This paper presents a heterogeneous configuration of the multirotor unmanned aerial system (UAS) ... more This paper presents a heterogeneous configuration of the multirotor unmanned aerial system (UAS) that features the combined characteristics of the helicopter and quadrotor in a single multirotor design, featuring the endurance and energy efficiency similar to a helicopter, while keeping the mechanical simplicity, control, and manoeuvrability of the standard quadrotor. Power needed for a rotorcraft to hover has the inverse relation with the rotor disc. Therefore, multiple small rotors of the quadrotor are energetically outperformed by a large rotor of the helicopter, for a similar size. Designing the stable control system for such a dynamically complex multirotor configuration remains the main challenge as the studies previously carried out on these designs have successfully demonstrated energy efficiency but at the cost of degraded attitude control. Advancements in the energetics of the multirotor results in enhanced endurance and range that could be highly effective in remote opera...
Journal of Automation, Mobile Robotics and Intelligent Systems
Different from conventional aircraft, an investigation on system identification and control desig... more Different from conventional aircraft, an investigation on system identification and control design has been carried out on a small fixed wing unmanned aerial vehicle (UAV) with a multi-segment ailerons. The multi-segment aileron setup is configured as a multi-input and single-output system and each segment is modeled as a control input. Experiments are conducted in a wind tunnel to determine the frequency responses of the system and the corresponding transfer functions. Multiple PID controllers are designed and implemented in a cascaded form for each control surface. Furthermore, a heuristic switching control strategy is implemented for the aircraft where the multi-segment ailerons perform as a single-segment aileron in a normal flight condition, and adapts to multi-segment control when encountering severe turbulence or a large angle reference change. Experimental results reveal that although each control surface has the capability for stabilization of the aircraft, the proposed con...
In this paper input power, as opposed to the usual input amplitude, constraints are introduced in... more In this paper input power, as opposed to the usual input amplitude, constraints are introduced in the context of intermittent control. They are shown to result in a combination of quadratic optimisation and quadratic constraints. The main motivation for considering input power constraints is its similarity with semi-active control. Such methods are commonly used to provide damping in mechanical systems and structures. It is shown that semi-active control can be re-expressed and generalised as control with power constraints and can thus be implemented as power-constrained intermittent control. The method is illustrated using simulations of resonant mechanical systems and the constrained nature of the power flow is represented using power-phaseplane plots. We believe the approach we present will be useful for control design of both semi-active and low-power vibration suppression systems.
This paper deals with data-driven predictive control for relative performance management in virtu... more This paper deals with data-driven predictive control for relative performance management in virtualized software system. The system dynamics are characterized in Hammerstein-Wiener structure to capture nonlinear and linear characteristics. The proposed control approach is the implementation of Subspace-based Predictive Control with the integration of nonlinear compensation. The compensator functions are inverse static input and output nonlinearity models from the Hammerstein-Wiener system identification. The subspace predictors are formulated from the linear model input and output of Wiener block. The experimental results from three scenarios of performance objectives show the reliability of Subspace-based Predictive Control to manage the virtualized software system.
This paper develops a new design method for predictive repetitive control systems to track period... more This paper develops a new design method for predictive repetitive control systems to track periodic reference signals or reject disturbances with bandlimited frequency content. In the presence of input disturbances acting on the system, the new design estimates these disturbances using an observer. This approach is complementary to the predictive repetitive control system designs previously reported where the periodic disturbance model was embedded in the controller. Supporting experimental results from application of the new design to a two joint robotic arm are given.
Integrating processes are widely encountered in electro-mechanical systems and other areas. Autom... more Integrating processes are widely encountered in electro-mechanical systems and other areas. Automatic tuning of PID controllers for this type of system requires special consideration since the underlying system is unstable. Using relay feedback control in a closed-loop setting, an auto-tuner is designed to systematically find the controller parameters using a frequency sampling filter model. The performance of this auto-tuner is evaluated on an electro-mechanical experimental test facility that can be configured to operate in either as a single-input, single-output or multiple-input, multipleoutput system. The experimental results demonstrate that when the interaction the between control loops is weak, the auto-tuner produces closed-loop performance that matches the specification, but this performance gradually decays as the level of interaction increases. The experimental results can also serve as experimental benchmarks to compare competing designs.
