003900348264001200387300005800399336002100457337002500478338002300503347002400526500005400550502007100604504004000675520246600715610006903181650004503250650002603295942001603321999001903337MY-KuUP20260407130142.0t||||fr|||| 000 0 ta260407t20252025my a|||fr|||| 000 0 eng d  aTHE0010441 (Local)qHardback  aUMPSAbengcUMPSAerda  aFTKEE .A94 2025 r Thesis1 aMohd Iskandar Putra Bin Azahar,eauthor.10aImproved prescribed performance control for dynamic motion of a pneumatic gripper robot /cMohd Iskandar Putra Bin Azahar 1aKuantan, Pahang :bUMPSA,c© 2025 4c© 2025  axx, 163 pages ;billustrations ;c30 cm. +e1 CD-ROM.  2rdacontentatext  2rdamediaaunmediated  2rdacarrieravolume  2rdaatext filebPDF  aFaculty of Electrical and Electronics Engineering  aThesis (Doctor of Philosophy) -- Universiti Malaysia Pahang - 2025  aIncludes bibliographical references3 aPneumatic robots offer significant advantages in compliance, power-to-weight ratio, and speed, but their use is hindered by significant control challenges. The inherent nonlinearities from air compressibility, stiction, and friction, combined with unmodeled system uncertainties and sudden external disturbances, cause conventional model-free control methods (like standard PID) to struggle. This results in poor tracking performance, oscillations, and instability, particularly during dynamic tasks. This research addresses this gap by proposing and validating the progression of adaptive Prescribed Performance Control (PPC) methods. These methods are integrated with a PID inner-loop to guarantee high performance for a tri-pneumatic grasper (TPG) robot without requiring a complex system model. The methodology first addresses finger positioning by developing a Finite-Time PPC (FT-PPC), which solves the asymptotic convergence of conventional PPC, enabling user-defined settling times. For the more dynamic task of pressure regulation, a Variable Convergence Rate PPC (VCRPPC) is introduced to provide a more flexible and aggressive adaptive control envelope. Finally, to ensure safe physical interaction, a Dynamic Error PPC (DEPPC) is formulated to solve the critical problem of control singularity, incorporating a pressure-based force estimator to robustly manage external forces. Experimental results from the physical TPG testbed validate the efficacy of each proposed controller in its specific domain. The FT-PPC eliminated overshoot and achieved a 0.3-second settling time with a 49% improvement in rise time for positioning. The VCRPPC excelled in pressure regulation, demonstrating a 63% faster transient response and a 78% reduction in steady-state error. Most critically, the DEPPC proved robust for dynamic interaction, achieving an 84% faster rise time and a 78% reduction in tracking error under applied forces, all while successfully preventing the control singularity that caused other controllers to fail. In conclusion, this progressive development of adaptive PPC methods provides a significant contribution by demonstrating a clear pathway to achieving high-performance, guaranteed control for complex pneumatic systems. The proposed frameworks successfully enhance the TPG's static and dynamic control, improving response time, accuracy, and stability, proving their practical effectiveness for advanced pneumatic robotic challenges.20aFaculty of Electrical and Electronics EngineeringxDissertations 0aUniversities and collegesxDissertations 0aThesesxDissertations  2lcccTHESIS  c104643d104649