Robotic and mechatronic systems, autonomous vehicles, electric power systems and smart grids, as well as manufacturing and industrial production systems can exhibit complex nonlinear dynamics or spatio-temporal dynamics which need to be controlled to ensure good functioning and performance.
In this comprehensive reference, the authors present new and innovative control and estimation methods and techniques based on dynamical nonlinear and partial differential equation systems. Such results can be classified in five main domains for the control of complex nonlinear dynamical systems using respectively methods of approximate (local) linearization, methods of exact (global) linearization, Lyapunov stability approaches, control and estimation of distributed parameter systems and stochastic estimation and fault diagnosis methods.
Control and Estimation of Dynamical Nonlinear and Partial Differential Equation Systems: Theory and applications will be of interest to electrical engineering, physics, computer science, robotics and mechatronics researchers and professionals working on control problems, condition monitoring, estimation and fault diagnosis and isolation problems. It will also be useful to skilled technical personnel working on applications in robotics, energy conversion, transportation and manufacturing.
Inspec keywords: manipulators; nonlinear control systems; electropneumatic control equipment; partial differential equations; control system synthesis; mobile robots; optimal control; position control; electrohydraulic control equipment; adaptive control
Other keywords: electropneumatic control equipment; position control; optimal control; partial differential equations; control system synthesis; mobile robots; manipulators; dynamical nonlinear control systems; adaptive control; electrohydraulic control equipment
Subjects: Manipulators; Control system analysis and synthesis methods; Electrohydraulic and electropneumatic control equipment; Spatial variables control; General and management topics; Self-adjusting control systems; Nonlinear control systems; Optimal control; Mobile robots; Mathematical analysis
The chapter analyzes established concepts in the control of non-linear and PDE dynamical systems. The following main approaches for the control of complex non-linear dynamical systems are considered (i) control with methods of approximate (local) linearization being associated with the solution of the non-linear optimal control problem, (ii) control with methods of exact (global) linearization comprising also adaptive control methods and (iii) control of distributed parameter systems (systems which are described by partial differential equations) and stochastic estimation methods. In (i) one can distinguish a novel non-linear optimal (H-infinity) control method. In (ii) one can distinguish flatness-based control for non-linear dynamical systems with known model and adaptive flatness-based control in the case of systems with the unknown model. In (iii) one can distinguish a flatness-based boundary control approach for PDEs which is implemented in successive loops.
The chapter analyzes methods and presents results on control and estimation based on approximate linearization for robotic systems: (i) nonlinear control of the cart and double-pendulum overhead crane, (ii) nonlinear control of the underactuated offshore crane, (iii) nonlinear control of the inertia wheel and pendulum system, (iv) nonlinear control of the torsional oscillator with rotational actuator, (v) nonlinear control of robotic exoskeletons, (vi) nonlinear control of brachiation robots, (vii) Nonlinear control of power line inspection robots, (viii) nonlinear control of robots with electrohydraulic actuators, (ix) nonlinear control of robots with electropneumatic actuators, (x) nonlinear control of flexible joint robots, (x) nonlinear control of redundant robotic manipulators, and (xi) nonlinear control of parallel closed-chain robotic manipulators.
The chapter analyzes methods and presents results on control and estimation based on approximate linearization for autonomous vehicles: (i) nonlinear control of tracked autonomous vehicles, (ii) nonlinear control of the autonomous fire-truck, (iii) nonlinear control of the truck and N-trailer system, (iv) nonlinear control of the ball-bot autonomous robot, (v) Nonlinear control of the ball-and-plate dynamical system, (vi) nonlinear control of 3-DOF unmanned surface vessels, (vii) nonlinear control of the 3-DOF autonomous underwater vessel, (viii) nonlinear control of the Vertical Take-off and Landing Aircraft, (ix) nonlinear control of aerial manipulators, (x) Nonlinear control of the 6-DOF autonomous octocopter, and (xi) nonlinear control of hypersonic aerial vehicles.
The chapter analyzes methods and presents results on control and estimation based on approximate linearization for energy conversion systems: (i) Nonlinear control of the VSI-fed three-phase PMSM, (ii) Nonlinear control of the VSI-fed six-phase PMSMs, (iii) Nonlinear control of DC electric microgrids, (iv) Nonlinear control of distributed marine power generation units, (v) Nonlinear control of PMLSGs in wave energy conversion systems, (vi) Nonlinear control of Permanent Magnet Brushless DC motors, (vii) Nonlinear optimal control of Hybrid Electric Vehicles powertrains, (viii) Nonlinear control of shipboard AC/DC microgrids and (ix) Nonlinear control of power generation in hybrid AC/DC microgrids.
The chapter analyzes methods and presents results on control and estimation based on approximate linearization for mechatronic systems: (i) nonlinear control of electrohydraulic actuators, (ii) nonlinear control of electropneumatic actuators, (iii) nonlinear control of hot-steel rolling mills, (iv) nonlinear control of paper mills, (v) nonlinear control of the injection moulding machine, (v) nonlinear control of the slosh-container system dynamics, (vi) nonlinear control of micro-satellites' attitude dynamics and (vi) nonlinear control of the industrial crystallization process.
The chapter analyses methods and presents results on control and estimation based on global linearisation for industrial and PDE systems: (i) control of a robotic exoskeleton subject to time-delays, (ii) adaptive control of synchronous reluctance machines, (iii) control of a mobile robotic manipulator (iv) state-of-charge estimation in EVs with a Kalman Filter-based disturbance observer, (v) control of nonlinear wave PDE dynamics, (vi) control of PDE diffusion dynamics for bandwidth allocation in internet routes, (vii) control of diffusion PDE for data flow management in communication networks, (viii) control of the diffusion PDE in Li-ion batteries, (ix) control of the diffusion PDE in industrial assets' management, (x) estimation of PDE dynamics of the highway traffic and (xi) estimation of the PDE dynamics of a cable-suspended bridge.