This paper addresses the performance of electric servo-actuators as part of a helicopter control ... more This paper addresses the performance of electric servo-actuators as part of a helicopter control linkage system. The development of a helicopter flight control system initially requires a non-linear model capable of accurately predicting the aircraft dynamics. The first step of this non-linear model represents the servo-actuator system, which transmits the pilots control inputs to the main rotor system. A series of system identification experiments were performed on a cyclic system servo-actuator under different operating conditions, and the servo-actuator step responses were estimated using a Frequency Sampling Filter. A performance comparison is made for a zero load bench test and the aircraft load condition in order to determine the most accurate representation of the servo-actuator dynamics for helicopter flight applications.
2008 47th IEEE Conference on Decision and Control, 2008
This paper seeks to extend Generalized Predictive Control (GPC) to tracking of trajectories in a ... more This paper seeks to extend Generalized Predictive Control (GPC) to tracking of trajectories in a periodic nature. The initial focus is on sinusoidal trajectories, but the work may be extended later on to a signal with bandlimited frequencies. In addition, this paper proposes strategies for optimizing the prefilter in GPC to improve the transient performance in setpoint tracking.
This paper develops a predictive iterative learning control algorithm starting from some recent r... more This paper develops a predictive iterative learning control algorithm starting from some recent results in the area of predictive repetitive control. Although similar in spirit to the original norm-optimal iterative learning control, the algorithm developed employs receding horizon control and Laguerre functions to parameterize the future control trajectory. As a result, difficulties encountered by the norm-optimal iterative control algorithm are overcome. The stability of the predictive iterative learning system is analyzed and conditions on error convergence are established. In addition, a strategy for learning the unknown plant initial conditions and the reduction of the initial plant errors is developed. A simulation example to illustrate the algorithm is also given.
This paper examines the design of model predictive control using nonminimal state space models, i... more This paper examines the design of model predictive control using nonminimal state space models, in which the state variables are chosen as the set of measured input and output variables and their past values. It shows that the proposed design approach avoids the use of an observer to access the state information and, as a result, the disturbance rejection, particularly the system input disturbance rejection, is significantly improved when constraints become activated. In addition, the paper shows that the system output constraints can be achieved in the proposed approach, which provides a significant improvement over the general observer based approach.
This paper derives the algorithm of integral plus finite control set (FCS)-predictive control for... more This paper derives the algorithm of integral plus finite control set (FCS)-predictive control for AC motor drives. In the paper, it is shown that the original FCS-predictive control algorithm in the d−q reference frame is equivalent to a dead-beat control system in the presence of constraints, where the closed-loop system is approximated by a unit time delay. Without integral action, the original FCS-predictive control system contains steady-state errors in both daxis and q-axis currents, hence compromising closed-loop performance. Using an integral control in a cascaded structure to the original FCS-predictive control, a simple algorithm is proposed to eliminate the steady-state errors of the current control system and improve its closed-loop performance. The sampling interval of the current control system is used as a performance tuning parameter for reduction of current variations. Furthermore, the algorithm is expressed in a velocity form for convenience in implementation using a digital signal processor. Experimental results are used to show the successful design and implementation of the integral finite control set (I-FCS) predictive control.
This paper proposes a continuous-time model predictive control design for disturbance rejection a... more This paper proposes a continuous-time model predictive control design for disturbance rejection and set-point following of periodic signals. By assuming input disturbance in the form of sinusoid, the periodic frequency is embedded into the design model. Hence, from internal model principle, the steady-state error of the model predictive control system is ensured to be zero for both disturbance rejection and set-point following. Furthermore, with the design framework of model predictive control, hard constraints on the derivative and amplitude of the control signals are imposed as part of the performance specification. Simulation studies have been used to show the efficacy of the design with or without hard constraints.
The nature of active magnetic bearings has many advantages over the conventional bearing, as its ... more The nature of active magnetic bearings has many advantages over the conventional bearing, as its operation is energy efficient and potentially leads to cleaner and noise-free environment. However, the successful operation of an active magnetic bearing system requires a complex real-time control system, because of its unstable characteristics, as well as its nature of being a multi-input and multi-output system. This paper presents design and implementation of a continuous time model predictive control algorithm (CMPC) to an active magnetic bearing system (AMB). In this application, the plant continuous time model is identified from experimental data using prediction error method. The control performance of this algorithm is studied using an experimental AMB laboratory system. A host-target development environment of real-time digital control system with hardware in the loop (HIL) is implemented and demonstrated by controlling a nonlinear, open-loop unstable, and multivariable magnetic levitation device.
A three-stage approach to system identification in the continuous-time is presented which is appr... more A three-stage approach to system identification in the continuous-time is presented which is appropriate for day-today application by plant engineers in the process industry. The three stages are: data acquisition using relay feedback; non-parametric identification of the system step response; and parametric model fitting of the identified step-response. The method is evaluated on a pilotscale food-cooking extruder.
In this paper input power, as opposed to the usual input amplitude, constraints are introduced in... more In this paper input power, as opposed to the usual input amplitude, constraints are introduced in the context of intermittent control. They are shown to result in a combination of quadratic optimisation and quadratic constraints. The main motivation for considering input power constraints is its similarity with semi-active control. Such methods are commonly used to provide damping in mechanical systems and structures. It is shown that semi-active control can be re-expressed and generalised as control with power constraints and can thus be implemented as power-constrained intermittent control. The method is illustrated using simulations of resonant mechanical systems and the constrained nature of the power flow is represented using power-phaseplane plots. We believe the approach we present will be useful for control design of both semi-active and low-power vibration suppression systems.
The generalised hold formulation of intermittent control is reexamined and shown to have some use... more The generalised hold formulation of intermittent control is reexamined and shown to have some useful theoretical and practical properties. It is shown that this provides a foundation for constrained model predictive control in an intermittent context. The method is illustrated using an example and verified with experimental results.
IEEE Transactions on Control Systems Technology, 2012
Repetitive control is a methodology for the tracking of a periodic reference signal. This paper d... more Repetitive control is a methodology for the tracking of a periodic reference signal. This paper develops a new approach to repetitive control systems design using receding horizon control with frequency decomposition of the reference signal. Moreover, design and implementation issues for this form of repetitive predictive control are investigated from the perspectives of controller complexity and the effects of measurement noise. The analysis is supported by a simulation study on a multi-input multi-output robot arm where the model has been constructed from measured frequency response data, and experimental results from application to an industrial AC motor.
This paper presents a heterogeneous configuration of the multirotor unmanned aerial system (UAS) ... more This paper presents a heterogeneous configuration of the multirotor unmanned aerial system (UAS) that features the combined characteristics of the helicopter and quadrotor in a single multirotor design, featuring the endurance and energy efficiency similar to a helicopter, while keeping the mechanical simplicity, control, and manoeuvrability of the standard quadrotor. Power needed for a rotorcraft to hover has the inverse relation with the rotor disc. Therefore, multiple small rotors of the quadrotor are energetically outperformed by a large rotor of the helicopter, for a similar size. Designing the stable control system for such a dynamically complex multirotor configuration remains the main challenge as the studies previously carried out on these designs have successfully demonstrated energy efficiency but at the cost of degraded attitude control. Advancements in the energetics of the multirotor results in enhanced endurance and range that could be highly effective in remote opera...
Journal of Automation, Mobile Robotics and Intelligent Systems
Different from conventional aircraft, an investigation on system identification and control desig... more Different from conventional aircraft, an investigation on system identification and control design has been carried out on a small fixed wing unmanned aerial vehicle (UAV) with a multi-segment ailerons. The multi-segment aileron setup is configured as a multi-input and single-output system and each segment is modeled as a control input. Experiments are conducted in a wind tunnel to determine the frequency responses of the system and the corresponding transfer functions. Multiple PID controllers are designed and implemented in a cascaded form for each control surface. Furthermore, a heuristic switching control strategy is implemented for the aircraft where the multi-segment ailerons perform as a single-segment aileron in a normal flight condition, and adapts to multi-segment control when encountering severe turbulence or a large angle reference change. Experimental results reveal that although each control surface has the capability for stabilization of the aircraft, the proposed con...
In this paper input power, as opposed to the usual input amplitude, constraints are introduced in... more In this paper input power, as opposed to the usual input amplitude, constraints are introduced in the context of intermittent control. They are shown to result in a combination of quadratic optimisation and quadratic constraints. The main motivation for considering input power constraints is its similarity with semi-active control. Such methods are commonly used to provide damping in mechanical systems and structures. It is shown that semi-active control can be re-expressed and generalised as control with power constraints and can thus be implemented as power-constrained intermittent control. The method is illustrated using simulations of resonant mechanical systems and the constrained nature of the power flow is represented using power-phaseplane plots. We believe the approach we present will be useful for control design of both semi-active and low-power vibration suppression systems.
This paper deals with data-driven predictive control for relative performance management in virtu... more This paper deals with data-driven predictive control for relative performance management in virtualized software system. The system dynamics are characterized in Hammerstein-Wiener structure to capture nonlinear and linear characteristics. The proposed control approach is the implementation of Subspace-based Predictive Control with the integration of nonlinear compensation. The compensator functions are inverse static input and output nonlinearity models from the Hammerstein-Wiener system identification. The subspace predictors are formulated from the linear model input and output of Wiener block. The experimental results from three scenarios of performance objectives show the reliability of Subspace-based Predictive Control to manage the virtualized software system.
This paper develops a new design method for predictive repetitive control systems to track period... more This paper develops a new design method for predictive repetitive control systems to track periodic reference signals or reject disturbances with bandlimited frequency content. In the presence of input disturbances acting on the system, the new design estimates these disturbances using an observer. This approach is complementary to the predictive repetitive control system designs previously reported where the periodic disturbance model was embedded in the controller. Supporting experimental results from application of the new design to a two joint robotic arm are given.
Integrating processes are widely encountered in electro-mechanical systems and other areas. Autom... more Integrating processes are widely encountered in electro-mechanical systems and other areas. Automatic tuning of PID controllers for this type of system requires special consideration since the underlying system is unstable. Using relay feedback control in a closed-loop setting, an auto-tuner is designed to systematically find the controller parameters using a frequency sampling filter model. The performance of this auto-tuner is evaluated on an electro-mechanical experimental test facility that can be configured to operate in either as a single-input, single-output or multiple-input, multipleoutput system. The experimental results demonstrate that when the interaction the between control loops is weak, the auto-tuner produces closed-loop performance that matches the specification, but this performance gradually decays as the level of interaction increases. The experimental results can also serve as experimental benchmarks to compare competing designs.
This paper addresses the performance of electric servo-actuators as part of a helicopter control ... more This paper addresses the performance of electric servo-actuators as part of a helicopter control linkage system. The development of a helicopter flight control system initially requires a non-linear model capable of accurately predicting the aircraft dynamics. The first step of this non-linear model represents the servo-actuator system, which transmits the pilots control inputs to the main rotor system. A series of system identification experiments were performed on a cyclic system servo-actuator under different operating conditions, and the servo-actuator step responses were estimated using a Frequency Sampling Filter. A performance comparison is made for a zero load bench test and the aircraft load condition in order to determine the most accurate representation of the servo-actuator dynamics for helicopter flight applications.
2008 47th IEEE Conference on Decision and Control, 2008
This paper seeks to extend Generalized Predictive Control (GPC) to tracking of trajectories in a ... more This paper seeks to extend Generalized Predictive Control (GPC) to tracking of trajectories in a periodic nature. The initial focus is on sinusoidal trajectories, but the work may be extended later on to a signal with bandlimited frequencies. In addition, this paper proposes strategies for optimizing the prefilter in GPC to improve the transient performance in setpoint tracking.
This paper develops a predictive iterative learning control algorithm starting from some recent r... more This paper develops a predictive iterative learning control algorithm starting from some recent results in the area of predictive repetitive control. Although similar in spirit to the original norm-optimal iterative learning control, the algorithm developed employs receding horizon control and Laguerre functions to parameterize the future control trajectory. As a result, difficulties encountered by the norm-optimal iterative control algorithm are overcome. The stability of the predictive iterative learning system is analyzed and conditions on error convergence are established. In addition, a strategy for learning the unknown plant initial conditions and the reduction of the initial plant errors is developed. A simulation example to illustrate the algorithm is also given.
This paper examines the design of model predictive control using nonminimal state space models, i... more This paper examines the design of model predictive control using nonminimal state space models, in which the state variables are chosen as the set of measured input and output variables and their past values. It shows that the proposed design approach avoids the use of an observer to access the state information and, as a result, the disturbance rejection, particularly the system input disturbance rejection, is significantly improved when constraints become activated. In addition, the paper shows that the system output constraints can be achieved in the proposed approach, which provides a significant improvement over the general observer based approach.
This paper derives the algorithm of integral plus finite control set (FCS)-predictive control for... more This paper derives the algorithm of integral plus finite control set (FCS)-predictive control for AC motor drives. In the paper, it is shown that the original FCS-predictive control algorithm in the d−q reference frame is equivalent to a dead-beat control system in the presence of constraints, where the closed-loop system is approximated by a unit time delay. Without integral action, the original FCS-predictive control system contains steady-state errors in both daxis and q-axis currents, hence compromising closed-loop performance. Using an integral control in a cascaded structure to the original FCS-predictive control, a simple algorithm is proposed to eliminate the steady-state errors of the current control system and improve its closed-loop performance. The sampling interval of the current control system is used as a performance tuning parameter for reduction of current variations. Furthermore, the algorithm is expressed in a velocity form for convenience in implementation using a digital signal processor. Experimental results are used to show the successful design and implementation of the integral finite control set (I-FCS) predictive control.
This paper proposes a continuous-time model predictive control design for disturbance rejection a... more This paper proposes a continuous-time model predictive control design for disturbance rejection and set-point following of periodic signals. By assuming input disturbance in the form of sinusoid, the periodic frequency is embedded into the design model. Hence, from internal model principle, the steady-state error of the model predictive control system is ensured to be zero for both disturbance rejection and set-point following. Furthermore, with the design framework of model predictive control, hard constraints on the derivative and amplitude of the control signals are imposed as part of the performance specification. Simulation studies have been used to show the efficacy of the design with or without hard constraints.
The nature of active magnetic bearings has many advantages over the conventional bearing, as its ... more The nature of active magnetic bearings has many advantages over the conventional bearing, as its operation is energy efficient and potentially leads to cleaner and noise-free environment. However, the successful operation of an active magnetic bearing system requires a complex real-time control system, because of its unstable characteristics, as well as its nature of being a multi-input and multi-output system. This paper presents design and implementation of a continuous time model predictive control algorithm (CMPC) to an active magnetic bearing system (AMB). In this application, the plant continuous time model is identified from experimental data using prediction error method. The control performance of this algorithm is studied using an experimental AMB laboratory system. A host-target development environment of real-time digital control system with hardware in the loop (HIL) is implemented and demonstrated by controlling a nonlinear, open-loop unstable, and multivariable magnetic levitation device.
A three-stage approach to system identification in the continuous-time is presented which is appr... more A three-stage approach to system identification in the continuous-time is presented which is appropriate for day-today application by plant engineers in the process industry. The three stages are: data acquisition using relay feedback; non-parametric identification of the system step response; and parametric model fitting of the identified step-response. The method is evaluated on a pilotscale food-cooking extruder.
In this paper input power, as opposed to the usual input amplitude, constraints are introduced in... more In this paper input power, as opposed to the usual input amplitude, constraints are introduced in the context of intermittent control. They are shown to result in a combination of quadratic optimisation and quadratic constraints. The main motivation for considering input power constraints is its similarity with semi-active control. Such methods are commonly used to provide damping in mechanical systems and structures. It is shown that semi-active control can be re-expressed and generalised as control with power constraints and can thus be implemented as power-constrained intermittent control. The method is illustrated using simulations of resonant mechanical systems and the constrained nature of the power flow is represented using power-phaseplane plots. We believe the approach we present will be useful for control design of both semi-active and low-power vibration suppression systems.
The generalised hold formulation of intermittent control is reexamined and shown to have some use... more The generalised hold formulation of intermittent control is reexamined and shown to have some useful theoretical and practical properties. It is shown that this provides a foundation for constrained model predictive control in an intermittent context. The method is illustrated using an example and verified with experimental results.
IEEE Transactions on Control Systems Technology, 2012
Repetitive control is a methodology for the tracking of a periodic reference signal. This paper d... more Repetitive control is a methodology for the tracking of a periodic reference signal. This paper develops a new approach to repetitive control systems design using receding horizon control with frequency decomposition of the reference signal. Moreover, design and implementation issues for this form of repetitive predictive control are investigated from the perspectives of controller complexity and the effects of measurement noise. The analysis is supported by a simulation study on a multi-input multi-output robot arm where the model has been constructed from measured frequency response data, and experimental results from application to an industrial AC motor.
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Papers by Liuping Wang